CN117578948B - Permanent magnet motor operation deviation self-adaptive regulation and control method and system - Google Patents

Abstract

The application discloses a permanent magnet motor operation deviation self-adaptive regulation and control method and a system, and relates to the technical field of motor operation control, wherein the method comprises the following steps: acquiring motor basic information and motor operation tasks of a permanent magnet motor; performing motor control decision analysis to obtain a motor control scheme; performing deviation verification computing force analysis on the permanent magnet motor to obtain a deviation verification computing force analysis result, and executing deviation verification node layout of a motor control scheme; controlling the permanent magnet motor according to a motor control scheme, and controlling feedback monitoring in real time; according to the motor control scheme, matching real-time motor control node decision; and carrying out multidimensional deviation regulation and control analysis on the real-time control feedback data according to the real-time motor control node decision, generating a motor deviation regulation and control scheme, and carrying out deviation self-adaptive regulation and control on the permanent magnet motor. Thereby achieving the technical effects of reducing the running deviation and improving the performance and stability of the permanent magnet synchronous motor.

Description

Permanent magnet motor operation deviation self-adaptive regulation and control method and system

Technical Field

The invention relates to the technical field of motor operation control, in particular to a permanent magnet motor operation deviation self-adaptive regulation and control method and system.

Background

Permanent Magnet Synchronous Motors (PMSMs) are a type of motor widely used in the fields of industry and electric vehicles, etc. Compared with a direct current motor, the PMSM has the advantages of simple structure, small volume, light weight, small loss, high efficiency, no defects of a commutator, a brush and the like of the direct current motor. Compared with an asynchronous motor, the PMSM has the advantages of high efficiency, high power factor, large moment inertia ratio, reduced stator current and stator resistance loss, measurable rotor parameters, good control performance, high efficiency, high power density and accurate control characteristics because reactive exciting current is not needed. However, the technical problem that the performance and stability of the permanent magnet synchronous motor are affected by the operation deviation of the PMSM still exists in the operation process.

Disclosure of Invention

The application aims to provide a permanent magnet motor running deviation self-adaptive regulation and control method and system. The method is used for solving the technical problem that the running deviation in the prior art affects the performance and stability of the permanent magnet synchronous motor.

In view of the technical problems, the application provides a permanent magnet motor operation deviation self-adaptive regulation and control method and system.

In a first aspect, the application provides a permanent magnet motor operation deviation adaptive regulation and control method, wherein the method comprises the following steps:

the motor data management terminal is connected, motor basic information and motor operation tasks of the permanent magnet motor are read, wherein the motor operation tasks comprise H-level motor operation loads of the permanent magnet motor, and H is a positive integer greater than 1; performing motor control decision analysis based on the motor basic information and the motor operation task to obtain a motor control scheme, wherein the motor control scheme comprises H motor control node decisions corresponding to the H-level motor operation load; performing deviation verification computing power analysis on the permanent magnet motor to obtain a deviation verification computing power analysis result, and executing deviation verification node layout of the motor control scheme based on the deviation verification computing power analysis result to obtain H deviation verification time domains corresponding to the decisions of the H motor control nodes; transmitting the motor control scheme to the motor regulation and control end, controlling the permanent magnet motor according to the motor control scheme, and performing real-time control feedback monitoring on the permanent magnet motor according to the H deviation verification time domains to obtain real-time control feedback data, wherein the real-time control feedback data has a real-time deviation verification time node corresponding to the mark; according to the motor control scheme, matching the real-time motor control node decision corresponding to the real-time deviation verification time node; based on a motor deviation regulation sub-module, multidimensional deviation regulation analysis is carried out on the real-time control feedback data according to the real-time motor control node decision, a motor deviation regulation scheme is generated, the motor deviation regulation scheme is transmitted to a motor regulation end, and deviation self-adaptive regulation is carried out on the permanent magnet motor according to the motor deviation regulation scheme.

In a second aspect, the present application further provides a permanent magnet motor operation deviation adaptive regulation and control system, where the system includes:

The information acquisition module is used for connecting the motor data management end, and reading motor basic information and motor operation tasks of the permanent magnet motor, wherein the motor operation tasks comprise H-level motor operation loads of the permanent magnet motor, and H is a positive integer greater than 1; the motor control decision analysis module is used for carrying out motor control decision analysis based on the motor basic information and the motor operation task to obtain a motor control scheme, wherein the motor control scheme comprises H motor control node decisions corresponding to the H-level motor operation load; the verification layout module is used for carrying out deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, and executing deviation verification node layout of the motor control scheme based on the deviation verification calculation force analysis result to obtain H deviation verification time domains corresponding to the H motor control node decisions; the real-time monitoring feedback module is used for transmitting the motor control scheme to the motor regulation and control end, controlling the permanent magnet motor according to the motor control scheme, performing real-time control feedback monitoring on the permanent magnet motor according to the H deviation verification time domains to obtain real-time control feedback data, wherein the real-time control feedback data has a real-time deviation verification time node corresponding to the mark; the node decision mapping module is used for matching the real-time motor control node decision corresponding to the real-time deviation verification time node according to the motor control scheme; the motor deviation regulation and control module is used for carrying out multidimensional deviation regulation and control analysis on the real-time control feedback data according to the real-time motor control node decision based on the motor deviation regulation and control submodule, generating a motor deviation regulation and control scheme, transmitting the motor deviation regulation and control scheme to the motor regulation and control end, and carrying out deviation self-adaptive regulation and control on the permanent magnet motor according to the motor deviation regulation and control scheme.

One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:

the motor basic information and motor operation tasks of the permanent magnet motor are read through connecting the motor data management end; based on the motor basic information and the motor operation task, performing motor control decision analysis to obtain a motor control scheme; performing deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, and executing deviation verification node layout of a motor control scheme based on the deviation verification calculation force analysis result to obtain H deviation verification time domains corresponding to H motor control node decisions; transmitting a motor control scheme to a motor regulation and control end, controlling the permanent magnet motor according to the motor control scheme, and carrying out real-time control feedback monitoring on the permanent magnet motor according to H deviation verification time domains to obtain real-time control feedback data, wherein the real-time control feedback data has a real-time deviation verification time node corresponding to the mark; according to the motor control scheme, matching real-time motor control node decisions corresponding to the real-time deviation verification time nodes; based on the motor deviation regulation sub-module, the real-time control feedback data is subjected to multidimensional deviation regulation analysis according to real-time motor control node decision, a motor deviation regulation scheme is generated, the motor deviation regulation scheme is transmitted to a motor regulation end, and the permanent magnet motor is subjected to deviation self-adaptive regulation according to the motor deviation regulation scheme. Thereby achieving the technical effects of reducing the running deviation and improving the performance and stability of the permanent magnet synchronous motor.

The foregoing description is only an overview of the present application, and is intended to more clearly illustrate the technical means of the present application, be implemented according to the content of the specification, and be more apparent in view of the above and other objects, features and advantages of the present application, as follows.

Drawings

Embodiments of the invention and the following brief description are described with reference to the drawings, in which:

FIG. 1 is a schematic flow chart of a permanent magnet motor operation deviation adaptive control method of the present application;

FIG. 2 is a schematic flow chart of a motor control scheme obtained in a permanent magnet motor operation deviation adaptive control method of the present application;

Fig. 3 is a schematic structural diagram of a permanent magnet motor operation deviation adaptive control system according to the present application.

Reference numerals illustrate: the system comprises an information acquisition module 11, a motor control decision analysis module 12, a verification layout module 13, a real-time monitoring feedback module 14, a node decision mapping module 15 and a motor deviation regulation and control module 16.

Detailed Description

The application provides a permanent magnet motor operation deviation self-adaptive regulation and control method and system, which solve the technical problem that the operation deviation influences the performance and stability of a permanent magnet synchronous motor in the prior art.

In order to solve the above problems, the technical embodiment adopts the following overall concept:

Connecting a motor data management end to acquire motor basic information and motor operation tasks of the permanent magnet motor; based on the motor basic information and the motor operation task, performing motor control decision analysis to obtain a motor control scheme; performing deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, and executing deviation verification node layout of a motor control scheme to obtain H deviation verification time domains corresponding to H motor control node decisions; transmitting a motor control scheme to a motor-based regulation and control end, controlling the permanent magnet motor according to the motor control scheme, and controlling feedback monitoring in real time; according to the motor control scheme, matching real-time motor control node decisions corresponding to the real-time deviation verification time nodes; and carrying out multidimensional deviation regulation and control analysis on the real-time control feedback data according to the real-time motor control node decision, generating a motor deviation regulation and control scheme, and carrying out deviation self-adaptive regulation and control on the permanent magnet motor. Thereby achieving the technical effects of reducing the running deviation and improving the performance and stability of the permanent magnet synchronous motor.

The motor basic information and motor operation tasks of the permanent magnet motor are read through connecting the motor data management end; based on the motor basic information and the motor operation task, performing motor control decision analysis to obtain a motor control scheme; performing deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, and executing deviation verification node layout of a motor control scheme based on the deviation verification calculation force analysis result to obtain H deviation verification time domains corresponding to H motor control node decisions; based on a motor regulation and control end, controlling the permanent magnet motor according to a motor control scheme, and performing real-time control feedback monitoring on the permanent magnet motor to obtain real-time control feedback data; according to the motor control scheme, matching real-time motor control node decisions corresponding to the real-time deviation verification time nodes; based on the motor deviation regulation sub-module, the real-time control feedback data is subjected to multidimensional deviation regulation analysis according to real-time motor control node decision, a motor deviation regulation scheme is generated, the motor deviation regulation scheme is transmitted to a motor regulation end, and the permanent magnet motor is subjected to deviation self-adaptive regulation according to the motor deviation regulation scheme. Thereby achieving the technical effects of reducing the running deviation and improving the performance and stability of the permanent magnet synchronous motor.

In order to better understand the above technical solutions, the following detailed description will be given with reference to the accompanying drawings and specific embodiments, and it should be noted that the described embodiments are only some embodiments of the present application, and not all embodiments of the present application, and it should be understood that the present application is not limited by the exemplary embodiments described herein. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to fall within the scope of the application. It should be further noted that, for convenience of description, only some, but not all of the drawings related to the present application are shown.

Example 1

As shown in fig. 1, the application provides a permanent magnet motor operation deviation self-adaptive regulation and control method, which comprises the following steps:

S100: the motor data management terminal is connected, motor basic information and motor operation tasks of the permanent magnet motor are read, wherein the motor operation tasks comprise H-level motor operation loads of the permanent magnet motor, and H is a positive integer greater than 1;

Optionally, a communication connection with the motor data management is first established. Through a network connection, API call, serial communication, or other suitable communication means. And the motor data management end stores motor basic information and motor operation tasks of the target PMSM.

Optionally, a request is sent to a motor data management end, and the motor data management end extracts basic information of the permanent magnet motor based on the request. The basic information of the permanent magnet motor comprises motor model, rated parameters (such as rated power, rated current, rated rotating speed and the like), manufacturer information and the like. H-level motor operation loads of the permanent magnet motor included in the motor operation task correspond to H motor operation load states respectively, and reflect H working conditions of the target PMSM in the target working environment. Further, the H-stage motor operates in a load state. The H-level motor operation load state parameters comprise operation conditions under different loads, target working conditions or working modes and the like.

Optionally, the motor basic information and the motor operation task of the permanent magnet motor are read, and the motor basic information and the motor operation task are realized by performing data mining processing on data stored by a motor data management end. The motor data management end stores data with a motor model label and a time node label. And the basic information and the motor operation task matched with the target PMSM are conveniently and efficiently acquired.

S200: performing motor control decision analysis based on the motor basic information and the motor operation task to obtain a motor control scheme, wherein the motor control scheme comprises H motor control node decisions corresponding to the H-level motor operation load;

And carrying out motor control decision analysis based on motor basic information and motor operation tasks, and determining how to control the permanent magnet motor to meet the requirements under different load conditions. Optionally, the motor control scheme determines a motor control node decision corresponding to each H-level motor operation load state based on the motor parameters and the control strategy. Including setting a target speed, a target torque, a current limit, etc. of the motor. For each motor control node, the control logic is written to achieve the desired motor operating state. To the operations of starting, stopping, accelerating, decelerating, steering, etc. of the motor.

