CN113325697B - Automatic control system - Google Patents
Automatic control system Download PDFInfo
- Publication number
- 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
- Authority
- CN
- China
- Prior art keywords
- controlled object
- automatic control
- module
- model
- real
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000010168 coupling process Methods 0.000 claims abstract description 20
- 238000005859 coupling reaction Methods 0.000 claims abstract description 20
- 238000003860 storage Methods 0.000 claims abstract description 10
- 238000000034 method Methods 0.000 claims description 11
- 230000003044 adaptive effect Effects 0.000 claims description 7
- 230000007704 transition Effects 0.000 claims description 7
- 230000008569 process Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 abstract description 3
- 230000006870 function Effects 0.000 description 14
- 238000010586 diagram Methods 0.000 description 13
- 238000004590 computer program Methods 0.000 description 7
- 230000004044 response Effects 0.000 description 5
- 230000004069 differentiation Effects 0.000 description 3
- 238000005070 sampling Methods 0.000 description 3
- 238000004088 simulation Methods 0.000 description 3
- 238000010891 electric arc Methods 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000003723 Smelting Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 239000003973 paint Substances 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000003466 welding Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B11/00—Automatic controllers
- G05B11/01—Automatic controllers electric
- G05B11/36—Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
- G05B11/42—Automatic 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.
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
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
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:
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):
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:
wherein alpha is more than 0 and less than 100,
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:
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):
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:
wherein alpha is more than 0 and less than 100,
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.
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.
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.
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:
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:
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):
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:
wherein alpha is more than 0 and less than 100,
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.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110656812.1A CN113325697B (en) | 2021-06-11 | 2021-06-11 | Automatic control system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110656812.1A CN113325697B (en) | 2021-06-11 | 2021-06-11 | Automatic control system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113325697A CN113325697A (en) | 2021-08-31 |
| CN113325697B true CN113325697B (en) | 2022-10-14 |
Family
ID=77420695
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110656812.1A Active CN113325697B (en) | 2021-06-11 | 2021-06-11 | Automatic control system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113325697B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102566426A (en) * | 2011-12-29 | 2012-07-11 | 大连交通大学 | Fractional order parameter adjustment controller algorithm of PI<alpha>D<beta> controller |
| CN103558755A (en) * | 2013-11-05 | 2014-02-05 | 四川理工学院 | Fractional order integration PID controller setting and self-setting method |
| CN105425612A (en) * | 2015-11-10 | 2016-03-23 | 华中科技大学 | Preferred method of water turbine adjustment system control parameter |
| CN106054590A (en) * | 2016-06-28 | 2016-10-26 | 云南大学 | Fractional order PID controller of five-degree-of-freedom robot |
| CN108803311A (en) * | 2018-08-03 | 2018-11-13 | 佛山科学技术学院 | A kind of PID controller design method |
| CN109164662A (en) * | 2018-10-23 | 2019-01-08 | 长春理工大学 | Light beam based on liquid crystal optical phased array deflects control method |
| GB202018633D0 (en) * | 2019-12-16 | 2021-01-13 | Chongqing Aerospace Polytechnic | Optimal sychronization control method for coupled fractional-order chaotic electromechanical device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110703606A (en) * | 2019-10-30 | 2020-01-17 | 曾喆昭 | Novel self-coupling PID cooperative control theory method |
-
2021
- 2021-06-11 CN CN202110656812.1A patent/CN113325697B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102566426A (en) * | 2011-12-29 | 2012-07-11 | 大连交通大学 | Fractional order parameter adjustment controller algorithm of PI<alpha>D<beta> controller |
| CN103558755A (en) * | 2013-11-05 | 2014-02-05 | 四川理工学院 | Fractional order integration PID controller setting and self-setting method |
| CN105425612A (en) * | 2015-11-10 | 2016-03-23 | 华中科技大学 | Preferred method of water turbine adjustment system control parameter |
| CN106054590A (en) * | 2016-06-28 | 2016-10-26 | 云南大学 | Fractional order PID controller of five-degree-of-freedom robot |
| CN108803311A (en) * | 2018-08-03 | 2018-11-13 | 佛山科学技术学院 | A kind of PID controller design method |
| CN109164662A (en) * | 2018-10-23 | 2019-01-08 | 长春理工大学 | Light beam based on liquid crystal optical phased array deflects control method |
| GB202018633D0 (en) * | 2019-12-16 | 2021-01-13 | Chongqing Aerospace Polytechnic | Optimal sychronization control method for coupled fractional-order chaotic electromechanical device |
Non-Patent Citations (2)
| Title |
|---|
| Optimal fractional-order PID control for plasma shape, position, and current in Tokamaks;Meena E.Girgis 等;《FUSION ENGINEERING AND DESIGN》;20200131;第150卷;1-7 * |
| 交流伺服系统分数阶PID改进型自抗扰控制;王荣林 等;《中国机械工程》;20190813;第30卷(第16期);1989-1995 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113325697A (en) | 2021-08-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Tsai et al. | A real-time predictor-corrector interpolator for CNC machining | |
| EP3379349A1 (en) | Control device, control program, and control system | |
| Mendes et al. | An architecture for adaptive fuzzy control in industrial environments | |
| CN115946120A (en) | Mechanical arm control method, device, equipment and medium | |
| Zhou et al. | Robust model predictive control algorithm with variable feedback gains for output tracking | |
| CN113325697B (en) | Automatic control system | |
| CN104423321B (en) | For identifying the position control of low-frequency disturbance | |
| CN112859601A (en) | Robot controller design method, device, equipment and readable storage medium | |
| CN116713998A (en) | Non-lifting optimization iterative learning control method for robot | |
| CN111805537A (en) | Multi-manipulator cooperative control method, system, equipment and storage medium | |
| CN116512256A (en) | Robot optimal man-machine interaction impedance control method based on joint learning, storage medium and robot | |
| CN115981159A (en) | Generalized improved active disturbance rejection control method based on model assistance and similar Smith estimation | |
| CN114093433B (en) | Observer-based method and system for evaluating prediction precision of single-ton energy consumption in rectification process | |
| CN112975986B (en) | Mechanical arm point-to-point trajectory planning method and device based on radial basis function | |
| Klopot et al. | Function block practical implementation of Balance-Based Adaptive Control for pH process | |
| CN115248554A (en) | Optimal iteration feedforward parameter adjusting method and system for motion control system | |
| Das et al. | Design and implement of a state feedback position output controller for a Maxon S-Dc Motor with dSPACE | |
| Rodrigues et al. | Fast estimation of plant steady state, with application to static RTO | |
| EP4068012B1 (en) | Learning processing apparatus, control apparatus, learning processing method, control method, learning program and control program | |
| CN115598985B (en) | Training method and device of feedback controller, electronic equipment and medium | |
| CN110793546B (en) | Optimization method and system for inertial equipment adjustment and storage medium | |
| Anisimov et al. | Development of a Robust Control System for a Manipulative Robot Using the Gramian Apparatus | |
| JPH0272404A (en) | Deciding method for membership function | |
| US20220166364A1 (en) | Motor control method, motor control model conversion method, motor control system, motor control model conversion system, and motor control model conversion program | |
| Hagane et al. | Linearizing Robotic Manipulator's Dynamics Using Koopman Operator and Applying Generalized Predictive Control |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |