CN113325697B - Automatic control system - Google Patents

Abstract

The present invention provides an automatic control system, the system includes a receiving module, a processing module, an output module and a storage module; wherein, the storage module is used to store the controlled object model and the automatic control model; the receiving module, 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, The controlled object model and the automatic control model output a target control signal based on the real-time data; the output module is configured to output the target control signal to the controlled object. The automatic control system proposed by the invention utilizes the fractional-order auto-coupling PI ^λ D ^μ controller to output a better control signal, which can significantly improve the controlled object to achieve a more satisfactory control effect.

Description

an automatic control system

technical field

The invention relates to the field of automatic control, in particular to an automatic control system.

Background technique

With the advancement of science and technology, more and more automatic control systems are used in industrial production. Among them, PID controllers are used more because of their simplicity and ease of adjustment.

At the same time, the systems that exist in practice are more or less affected by non-integer orders. These systems are difficult to be accurately described by traditional integer order mathematical models. Therefore, fractional order models are needed to obtain a more accurate mathematical description and satisfaction. control performance. The fractional-order PI ^λ D ^μ controller has been widely used and developed in the fields of national defense, industry, aviation, and aerospace. Compared with the traditional integer-order PID controller, the PI ^λ D ^μ controller has two additional parameters: the integral order λ and differential order μ, so that it has more opportunities to make flexible and satisfactory adjustments to the dynamics of fractional-order systems. Therefore, for fractional-order systems, the fractional-order PI ^λ D ^μ controller can play a better control effect than the integer-order PID controller.

However, most of the parameters obtained by the existing fractional-order PI ^λ D ^μ controller tuning methods are fixed constants or piecewise constants. It can be seen that the fractional-order PI ^λ D ^μ is the same as the parameter tuning problem of the integer-order PID controller. The choice of controller parameters is still a difficult problem.

SUMMARY OF THE INVENTION

In order to solve the technical problems existing in the above background technology, the present invention provides an automatic control system.

The present invention provides an automatic control system, the system includes a receiving module, a processing module, an output module and a storage module; wherein,

The storage module is used to store the controlled object model and the automatic control model;

The receiving module is used to receive the real-time data of the controlled object, and transmit the real-time data to the processing module;

The processing module is configured to receive the real-time data, call the controlled object model and the automatic control model, and output a target control signal based on the real-time data of the controlled object model and the automatic control model;

The output module is used for outputting the target control signal to the controlled object.

Optionally, the automatic control model is constructed based on a fractional-order autocoupling PI ^λ D ^μ controller.

Optionally, the fractional-order autocoupling PI ^λ D ^μ controller is constructed using the s-function function in matlab.

Optionally, the fractional-order autocoupling PI ^λ D ^μ controller is:

In the formula, k _p , k _i , and k _d are the adjustable control parameters of the fractional-order auto-coupled PI ^λ D ^μ controller; λ and μ are the fractional integral order and fractional differential order, respectively.

Optionally, the adjustable control parameters k _p , k _i , and k _d are calculated by using the following formula 2):

In the formula, z _c is the adaptive speed factor.

Optionally, the calculation formula of the adaptive speed factor z _c is:

T_t是由动态过渡到稳态的过渡过程时间。In the formula, 0<α<100,

T _t is the transition time from dynamic to steady state.

Optionally, if the controlled object belongs to the fast system, the value can be arbitrarily set within the range of 10<α<100; if the controlled object belongs to the slow system, the value can be arbitrarily set within the range of 1<α≤10.

Optionally, the transition process time T _t is determined based on time scale characteristics of the controlled object.

The beneficial effects of the present invention are:

The automatic control system proposed by the present invention utilizes a fractional-order autocoupling PI ^λ D ^μ controller to construct an automatic control model for realizing a good automatic control goal. Among them, the three parameters of proportional gain K _p , integral gain K _i , and differential gain K _d in the fractional-order auto-coupling PI ^λ D ^μ controller are three kinds of continuously time-varying functions, and the continuously time-varying parameters have “soft” ” characteristics, the fractional-order PI ^λ D ^μ controller with time-varying parameters is more suitable for the fractional-order control system (that is, the controlled object) with flexible structural characteristics, making it more likely to achieve satisfactory control effects. The traditional fractional-order PI ^λ D ^μ controller forms the control signal by the weighted summation of the differential and integral of the error and the error, while the fractional-order auto-coupling PI ^λ D ^μ controller in the present invention _adjusts the proportional The physical links of three different properties of , integration and differentiation are closely coupled to form control signals, which has the idea of cooperative control.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore do not It should be regarded as a limitation of the scope, and for those of ordinary skill in the art, other related drawings can also be obtained according to these drawings without any creative effort.

1 is a schematic structural diagram of an automatic control system disclosed in an embodiment of the present invention;

2 is a schematic structural diagram of a fractional-order auto-coupled PI ^λ D ^μ controller disclosed in an embodiment of the present invention;

3 is a schematic structural diagram of a simulation program disclosed in Embodiment 2 of the present invention;

4 is a unit step response curve diagram of a conventional integer-order PID controller disclosed in Embodiment 2 of the present invention;

FIG. 5 is a unit step response curve diagram of the fractional-order auto-coupling PIλDμ controller disclosed in the second embodiment of the present invention.