Further, as shown in fig. 2, based on the motor basic information and the motor operation task, a motor control decision analysis is performed to obtain a motor control scheme, and step S200 includes:

obtaining motor operation time sequence constraint of the motor operation task, sequencing the motor operation task according to the motor operation time sequence constraint, and generating a motor operation first load and a motor operation second load … motor operation H load;

Performing motor control record inquiry based on the motor basic information and the motor operation task to obtain a motor control record library;

Based on the motor control record library, according to the motor basic information, motor control decision matching is respectively carried out on the motor operation first load and the motor operation second load … and the motor operation H load, and a first motor control node decision and a second motor control node decision … H motor control node decision are generated;

And generating the motor control scheme according to the first motor control node decision and the second motor control node decision … and the H motor control node decision.

Optionally, the motor job timing constraint of the motor job task is a job feature in a motor job task time dimension, including a duration, a sequence, and the like of the motor job task. The motor operation tasks are ordered through the motor operation time sequence constraint, so that the ordering of H motor loads is realized, and the sequence relation of the motor operation tasks is determined.

In the motor control record inquiry, motor basic information and motor operation tasks are inquiry constraint parameters. Optionally, the motor control records adapting to the basic information and the motor operation tasks of the motor are traversed and screened through the interaction big data motor control record set, and a plurality of motor control records are stored in a motor control record library. The motor control record comprises motor basic information, motor operation task information, motor control parameter information, motor control instruction information and the like.

Optionally, motor control decision matching is performed on the motor operation first load and the motor operation second load … motor operation H load respectively, a first motor control node decision and a second motor control node decision … H motor control node decision are generated, and the motor control decision matching is realized based on the feature matching technology principle. Illustratively, the historical data is feature extracted to identify key features associated with different load conditions. These characteristics include motor current, voltage, rotational speed, temperature, etc. And then, according to the current electronic work load characteristics of the current PMSM, carrying out similarity calculation on the characteristic extraction result in the historical data. And then the motor control decision with the highest similarity is obtained as a motor control decision matching result.

Optionally, the motor control scheme includes a first motor control node decision, a second motor control node decision … and an H motor control node decision, where the H motor control node decisions have the same ordering relationship with the motor operation first load and the motor operation second load … and the motor operation H load.

S300: performing deviation verification computing power analysis on the permanent magnet motor to obtain a deviation verification computing power analysis result, and executing deviation verification node layout of the motor control scheme based on the deviation verification computing power analysis result to obtain H deviation verification time domains corresponding to the decisions of the H motor control nodes;

And performing deviation verification calculation force analysis on the permanent magnet motor, wherein the deviation verification calculation force analysis is used for determining the deviation regulation and control intensity of the target PMSM, and if the deviation regulation and control intensity of the target PMSM is high, more strict deviation verification is required to be performed on the target PMSM, so that a corresponding deviation verification calculation force analysis result is obtained.

Optionally, determining a node that needs to be subjected to deviation verification based on the deviation verification calculation force analysis result. These nodes may include motor control parameters, sensor calibration, environmental conditions, and the like. In addition, the deviation verification time domain refers to a verification sampling time plan of the distributed deviation verification nodes, and the verification sampling time plan comprises verification intervals, verification time nodes and the like. The method is used for providing the monitoring and verification of the motor performance at different time points or working conditions.

Further, performing deviation verification calculation analysis on the permanent magnet motor to obtain a deviation verification calculation analysis result, wherein step S300 includes:

Obtaining N-level historical time zone constraint, and setting N-level time zone gradual change weight corresponding to the N-level historical time zone constraint, wherein N is a positive integer greater than 1;

reading the historical operation deviation record of the permanent magnet motor according to the N-level historical time zone constraint, and obtaining N operation deviation record libraries corresponding to the N-level historical time zone constraint;

traversing the N operation deviation record libraries to count operation deviation record times to obtain N time zone deviation triggering times;

Weighting calculation is carried out on the N time zone deviation triggering times based on the N-level time zone gradual change weight, and motor operation deviation triggering degrees are generated;

constructing a motor deviation verification computing power configuration table, wherein the motor deviation verification computing power configuration table comprises a plurality of preset motor operation deviation trigger degree intervals and a plurality of preset motor deviation verification computing powers;

And inputting the motor operation deviation triggering degree into the motor deviation verification computing force configuration table, obtaining a matched motor deviation verification computing force corresponding to the motor operation deviation triggering degree, and outputting the matched motor deviation verification computing force as the deviation verification computing force analysis result.

Optionally, the N-level historical time zone constraint is used to divide the historical time into N-level time zones, where the N-level time zones in the N-level historical time zone constraint have corresponding N-level time zone gradual change weights. The N-level time zone gradual change weight is inversely proportional to the time difference between the historical time zone and the current time. I.e., the smaller the time difference, the closer the historical time zone is to the current time zone, and the higher the weight. The weights are adjusted according to the correlation of the historical time zones to better reflect the impact of the past time period on the current question.

Alternatively, the setting of the N-level time zone gradation weight may use an exponential function, a logarithmic function, a linear function, or the like. The N-level time zone gradual weights are normalized to ensure that their sum equals 1.

The N time zone deviation triggering times are the deviation recording times in N operation deviation record libraries, namely the deviation recording frequency information of different historical time zones. And carrying out weighted calculation on the N time zone deviation triggering times based on the N-level time zone gradual change weight, and multiplying the corresponding deviation triggering times with the corresponding time zone gradual change weight for each historical time zone. All N results are then added to generate the motor run bias trigger. To better reflect the effect of the past period on motor operation.

Optionally, the motor deviation verification computing power configuration table establishes a mapping relation between the motor operation deviation triggering degree and the motor deviation verification computing power. Illustratively, first, different intervals of motor operation deviation trigger degrees are determined. These intervals are defined according to specific regulatory requirements and motor operating conditions. Each interval represents a range within which motors with a trigger level will be assigned a corresponding computing power configuration. Then, for each trigger metric interval, a corresponding motor deviation verification algorithm is determined. Wherein the computing force may be a number indicating how much computing force resources the motors within the interval will allocate. The motor deviation verification calculation force is determined according to the system performance requirement and the importance of the motor.

Optionally, the motor operation and trigger level are checked periodically, and the configuration table is updated as needed to reflect new requirements or motor performance. Proper verification calculation force can be distributed to the motor according to different running deviation conditions, and stability and performance of self-adaptive regulation and control are achieved.

Further, obtaining H deviation verification time domains corresponding to the H motor control node decisions, where step S300 includes:

based on the N operation deviation record libraries, performing operation deviation association triggering degree calculation on a first motor control node decision to obtain a first node operation deviation association triggering degree;

Based on the N operation deviation record libraries, continuously calculating operation deviation association triggering degrees of H motor control node decisions of a second motor control node decision …, obtaining H node operation deviation association triggering degrees of a second node operation deviation association triggering degree …, and generating H node operation deviation association triggering degrees corresponding to the H motor control node decisions by combining the first node operation deviation association triggering degrees;

Based on a preset node operation deviation association triggering degree, respectively adjusting the deviation verification computing power analysis result according to the H node operation deviation association triggering degrees to obtain H node deviation verification computing powers;

and based on the H node deviation verification calculation forces, respectively carrying out deviation verification time node setting on the H motor control node decisions, and generating H deviation verification time domains, wherein each deviation verification time domain comprises a plurality of deviation verification time nodes corresponding to each motor control node decision.

Optionally, the preset node operation deviation association triggering degree reflects the influence of an unreliability part in the node operation deviation triggering degree, namely the influence degree of the system error on the node operation deviation association triggering degree, which includes monitoring instrument error, motor tolerance and the like.

Optionally, based on the preset node operation deviation association triggering degree, the deviation verification calculation force analysis result is adjusted according to the H node operation deviation association triggering degrees, and the adjustment algorithm is used for carrying out. Based on the adjustment algorithm, according to the triggering degree data of each node, the triggering degree is converted into a weight or coefficient of the calculation force, and a corresponding adjustment value is calculated, so that H node deviation verification calculation forces are obtained. To more accurately reflect the contribution and impact of each node. This helps to improve the efficiency and performance of the adaptive modulation.

Optionally, each deviation verification time domain includes a plurality of deviation verification time nodes corresponding to each motor control node decision. And, the greater the node deviation verification calculation power, the denser the deviation verification time nodes in the corresponding deviation verification time domain.

Further, based on the N operation deviation record libraries, operation deviation association triggering degrees are calculated for the first motor control node decision, and a first node operation deviation association triggering degree is obtained, and the steps further include:

Based on the first motor control node decision, respectively extracting associated operation deviation records of the N operation deviation record libraries to obtain N associated operation deviation record libraries corresponding to the first motor control node decision;

traversing the N associated operation deviation record libraries to count operation deviation record times, and obtaining N associated time zone deviation triggering times;

And carrying out weighted calculation on the N associated time zone deviation triggering times based on the N-level time zone gradual change weight, and generating the first node operation deviation associated triggering degree.

Optionally, traversing the N related operation deviation record libraries to count the operation deviation record times to obtain N related time zone deviation trigger times, counting the operation deviation record times based on the traversed N operation deviation record libraries to obtain N time zone deviation trigger times, and giving the trigger times of each record library. It should be understood that for brevity of description, no further development is made here.

And weighting and calculating the triggering times of each associated time zone deviation by using the N-level time zone gradual change weight. Time zones closer to the current time will have higher weights and time zones farther away will have lower weights. To more accurately reflect the influence of the running deviation of different time zones on node decision, and to better understand and respond to the running deviation of different time zones.

S400: transmitting the motor control scheme to the motor regulation and control end, controlling the permanent magnet motor according to the motor control scheme, and performing real-time control feedback monitoring on the permanent magnet motor according to the H deviation verification time domains to obtain real-time control feedback data, wherein the real-time control feedback data has a real-time deviation verification time node corresponding to the mark;

wherein, transmit the motor control scheme to the motor regulation and control end. The motor control scheme includes a control strategy for the permanent magnet motor for controlling different motor operating load conditions. And controlling the permanent magnet motor in real time, and controlling the motor to meet the required motor operation load state. And simultaneously, carrying out real-time feedback monitoring to obtain real-time control feedback data. These data include state information of the motor at different time nodes and parameters related to control objectives and performance. Each data point has a corresponding identified real-time bias verification time node ensuring that the performance and behavior of the motor can be tracked over time. And then the control strategy of the motor is adjusted according to the real-time data so as to meet the performance and load requirements, and the efficiency and stability of the permanent magnet motor are improved.

S500: according to the motor control scheme, matching the real-time motor control node decision corresponding to the real-time deviation verification time node;

Optionally, the real-time motor control node decision corresponding to the real-time deviation verification time node refers to a motor control node decision with a deviation phenomenon discovered in real-time monitoring. Matching the real-time deviation verification time node with the closest motor control node decision, relating to the comparison of time stamps, and finding the closest real-time motor control node decision. Through the matching process, more accurate motor control is realized, and the motor is ensured to be properly adjusted according to real-time conditions at different time points so as to meet the performance and load requirements.

S600: based on a motor deviation regulation sub-module, multidimensional deviation regulation analysis is carried out on the real-time control feedback data according to the real-time motor control node decision, a motor deviation regulation scheme is generated, the motor deviation regulation scheme is transmitted to a motor regulation end, and deviation self-adaptive regulation is carried out on the permanent magnet motor according to the motor deviation regulation scheme.

Optionally, the multidimensional deviation regulation analysis refers to regulation analysis performed by using different performance indexes or parameters from multiple dimensions, selecting the performance indexes or parameters to be regulated, and determining the adjustment amount of the performance indexes or parameters to be regulated.

Optionally, a motor bias control scheme is generated based on the multi-dimensional bias analysis. The regulation scheme includes real-time adjustment recommendations for motor control parameters to minimize bias and meet performance and load requirements. Illustratively, it relates to adjusting parameters of current, speed, torque, etc. to optimize operation of the motor. In addition, the generated regulation scheme is transmitted to the permanent magnet motor to implement real-time adjustment. By way of example, this is achieved by adjusting the parameters of the PID controller for each load state, and thus changing the output of the motor controller, ensuring that the motor maintains optimal performance in different operating states.

