CN113325697B - Automatic control system - Google Patents

Automatic control system Download PDF

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CN113325697B
CN113325697B CN202110656812.1A CN202110656812A CN113325697B CN 113325697 B CN113325697 B CN 113325697B CN 202110656812 A CN202110656812 A CN 202110656812A CN 113325697 B CN113325697 B CN 113325697B
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controlled object
automatic control
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赵伊男
张友琦
周健
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Tongji University
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    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00Automatic controllers
    • G05B11/01Automatic controllers electric
    • G05B11/36Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
    • G05B11/42Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P. I., P. I. D.

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Abstract

The invention provides an automatic control system, which comprises a receiving module, a processing module, an output module and a storage module, wherein the receiving module is used for receiving a control signal; the storage module is used for storing a controlled object model and an automatic control model; the receiving module is used for receiving the real-time data of the controlled object and transmitting the real-time data to the processing module; the processing module is used for receiving the real-time data, calling the controlled object model and the automatic control model, and outputting a target control signal based on the real-time data and the controlled object model and the automatic control model; and the output module is used for outputting the target control signal to a controlled object. The automatic control system provided by the invention utilizes fractional order self-coupling PI λ D μ The controller outputs more excellent control signals, and can remarkably improve the control effect of the controlled object to be more satisfactory.