Detailed ways

In order to make the purposes, 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 accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments These are some embodiments of the present invention, but not all embodiments. The components of the embodiments of the invention generally described and illustrated in the drawings herein may be arranged and designed in a variety of different configurations.

Thus, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

It should be noted that like numerals and letters refer to like items in the following figures, so once an item is defined in one figure, it does not require further definition and explanation in subsequent figures.

In the description of the present invention, it should be noted that, if the terms "upper", "lower", "inner", "outer", etc. appear, the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the drawings, or It is the orientation or positional relationship that the product of the invention is usually placed in use, only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation , so it should not be construed as a limitation of the present invention.

In addition, where the terms "first", "second" and the like appear, they are only used to differentiate the description, and should not be construed as indicating or implying relative importance.

It should be noted that the features in the embodiments of the present invention may be combined with each other without conflict.

Example 1

Please refer to FIG. 1. FIG. 1 is a schematic structural diagram of an automatic control system disclosed in 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 to store the controlled object model and the automatic control model;

The receiving module is used to receive the real-time data of the controlled object, and transmit the real-time data to the processing module;

The processing module is configured to receive the real-time data, call the controlled object model and the automatic control model, and output a target control signal based on the real-time data of the controlled object model and the automatic control model;

The output module is used for outputting the target control signal to the controlled object.

In the embodiments of the present invention, the automatic control system proposed by the present invention utilizes a fractional-order autocoupling PI ^λ D ^μ controller to construct an automatic control model for achieving a good automatic control goal. Among them, the proportional gain K _p , the integral gain K _i , and the differential gain K _d in the fractional-order auto-coupling PI ^λ D ^μ controller are three kinds of continuous time-varying functions, and the continuously time-varying parameters have "soft" The fractional-order PI ^λ D ^μ controller with time-varying parameters is more suitable for the fractional-order control system with flexible structural characteristics, making it more likely to achieve satisfactory control effects.

Among them, the controlled object can be various industrial automation systems, for example, industrial robots used in the production process of automobiles such as grasping, welding, painting and other processes, and the corresponding real-time data can be the spatial coordinate position of the robot arm, and the predetermined coordinates. Position deviation, etc.; it can also be the power grid automatic dispatching equipment in the power sector, and the corresponding real-time data can be the working status of the target control equipment of the power grid automatic dispatching equipment, the real-time output power of the generator, etc.; it can also be the smelter’s Electric arc furnace automatic control equipment, the corresponding real-time data can be electric arc furnace temperature, real-time voltage and so on. Since the core of the present invention lies in the control algorithm, in addition to the above scenario, any other system may be used, which is not limited in the present invention.

Optionally, the automatic control model is constructed based on a fractional-order autocoupling PI ^λ D ^μ controller.

Optionally, the fractional-order autocoupling PI ^λ D ^μ controller is constructed using the s-function function in matlab.

Among them, for some relatively miniaturized automatic systems, the automatic control model can be constructed based on the matlab platform, while for industrial automation systems, more reliable and professional programming platforms can be selected, such as VAL language, AL language , SLIM language, RAPID language, AML language, KAREL language, etc.

Optionally, the fractional-order autocoupling PI ^λ D ^μ controller is:

In the formula, k _p , k _i , and k _d are the adjustable control parameters of the fractional-order auto-coupled PI ^λ D ^μ controller; λ and μ are the fractional integral order and fractional differential order, respectively.

Optionally, the adjustable control parameters k _p , k _i , and k _d are calculated by using the following formula 2):

In the formula, z _c is the adaptive speed factor.

Optionally, the calculation formula of the adaptive speed factor z _c is:

T_t是由动态过渡到稳态的过渡过程时间。In the formula, 0<α<100,

T _t is the transition time from dynamic to steady state.

Optionally, if the controlled object belongs to the fast system, the value can be arbitrarily set within the range of 10<α<100; if the controlled object belongs to the slow system, the value can be arbitrarily set within the range of 1<α≤10.

Optionally, the transition process time T _t is determined based on time scale characteristics of the controlled object.

In the embodiment of the present invention, different systems have different adjustment degrees. In principle, it is expected that the shorter the adjustment time, the smaller T _t can be obtained. It is worth noting that α and T _t have an inherent influence. Too fast response speed will inevitably aggravate the overshoot of the system, while too slow response speed will prolong the adjustment time to a certain extent. The selection of specific solutions needs to weigh the advantages and disadvantages. , choose according to the actual situation.

In addition, the function of the processing module in the present invention can be implemented based on a computer program, and the calculation program can be further implemented in the form of an electronic device or a computer storage medium, and for the electronic device and the computer storage medium can be directly provided in the processing module can also be set separately and called by the processing module.