Further, based on the motor deviation regulation sub-module, the real-time control feedback data is subjected to multidimensional deviation regulation analysis according to the real-time motor control node decision, and a motor deviation regulation scheme is generated, and step S600 includes:

extracting a plurality of index control reference data corresponding to a plurality of motor control indexes from the real-time motor control node decision;

carrying out random numbering based on the motor control indexes to obtain a first motor control index, a second motor control index … and a Kth motor control index, wherein the K value is the total number of the motor control indexes;

based on the motor deviation regulation sub-module, carrying out deviation regulation on the real-time control feedback data according to the first motor control index to obtain a first index deviation regulation decision;

Based on the motor deviation regulation sub-module, respectively carrying out deviation regulation on the real-time control feedback data according to the K-th motor control index of the second motor control index … to obtain a K-th index deviation regulation decision of a second index deviation regulation decision …;

And generating the motor deviation regulation scheme according to the first index deviation regulation decision and the K index deviation regulation decision of the second index deviation regulation decision ….

Wherein each motor control index has corresponding reference data. Alternatively, these baseline data are measured or calculated under normal operating conditions and represent the expected performance of the motor under certain operating conditions.

Optionally, the motor deviation regulation submodule includes control logic of each motor control node, and is used for converting the motor control index into the running operation action of the motor through the control logic. To achieve the desired motor operating conditions. The control logic of the motor deviation regulating sub-module relates to the operation actions such as starting, stopping, accelerating, decelerating, steering and the like of the motor.

Further, based on the motor deviation regulation sub-module, performing deviation regulation on the real-time control feedback data according to the first motor control index to obtain a first index deviation regulation decision, and the steps further include:

Based on the first motor control index, matching first index control reference data according to the plurality of index control reference data;

Based on the first motor control index, matching first index control feedback data according to the real-time control feedback data;

Comparing the first index control reference data with the first index control feedback data to obtain a first index control comparison degree;

Judging whether the first index control comparison degree is smaller than a preset control comparison degree or not;

if the first index control comparison degree is greater than/equal to the preset control comparison degree, a first index deviation regulation instruction is obtained; and judge

Activating a first index deviation regulating network corresponding to the first motor control index in the motor deviation regulating sub-module based on the first index deviation regulating instruction, wherein the motor deviation regulating sub-module comprises index deviation regulating networks corresponding to all motor control indexes constructed in advance;

And inputting the first index control comparison degree, the first index control reference data and the first index control feedback data into the first index deviation regulation and control network to generate the first index deviation regulation and control decision.

Optionally, the data in the real-time motor control node decision is compared with corresponding index control reference data. For determining whether the actual performance of the motor in the current operating state corresponds to the desired performance. The first index control comparison degree is obtained by comparing the first index control reference data with the first index control feedback data, and the relation between the first index control comparison degree and the preset control comparison degree is judged.

Optionally, if the first index control comparison degree is smaller than the preset control comparison degree, the corresponding first index deviation regulation decision is recorded as 0, and at this time, the corresponding first index does not need to be regulated.

Optionally, the motor deviation regulation sub-module includes a plurality of index deviation regulation networks, each network corresponding to a motor control index. The index deviation regulation and control network is used for generating a first index deviation regulation and control decision according to the first index control comparison degree, the first index control reference data and the first index control feedback data.

Optionally, the index deviation regulation network is constructed based on a neural network model. The index deviation regulation and control network takes the first index control comparison degree, the first index control reference data and the first index control feedback data as inputs, and the first index deviation regulation and control decision as outputs. Illustratively, the pre-construction of the index bias control network begins with collecting sufficient data as a dataset for training the neural network. These data include inputs (control signals) and outputs (performance indicators such as current, speed, temperature, etc.) of the motor. The data is then pre-processed, including normalization, or other necessary processing, to ensure availability of the data, which can have a positive effect on the training of the neural network. Next, the architecture of the neural network is selected, including the number of layers, the number of neurons per layer, and the activation function, and a loss function is defined that measures the difference between the actual output and the desired output, optionally using a mean square error (Mean Squared Error) as the loss function. The neural network is then trained using the data set. Network parameters and weights are adjusted by gradient descent or other optimization algorithms to minimize the loss function. Model verification and testing is then performed using data not included in the training data to evaluate the performance of the neural network, which is embedded in the motor bias control sub-module once model training is complete.

In summary, the permanent magnet motor operation deviation self-adaptive regulation and control method provided by the invention has the following technical effects:

the motor basic information and motor operation tasks of the permanent magnet motor are read through connecting the motor data management end; based on the motor basic information and the motor operation task, performing motor control decision analysis to obtain a motor control scheme; performing deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, and executing deviation verification node layout of a motor control scheme based on the deviation verification calculation force analysis result to obtain H deviation verification time domains corresponding to H motor control node decisions; transmitting a motor control scheme to a motor regulation and control end, controlling the permanent magnet motor according to the motor control scheme, and carrying out real-time control feedback monitoring on the permanent magnet motor according to H deviation verification time domains to obtain real-time control feedback data, wherein the real-time control feedback data has a real-time deviation verification time node corresponding to the mark; according to the motor control scheme, matching real-time motor control node decisions corresponding to the real-time deviation verification time nodes; based on the motor deviation regulation sub-module, the real-time control feedback data is subjected to multidimensional deviation regulation analysis according to real-time motor control node decision, a motor deviation regulation scheme is generated, the motor deviation regulation scheme is transmitted to a motor regulation end, and the permanent magnet motor is subjected to deviation self-adaptive regulation according to the motor deviation regulation scheme. Thereby achieving the technical effects of reducing the running deviation and improving the performance and stability of the permanent magnet synchronous motor.

Example two

Based on the same concept as the permanent magnet motor operation deviation adaptive regulation method in the embodiment, as shown in fig. 3, the application further provides a permanent magnet motor operation deviation adaptive regulation system, which comprises:

The information acquisition module 11 is used for connecting the motor data management end, and reading motor basic information and motor operation tasks of the permanent magnet motor, wherein the motor operation tasks comprise H-level motor operation loads of the permanent magnet motor, and H is a positive integer greater than 1;

The motor control decision analysis module 12 is configured to perform motor control decision analysis based on the motor basic information and the motor operation task, so as to obtain a motor control scheme, where the motor control scheme includes H motor control node decisions corresponding to the H-level motor operation load;

The verification layout module 13 is used for carrying out deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, and executing deviation verification node layout of the motor control scheme based on the deviation verification calculation force analysis result to obtain H deviation verification time domains corresponding to the H motor control node decisions;

the real-time monitoring feedback module 14 is configured to transmit the motor control scheme to the motor regulation end, control the permanent magnet motor according to the motor control scheme, and perform real-time control feedback monitoring on the permanent magnet motor according to the H deviation verification time domains, so as to obtain real-time control feedback data, where the real-time control feedback data has a real-time deviation verification time node corresponding to the identifier;

the node decision mapping module 15 is configured to match the real-time motor control node decision corresponding to the real-time deviation verification time node according to the motor control scheme;

The motor deviation regulation and control module 16 is configured to perform multidimensional deviation regulation and control analysis on the real-time control feedback data according to the real-time motor control node decision, generate a motor deviation regulation and control scheme, transmit the motor deviation regulation and control scheme to the motor regulation and control end, and perform deviation self-adaptive regulation and control on the permanent magnet motor according to the motor deviation regulation and control scheme.