Description

Automatic control system
Technical Field
The invention relates to the field of automatic control, in particular to an automatic control system.
Background
With the development of science and technology, various automatic control systems are increasingly used in industrial production, wherein a PID controller is frequently used due to simplicity and easiness in adjustment.
Meanwhile, in practice, systems are influenced by non-integer orders to a greater or lesser extent, and the systems are difficult to accurately describe by using a traditional integer order mathematical model, so that a fractional order model is required to obtain more accurate mathematical description and satisfactory control performance. Fractional order PI λ D μ The controller is applied and developed in the fields of national defense, industry, aviation, aerospace and the like, and PI λ D μ The controller has two parameters added compared with the traditional integer order PID controller: the integration order λ and the differentiation order μ allow more opportunities for flexible and satisfactory adjustment of the dynamics of the fractional order system. Therefore, for fractional order systems, fractional order PI λ D μ Compared with an integral-order PID controller, the controller can achieve a better control effect.
But existing fractional order PI λ D μ Most of the parameters obtained by the setting method of the controller are fixed constants or segmented constants, so that the fractional order PI (proportional integral) controller has the same parameter setting problem as the integer order PID controller λ D μ The selection of controller parameters remains a challenge.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides an automatic control system.
The invention provides an automatic control system, which comprises a receiving module, a processing module, an output module and a storage module, wherein the receiving module is used for receiving a control signal; wherein,
the storage module is used for storing a controlled object model and an automatic control model;
the receiving module is used for receiving the real-time data of the controlled object and transmitting the real-time data to the processing module;
the processing module is used for receiving the real-time data, calling the controlled object model and the automatic control model, and outputting a target control signal based on the real-time data and the controlled object model and the automatic control model;
and the output module is used for outputting the target control signal to a controlled object.
Optionally, the automatic control model is based on fractional order auto-coupling PI λ D μ And constructing a controller.
Optionally, the fractional order self-coupling PI is constructed by using an s-function in matlab λ D μ And a controller.
Optionally, the fractional order auto-coupling PI λ D μ The controller is as follows:
Figure BDA0003113315030000021
in the formula, k p 、k i 、k d Is the fractional order auto-coupling PI λ D μ Adjustable control parameters of the controller; λ and μ are the fractional integral order and the fractional derivative order, respectively.
Optionally, the adjustable control parameter k p 、k i 、k d Calculated using the following formula 2):
Figure BDA0003113315030000022
in the formula, z c Is an adaptive speed factor.
Optionally, the adaptive speed factor z c The calculation formula of (2) is as follows:
Figure BDA0003113315030000023
wherein alpha is more than 0 and less than 100,
Figure BDA0003113315030000024
T t is the transition time from dynamic to steady state.
Optionally, if the controlled object belongs to a fast system, the value is arbitrarily selected within the range of 10 < alpha < 100; if the controlled object belongs to a slow system, the value is arbitrarily selected within the range of 1 < alpha < 10.
Optionally, the transition process time T t And determining based on the time scale characteristics of the controlled object.
The invention has the beneficial effects that:
the automatic control system provided by the invention utilizes fractional order self-coupling PI λ D μ The controller builds an automatic control model for achieving good automatic control objectives. Wherein the fractional order auto-coupling PI λ D μ Proportional gain K in a controller p Integral gain K i Differential gain K d The three parameters are three continuous time-varying functions, the continuous time-varying parameters have 'soft' characteristic, and the fractional order PI of the time-varying parameters λ D μ The controller is more adaptable to a fractional order control system (i.e., controlled object) with flexible structural features, making it more likely to achieve satisfactory control. Conventional fractional order PI λ D μ The controller forms the control signal by differential and integral weighted summation of the error and the error, and the fractional order self-coupling PI in the invention λ D μ The controller passes the adaptive speed factor z c Three physical links with different attributes of proportion, integral and differentiation are closely coupled together to form a control signal, and the method has a cooperative control idea.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a schematic structural diagram of an automatic control system according to an embodiment of the present invention;
FIG. 2 is a fractional order auto-coupling PI disclosed in embodiments of the present invention λ D μ The structure schematic diagram of the controller;
FIG. 3 is a schematic structural diagram of a simulation program disclosed in the second embodiment of the present invention;
FIG. 4 is a graph of unit step response of a conventional integer-order PID controller according to a second embodiment of the invention;
fig. 5 is a graph showing a unit step response of the fractional order auto-coupled PI λ dju controller according to the second embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. indicate an orientation or a positional relationship based on that shown in the drawings or that the product of the present invention is used as it is, this is only for convenience of description and simplification of the description, and it does not indicate or imply that the device or the element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention.
Furthermore, the appearances of the terms "first," "second," and the like, if any, are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.
Example one
Referring to fig. 1, fig. 1 is a schematic structural diagram of an automatic control system according to an embodiment of the present invention. As shown in fig. 1, an automatic control system according to an embodiment of the present invention includes a receiving module, a processing module, an output module, and a storage module; wherein,
the storage module is used for storing a controlled object model and an automatic control model;
the receiving module is used for receiving the real-time data of the controlled object and transmitting the real-time data to the processing module;
the processing module is used for receiving the real-time data, calling the controlled object model and the automatic control model, and outputting a target control signal based on the real-time data and the controlled object model and the automatic control model;
and the output module is used for outputting the target control signal to a controlled object.
In the embodiment of the invention, the automatic control system provided by the invention utilizes fractional order self-coupling PI λ D μ The controller builds an automatic control model for achieving good automatic control objectives. Wherein, fractional order self coupling PI λ D μ Proportional gain K in a controller p Integral gain K i Differential gain K d The three parameters are three continuous time-varying functions, the continuous time-varying parameters have 'soft' characteristic, and the fractional order PI of the time-varying parameters λ D μ The controller is more adaptable to a fractional order control system with flexible structural features, making it more likely to achieve satisfactory control.