Further, the motor control decision analysis module 12 further includes:

The operation task serialization unit is used for obtaining motor operation time sequence constraint of the motor operation tasks, and sequencing the motor operation tasks according to the motor operation time sequence constraint to generate a motor operation first load and a motor operation second load … motor operation H load;

The control record inquiring unit is used for inquiring the motor control record based on the motor basic information and the motor operation task to obtain a motor control record library;

the control decision matching unit is used for respectively carrying out motor control decision matching on the motor operation first load and the motor operation second load … and the motor operation H load according to the motor basic information based on the motor control record library to generate a first motor control node decision and a second motor control node decision … H motor control node decision;

And the control scheme generating unit is used for generating the motor control scheme according to the first motor control node decision and the second motor control node decision … and the H motor control node decision.

Further, the verification layout module 13 further includes:

the history time zone weight constraint unit is used for obtaining N-level history time zone constraints and setting N-level time zone gradual change weights corresponding to the N-level history time zone constraints, wherein N is a positive integer greater than 1;

The deviation record extraction unit is used for reading the historical operation deviation record of the permanent magnet motor according to the N-level historical time zone constraint and obtaining N operation deviation record libraries corresponding to the N-level historical time zone constraint;

the deviation frequency counting unit is used for traversing the N operation deviation record libraries to count the operation deviation record times and obtain N time zone deviation triggering times;

The operation deviation triggering degree unit is used for carrying out weighted calculation on the N time zone deviation triggering times based on the N-level time zone gradual change weight to generate motor operation deviation triggering degree;

the configuration table construction unit is used for constructing a motor deviation verification computing power configuration table, wherein the motor deviation verification computing power configuration table comprises a plurality of preset motor operation deviation trigger degree intervals and a plurality of preset motor deviation verification computing powers;

The calculation force matching unit is used for inputting the motor operation deviation triggering degree into the motor deviation verification calculation force configuration table, obtaining the matched motor deviation verification calculation force corresponding to the motor operation deviation triggering degree, and outputting the matched motor deviation verification calculation force as the deviation verification calculation force analysis result.

Further, the verification layout module 13 further includes:

The associated trigger degree calculation unit is used for calculating the associated trigger degrees of the operation deviation of the first motor control node decision based on the N operation deviation record libraries to obtain the associated trigger degrees of the operation deviation of the first node;

The trigger degree corresponding unit is configured to continuously perform operation deviation association trigger degree calculation on an H motor control node decision of a second motor control node decision … based on the N operation deviation record libraries, obtain an H node operation deviation association trigger degree of a second node operation deviation association trigger degree …, and generate H node operation deviation association trigger degrees corresponding to the H motor control node decisions by combining the first node operation deviation association trigger degrees;

The adjusting unit is used for respectively adjusting the deviation verification computing power analysis results according to the H node operation deviation association triggering degrees based on the preset node operation deviation association triggering degrees to obtain H node deviation verification computing powers;

The time domain configuration unit is used for respectively setting the deviation verification time nodes for the H motor control node decisions based on the H node deviation verification calculation forces and generating H deviation verification time domains, wherein each deviation verification time domain comprises a plurality of deviation verification time nodes corresponding to each motor control node decision.

Further, the associated trigger degree calculating unit further includes:

The associated deviation record extraction unit is used for respectively extracting the associated operation deviation records of the N operation deviation record libraries based on the decision of the first motor control node to obtain N associated operation deviation record libraries corresponding to the decision of the first motor control node;

The deviation triggering times counting unit is used for traversing the N associated operation deviation record libraries to count operation deviation record times and obtain N associated time zone deviation triggering times;

And the node association triggering degree calculation unit is used for carrying out weighted calculation on the N association time zone deviation triggering times based on the N-level time zone gradual change weight to generate the first node operation deviation association triggering degree.

Further, the motor deviation adjusting module 16 further includes:

the reference unit is used for extracting a plurality of index control reference data corresponding to a plurality of motor control indexes from the real-time motor control node decision;

the random numbering unit is used for carrying out random numbering based on the motor control indexes to obtain a first motor control index, a second motor control index … Kth motor control index, and the K value is the total number of the motor control indexes;

the first regulation and control decision unit is used for carrying out deviation regulation and control on the real-time control feedback data according to the first motor control index based on the motor deviation regulation and control submodule to obtain a first index deviation regulation and control decision;

The regulation and control decision unit is used for respectively carrying out deviation regulation and control on the real-time control feedback data according to the K-th motor control index of the second motor control index … based on the motor deviation regulation and control submodule to obtain a K-th index deviation regulation and control decision of a second index deviation regulation and control decision …;

and the scheme integrating unit is used for generating the motor deviation regulating scheme according to the first index deviation regulating and controlling decision and the K index deviation regulating and controlling decision of the second index deviation regulating and controlling decision ….

Further, the first regulation decision unit further comprises:

a reference matching unit for matching the first index control reference data according to the plurality of index control reference data based on the first motor control index;

The feedback data matching unit is used for matching the first index control feedback data according to the real-time control feedback data based on the first motor control index;

The control comparison unit is used for comparing the first index control reference data with the first index control feedback data to obtain a first index control comparison degree;

the judging unit is used for judging whether the first index control comparison degree is smaller than a preset control comparison degree or not;

The deviation regulation and control instruction unit is used for obtaining a first index deviation regulation and control instruction if the first index control comparison degree is greater than/equal to a preset control comparison degree;

The activating unit is used for activating a first index deviation regulating network corresponding to the first motor control index in the motor deviation regulating sub-module based on the first index deviation regulating instruction, wherein the motor deviation regulating sub-module comprises index deviation regulating networks corresponding to all motor control indexes which are built in advance;

The network decision unit is used for inputting the first index control comparison degree, the first index control reference data and the first index control feedback data into the first index deviation regulation and control network to generate the first index deviation regulation and control decision.