The controlled object can be various industrial automation systems, for example, an industrial robot used in processes of grabbing, welding, spraying paint and the like in the automobile production process, and the corresponding real-time data can be a space coordinate position of a mechanical arm of the robot, a deviation from a preset coordinate position and the like; the corresponding real-time data can be the working state of target control equipment of the automatic power grid dispatching equipment, the real-time output power of a generator and the like; or an automatic control device of an electric arc furnace of a smelting plant, and the corresponding real-time data can be the furnace temperature of the electric arc furnace, the real-time voltage and the like. The core of the present invention is a control algorithm, so that the present invention may be any system besides the above-mentioned scenarios, which is not limited in this respect.
Optionally, the automatic control model is based on fractional order auto-coupling PI λ D μ And constructing a controller.
Optionally, the score is constructed by using an s-function in matlabSeveral-order self-coupling PI λ D μ And a controller.
For some miniaturized automatic systems, the automatic control model can be constructed based on a matlab platform, and for industrial automatic systems, more reliable and professional programming platforms can be selected, such as a VAL language, an AL language, a SLIM language, a RAPID language, an AML language, a KAREL language and the like.
Optionally, the fractional order auto-coupling PI λ D μ The controller is as follows:
Figure BDA0003113315030000051
in the formula, k p 、k i 、k d Is the fractional order auto-coupling PI λ D μ Adjustable control parameters of the controller; λ and μ are the fractional integration order and the fractional differentiation order, respectively.
Optionally, the adjustable control parameter k p 、k i 、k d Calculated using the following formula 2):
Figure BDA0003113315030000052
in the formula, z c Is an adaptive speed factor.
Optionally, the adaptive speed factor z c The calculation formula of (2) is as follows:
Figure BDA0003113315030000053
wherein alpha is more than 0 and less than 100,
Figure BDA0003113315030000061
T t is the transition process time from dynamic to steady state.
Optionally, if the controlled object belongs to a fast system, the value is arbitrarily selected within the range of 10 < alpha < 100; if the controlled object belongs to a slow system, the value is arbitrarily selected within the range of 1 < alpha < 10.
Optionally, the transition time T t Based on the time scale characteristics of the controlled object.
In the exemplary embodiment of the invention, the degree of adjustment is different for different systems, and it is in principle desirable that the shorter the time adjustment time, the shorter T t The smaller can be achieved. It is noted that α and T t The method has the inherent influence that the overshoot of the system is aggravated when the response speed is too high, the response speed is too low, the adjustment time is prolonged to a certain extent, the advantages and the disadvantages need to be balanced when a specific scheme is selected, and the selection is carried out according to the actual situation.
In addition, the functions of the processing module in the present invention may be implemented based on a computer program, and the computer program may be further embodied in the form of an electronic device or a computer storage medium, and the electronic device or the computer storage medium may be directly provided in the processing module, or may be separately provided and called by the processing module.
Example two
In addition, the invention also realizes the simulation of the automatic control model, wherein the simulation method is realized by means of matlab/simulink platform. Referring to fig. 3, fig. 3 is a schematic structural diagram of a structure diagram disclosed in the embodiment of the present invention. A structure diagram program is written in the simulink, the structure diagram of the simulink adopts a public fractional order tool package, and the controller partially writes m file codes in matlab by means of an s-function.
The s-function program includes k p Module, k i Module, k d The building process of the module specifically comprises the following steps:
1.creation of kp modules
function[sys,x0,str,ts]=sfexample(t,x,u,flag,x_initial)
% where t represents time, x represents a state vector, u represents an input vector, flag represents a subroutine call flag, and x _ initial represents user initialization.
global kp; % sets global variables, keeping kp time-varying.
Figure BDA0003113315030000062
Figure BDA0003113315030000071
And judging the flag percent, and executing a corresponding program according to the flag value.
function[sys,x0,str,ts]=mdlInitializeSizes(x_initial)
sizes=simsizes;
sizes.NumContStates =0;
sizes.NumDiscStates =0;
sizes.NumOutputs =1;
sizes.NumInputs =1;
sizes.DirFeedthrough =1;
sizes.NumSampleTimes =1;
sys=simsizes(sizes);
x0=[];
str=[];
ts=[00];
simStateCompliance='UnknownSimState';
% initialization operation. According to the model requirements: the single-input single-output system has no other continuous or discrete variables and is set as a continuous system.
functionsys=mdlOutputs(t,x,u)
zc=30/1*(1-0.9*exp(-1*t));
kp=zc*zc*3*0.2;
sys=kp*u;
% sets k according to equations (2) and (3) p And outputs the result.
function sys=mdlGetTimeOfNextVarHit(t,x,u)
sampleTime=1;
sys=t+sampleTime;
% sets the sampling time.
2.ki Module set-up
function[sys,x0,str,ts]=sfexample(t,x,u,flag,x_initial)
% where t represents time, x represents a state vector, u represents an input vector, flag represents a subroutine call flag, and x _ initial represents user initialization.
global ki; % sets global variables, keeping ki time-varying.
Figure BDA0003113315030000081
And judging the flag value by percentage, and executing a corresponding program according to the flag value.
function[sys,x0,str,ts]=mdlInitializeSizes(x_initial)
sizes=simsizes;
sizes.NumContStates =0;
sizes.NumDiscStates =0;
sizes.NumOutputs =1;
sizes.NumInputs =1;
sizes.DirFeedthrough =1;
sizes.NumSampleTimes=1;
sys=simsizes(sizes);
x0=[];
str=[];
ts=[00];
simStateCompliance='UnknownSimState';
% initialization according to model requirements: one input quantity and one output quantity, without adding other continuous or discrete variables, are set as a continuous system.
functionsys=mdlOutputs(t,x,u)
zc=30/1*(1-0.9*exp(-1*t));
ki=zc*zc*zc;
sys=ki*u;
% setting k according to equations (2) and (3) i And outputs the result.
functionsys=mdlGetTimeOfNextVarHit(t,x,u)
sampleTime=1;
sys=t+sampleTime;
% sets the sampling time.
3.kd Module set-Up
function[sys,x0,str,ts]=sfexample(t,x,u,flag,x_initial)
% where t represents time, x represents a state vector, u represents an input vector, flag represents a subroutine call flag, and x _ initial represents user initialization.
global kd; % sets global variables, keeping kd time-varying.
Figure BDA0003113315030000091
Figure BDA0003113315030000101
And judging the flag percent, and executing a corresponding program according to the flag value.
function[sys,x0,str,ts]=mdlInitializeSizes(x_initial)
sizes=simsizes;
sizes.NumContStates =0;
sizes.NumDiscStates =0;
sizes.NumOutputs =1;
sizes.NumInputs =1;
sizes.DirFeedthrough =1;
sizes.NumSampleTimes =1;
sys=simsizes(sizes);
x0=[];
str=[];
ts=[0 0];
simStateCompliance='UnknownSimState';
% initialization according to model requirements: one input quantity and one output quantity, without adding other continuous or discrete variables, are set as a continuous system.
functionsys=mdlOutputs(t,x,u)
zc=30/1*(1-0.9*exp(-1*t));
kd=6*zc/1.1;
sys=kd*u;
% setting k according to equations (2) and (3) d And outputs the result.
functionsys=mdlGetTimeOfNextVarHit(t,x,u)
sampleTime=1;
sys=t+sampleTime;
% sets the sampling time.
Then, the visualized simulation result is compared with a conventional integer order PID controller (such as:
Figure BDA0003113315030000102
by comparison, referring to the unit step response graphs shown in FIGS. 4-5, it is apparent from the graphs that the fractional order auto-coupling PI of the present invention λ D μ The controller can obtain better control effect.
The present invention has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims (4)

1. An automatic control system, the system includes receiving module, processing module, output module and storage module, its characterized in that:
the storage module is used for storing a controlled object model and an automatic control model;
the receiving module is used for receiving the real-time data of the controlled object and transmitting the real-time data to the processing module;
the processing module is used for receiving the real-time data, calling the controlled object model and the automatic control model, and outputting a target control signal based on the real-time data, the controlled object model and the automatic control model;
the output module is used for outputting the target control signal to a controlled object;
the automatic control model is based on fractional order self-coupling PI λ D μ Constructing a controller;
the fractional order self-coupling PI is constructed by utilizing an s-function in matlab λ D μ A controller;
the fractional order self-coupling PI λ D μ The controller is as follows:
Figure FDA0003810532090000011
in the formula, k p 、k i 、k d Is the fractional order auto-coupling PI λ D μ Adjustable control parameters of the controller; λ and μ are the fractional integral order and the fractional differential order, respectively;
the adjustable control parameter k p 、k i 、k d Calculated using the following formula 2):
Figure FDA0003810532090000012
in the formula, z c Is an adaptive speed factor.
2. The automatic control system according to claim 1, characterized in that: the adaptive speed factor z c The calculation formula of (2) is as follows:
Figure FDA0003810532090000021
wherein alpha is more than 0 and less than 100,
Figure FDA0003810532090000022
T t is the transition process time from dynamic transition to steady state, and t is the time scale characteristic of the controlled object.
3. The automatic control system of claim 2, wherein: if the controlled object belongs to a fast system, the value is arbitrarily selected within the range of more than 10 and less than 100; if the controlled object belongs to the slow system, the value is arbitrarily selected within the range of 0 < alpha < 100.
4. According to the rightThe automatic control system according to claim 2 or 3, characterized in that: the transition time T t Based on the time scale characteristics of the controlled object.
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