It should be understood that the embodiments mentioned in this specification focus on the differences from other embodiments, and the specific embodiment in the first embodiment is equally applicable to the operation deviation adaptive control system of the permanent magnet motor described in the second embodiment, which is not further developed herein for brevity of the specification.

It is to be understood that both the foregoing description and the embodiments of the present application enable one skilled in the art to utilize the present application. While the application is not limited to the embodiments described above, obvious modifications and variations of the embodiments described herein are possible and are within the principles of the application.

Claims (5)

1. The method is applied to a permanent magnet motor operation deviation self-adaptive regulation and control system, wherein the system comprises a motor data management end and a motor regulation and control end, and the method comprises the following steps:

The motor data management terminal is connected, motor basic information and motor operation tasks of the permanent magnet motor are read, wherein the motor operation tasks comprise H-level motor operation loads of the permanent magnet motor, and H is a positive integer greater than 1;

performing motor control decision analysis based on the motor basic information and the motor operation task to obtain a motor control scheme, wherein the motor control scheme comprises H motor control node decisions corresponding to the H-level motor operation load;

And performing motor control decision analysis based on the motor basic information and the motor operation task to obtain a motor control scheme, wherein the motor control scheme comprises the following steps:

obtaining motor operation time sequence constraint of the motor operation task, sequencing the motor operation task according to the motor operation time sequence constraint, and generating a motor operation first load and a motor operation second load … motor operation H load;

Performing motor control record inquiry based on the motor basic information and the motor operation task to obtain a motor control record library;

Based on the motor control record library, according to the motor basic information, motor control decision matching is respectively carried out on the motor operation first load and the motor operation second load … and the motor operation H load, and a first motor control node decision and a second motor control node decision … H motor control node decision are generated;

Generating the motor control scheme according to the first motor control node decision and the second motor control node decision … and the H motor control node decision;

performing deviation verification computing power analysis on the permanent magnet motor to obtain a deviation verification computing power analysis result, and executing deviation verification node layout of the motor control scheme based on the deviation verification computing power analysis result to obtain H deviation verification time domains corresponding to the decisions of the H motor control nodes;

Performing deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, wherein the method comprises the following steps of:

Obtaining N-level historical time zone constraint, and setting N-level time zone gradual change weight corresponding to the N-level historical time zone constraint, wherein N is a positive integer greater than 1;

reading the historical operation deviation record of the permanent magnet motor according to the N-level historical time zone constraint, and obtaining N operation deviation record libraries corresponding to the N-level historical time zone constraint;

traversing the N operation deviation record libraries to count operation deviation record times to obtain N time zone deviation triggering times;

Weighting calculation is carried out on the N time zone deviation triggering times based on the N-level time zone gradual change weight, and motor operation deviation triggering degrees are generated;

constructing a motor deviation verification computing power configuration table, wherein the motor deviation verification computing power configuration table comprises a plurality of preset motor operation deviation trigger degree intervals and a plurality of preset motor deviation verification computing powers;

Inputting the motor operation deviation triggering degree into the motor deviation verification computing force configuration table, obtaining a matched motor deviation verification computing force corresponding to the motor operation deviation triggering degree, and outputting the matched motor deviation verification computing force as the deviation verification computing force analysis result;

Transmitting the motor control scheme to the motor regulation and control end, controlling the permanent magnet motor according to the motor control scheme, and performing real-time control feedback monitoring on the permanent magnet motor according to the H deviation verification time domains to obtain real-time control feedback data, wherein the real-time control feedback data has a real-time deviation verification time node corresponding to the mark;

according to the motor control scheme, matching the real-time motor control node decision corresponding to the real-time deviation verification time node;

Based on a motor deviation regulation sub-module, carrying out multidimensional deviation regulation analysis on the real-time control feedback data according to the real-time motor control node decision, generating a motor deviation regulation scheme, transmitting the motor deviation regulation scheme to a motor regulation end, and carrying out deviation self-adaptive regulation on the permanent magnet motor according to the motor deviation regulation scheme;

Based on a motor deviation regulation sub-module, the real-time control feedback data is subjected to multidimensional deviation regulation analysis according to the real-time motor control node decision, and a motor deviation regulation scheme is generated, and the method comprises the following steps:

extracting a plurality of index control reference data corresponding to a plurality of motor control indexes from the real-time motor control node decision;

carrying out random numbering based on the motor control indexes to obtain a first motor control index, a second motor control index … and a Kth motor control index, wherein the K value is the total number of the motor control indexes;

based on the motor deviation regulation sub-module, carrying out deviation regulation on the real-time control feedback data according to the first motor control index to obtain a first index deviation regulation decision;

Based on the motor deviation regulation sub-module, respectively carrying out deviation regulation on the real-time control feedback data according to the K-th motor control index of the second motor control index … to obtain a K-th index deviation regulation decision of a second index deviation regulation decision …;

And generating the motor deviation regulation scheme according to the first index deviation regulation decision and the K index deviation regulation decision of the second index deviation regulation decision ….

2. The method of claim 1, wherein obtaining H bias verification time domains for the H motor control node decisions comprises:

based on the N operation deviation record libraries, performing operation deviation association triggering degree calculation on a first motor control node decision to obtain a first node operation deviation association triggering degree;

Based on the N operation deviation record libraries, continuously calculating operation deviation association triggering degrees of H motor control node decisions of a second motor control node decision …, obtaining H node operation deviation association triggering degrees of a second node operation deviation association triggering degree …, and generating H node operation deviation association triggering degrees corresponding to the H motor control node decisions by combining the first node operation deviation association triggering degrees;

Based on a preset node operation deviation association triggering degree, respectively adjusting the deviation verification computing power analysis result according to the H node operation deviation association triggering degrees to obtain H node deviation verification computing powers;

and based on the H node deviation verification calculation forces, respectively carrying out deviation verification time node setting on the H motor control node decisions, and generating H deviation verification time domains, wherein each deviation verification time domain comprises a plurality of deviation verification time nodes corresponding to each motor control node decision.

3. The method of claim 2, wherein performing a run-bias-related trigger degree calculation on the first motor control node decision based on the N run-bias record libraries to obtain a first node run-bias-related trigger degree, comprises:

Based on the first motor control node decision, respectively extracting associated operation deviation records of the N operation deviation record libraries to obtain N associated operation deviation record libraries corresponding to the first motor control node decision;

traversing the N associated operation deviation record libraries to count operation deviation record times, and obtaining N associated time zone deviation triggering times;

And carrying out weighted calculation on the N associated time zone deviation triggering times based on the N-level time zone gradual change weight, and generating the first node operation deviation associated triggering degree.

4. The method of claim 1, wherein performing bias control on the real-time control feedback data based on the first motor control index based on the motor bias control sub-module to obtain a first index bias control decision, comprising:

Based on the first motor control index, matching first index control reference data according to the plurality of index control reference data;

Based on the first motor control index, matching first index control feedback data according to the real-time control feedback data;

Comparing the first index control reference data with the first index control feedback data to obtain a first index control comparison degree;

Judging whether the first index control comparison degree is smaller than a preset control comparison degree or not;

if the first index control comparison degree is greater than/equal to the preset control comparison degree, a first index deviation regulation instruction is obtained;

Activating a first index deviation regulating network corresponding to the first motor control index in the motor deviation regulating sub-module based on the first index deviation regulating instruction, wherein the motor deviation regulating sub-module comprises index deviation regulating networks corresponding to all motor control indexes constructed in advance;

And inputting the first index control comparison degree, the first index control reference data and the first index control feedback data into the first index deviation regulation and control network to generate the first index deviation regulation and control decision.

5. A permanent magnet motor operation deviation adaptive regulation and control system, characterized in that the system comprises a motor data management end and a motor regulation and control end, the system further comprises:

The information acquisition module is used for connecting the motor data management end, and reading motor basic information and motor operation tasks of the permanent magnet motor, wherein the motor operation tasks comprise H-level motor operation loads of the permanent magnet motor, and H is a positive integer greater than 1;

The motor control decision analysis module is used for carrying out motor control decision analysis based on the motor basic information and the motor operation task to obtain a motor control scheme, wherein the motor control scheme comprises H motor control node decisions corresponding to the H-level motor operation load;

The verification layout module is used for carrying out deviation verification calculation force analysis on the permanent magnet motor to obtain a deviation verification calculation force analysis result, and executing deviation verification node layout of the motor control scheme based on the deviation verification calculation force analysis result to obtain H deviation verification time domains corresponding to the H motor control node decisions;

The real-time monitoring feedback module is used for transmitting the motor control scheme to the motor regulation and control end, controlling the permanent magnet motor according to the motor control scheme, performing real-time control feedback monitoring on the permanent magnet motor according to the H deviation verification time domains to obtain real-time control feedback data, wherein the real-time control feedback data has a real-time deviation verification time node corresponding to the mark;

the node decision mapping module is used for matching the real-time motor control node decision corresponding to the real-time deviation verification time node according to the motor control scheme;

The motor deviation regulation and control module is used for carrying out multidimensional deviation regulation and control analysis on the real-time control feedback data according to the real-time motor control node decision based on a motor deviation regulation and control submodule, generating a motor deviation regulation and control scheme, transmitting the motor deviation regulation and control scheme to the motor regulation and control end, and carrying out deviation self-adaptive regulation and control on the permanent magnet motor according to the motor deviation regulation and control scheme;

wherein, the motor control decision analysis module further comprises:

The operation task serialization unit is used for obtaining motor operation time sequence constraint of the motor operation tasks, and sequencing the motor operation tasks according to the motor operation time sequence constraint to generate a motor operation first load and a motor operation second load … motor operation H load;

The control record inquiring unit is used for inquiring the motor control record based on the motor basic information and the motor operation task to obtain a motor control record library;

the control decision matching unit is used for respectively carrying out motor control decision matching on the motor operation first load and the motor operation second load … and the motor operation H load according to the motor basic information based on the motor control record library to generate a first motor control node decision and a second motor control node decision … H motor control node decision;

the control scheme generating unit is used for generating the motor control scheme according to the first motor control node decision and the second motor control node decision … and the H motor control node decision;

wherein, the verification layout module further comprises:

the history time zone weight constraint unit is used for obtaining N-level history time zone constraints and setting N-level time zone gradual change weights corresponding to the N-level history time zone constraints, wherein N is a positive integer greater than 1;

The deviation record extraction unit is used for reading the historical operation deviation record of the permanent magnet motor according to the N-level historical time zone constraint and obtaining N operation deviation record libraries corresponding to the N-level historical time zone constraint;

the deviation frequency counting unit is used for traversing the N operation deviation record libraries to count the operation deviation record times and obtain N time zone deviation triggering times;

The operation deviation triggering degree unit is used for carrying out weighted calculation on the N time zone deviation triggering times based on the N-level time zone gradual change weight to generate motor operation deviation triggering degree;

the configuration table construction unit is used for constructing a motor deviation verification computing power configuration table, wherein the motor deviation verification computing power configuration table comprises a plurality of preset motor operation deviation trigger degree intervals and a plurality of preset motor deviation verification computing powers;

The calculation force matching unit is used for inputting the motor operation deviation triggering degree into the motor deviation verification calculation force configuration table, obtaining a matched motor deviation verification calculation force corresponding to the motor operation deviation triggering degree, and outputting the matched motor deviation verification calculation force as the deviation verification calculation force analysis result;

wherein, the motor deviation regulation and control module still includes:

the reference unit is used for extracting a plurality of index control reference data corresponding to a plurality of motor control indexes from the real-time motor control node decision;

the random numbering unit is used for carrying out random numbering based on the motor control indexes to obtain a first motor control index, a second motor control index … Kth motor control index, and the K value is the total number of the motor control indexes;

the first regulation and control decision unit is used for carrying out deviation regulation and control on the real-time control feedback data according to the first motor control index based on the motor deviation regulation and control submodule to obtain a first index deviation regulation and control decision;

The regulation and control decision unit is used for respectively carrying out deviation regulation and control on the real-time control feedback data according to the K-th motor control index of the second motor control index … based on the motor deviation regulation and control submodule to obtain a K-th index deviation regulation and control decision of a second index deviation regulation and control decision …;

and the scheme integrating unit is used for generating the motor deviation regulating scheme according to the first index deviation regulating and controlling decision and the K index deviation regulating and controlling decision of the second index deviation regulating and controlling decision ….