Embodiment 2

In addition, the present invention also implements the simulation of the automatic control model, and the simulation method is realized by means of the matlab/simulink platform. Please refer to FIG. 3 , which is a schematic structural diagram of a structural diagram disclosed in an embodiment of the present invention. The structure diagram program is written in simulink, and the open fractional order toolkit is used to write the structure diagram of simulink, in which the controller part uses the s-function function to write the m file code in matlab.

The s-function function program includes the establishment process of the k _p module, the k _i module, and the k _d module, as follows:

1. Establishment of kp module

function[sys,x0,str,ts]=sfexample(t,x,u,flag,x_initial)

% Where t represents time, x represents state vector, u represents input vector, flag represents subroutine call flag, and x_initial represents user initialization.

global kp; % set a global variable, keeping kp time-varying.

% Judge the flag and execute the 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';

%Initialize operation. According to the model requirements: single-input single-output system, no other continuous or discrete variables, set as 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;

% Set k _p according to formula (2) and formula (3) and output the result.

function sys=mdlGetTimeOfNextVarHit(t,x,u)

sampleTime = 1;

sys=t+sampleTime;

% Set the sampling time.

2. The establishment of the ki module

function[sys,x0,str,ts]=sfexample(t,x,u,flag,x_initial)

% Where t represents time, x represents state vector, u represents input vector, flag represents subroutine call flag, and x_initial represents user initialization.

global ki; % set a global variable, keeping ki time-varying.

% Determine the flag value and execute the 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 is based on model requirements: one input and one output, no other continuous or discrete variables are added, and a continuous system is set.

functionsys=mdlOutputs(t,x,u)

zc=30/1*(1-0.9*exp(-1*t));

ki=zc*zc*zc;

sys=ki*u;

% Set k _i according to formula (2) and formula (3) and output the result.

functionsys=mdlGetTimeOfNextVarHit(t,x,u)

sampleTime = 1;

sys=t+sampleTime;

% Set the sampling time.

3. Establishment of kd module

function[sys,x0,str,ts]=sfexample(t,x,u,flag,x_initial)

% Where t represents time, x represents state vector, u represents input vector, flag represents subroutine call flag, and x_initial represents user initialization.

global kd; % set a global variable, keeping kd time-varying.

% Judge the flag and execute the 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 is based on model requirements: one input and one output, no other continuous or discrete variables are added, and a continuous system is set.

functionsys=mdlOutputs(t,x,u)

zc=30/1*(1-0.9*exp(-1*t));

kd=6*zc/1.1;

sys=kd*u;

% Set k _d according to formula (2) and formula (3) and output the result.

functionsys=mdlGetTimeOfNextVarHit(t,x,u)

sampleTime = 1;

sys=t+sampleTime;

% Set the sampling time.

进行了比较，参照图4-5所示的单位阶跃响应曲线图，从图中可以明显看出，本发明的分数阶自耦PI^λD^μ控制器可以获得更为良好的控制效果。Then, compare the visualized simulation results with a conventional integer-order PID controller (eg:

After comparison, referring to the unit step response curves shown in Figures 4-5, it can be clearly seen from the figures that the fractional-order autocoupling PI ^λ D ^μ controller of the present invention can obtain better control effects.

The present invention is 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 process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes 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 the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device produce Means for implementing the functions specified in a flow or flow of a flowchart and/or a block or blocks of a block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory result in an article of manufacture comprising instruction means, the instructions The apparatus implements the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.

These computer program instructions can also be loaded on a computer or other programmable data processing device to cause a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process such that The instructions provide steps for implementing the functions specified in the flow or blocks of the flowcharts and/or the block or blocks of the block diagrams.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical scope disclosed by the present invention can easily think of changes or substitutions. All should be included within the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims (4)

1. an automatic control system, the system comprises a receiving module, a processing module, an output module and a storage module, it is characterized in that: The storage module is used to store the controlled object model and the automatic control model; The receiving module is used to receive the real-time data of the controlled object, and transmit the real-time data to the processing module; The processing module is configured to receive the real-time data, call the controlled object model and the automatic control model, and output a target control signal based on the real-time data of the controlled object model and the automatic control model; the output module, for outputting the target control signal to the controlled object; The automatic control model is constructed based on a fractional-order autocoupling PI ^λ D ^μ controller; The fractional-order autocoupling PI ^λ D ^μ controller is constructed by using the s-function function in matlab; The fractional-order autocoupling PI ^λ D ^μ controller is:

where k _p , k _i , and k _d are the adjustable control parameters of the fractional-order auto-coupled PI ^λ D ^μ controller; λ and μ are the fractional integral order and fractional differential order, respectively; The adjustable control parameters k _p , k _i , k _d are calculated by the following formula 2):

In the formula, z _c is the adaptive speed factor. 2. automatic control system according to claim 1, is characterized in that: the calculation formula of described self-adaptive speed factor z _c is:

In the formula, 0<α<100,

T _t is the transition process time from dynamic to steady state, and t is the time scale characteristic of the plant. 3. The automatic control system according to claim 2, characterized in that: if the controlled object belongs to a fast system, the value can be arbitrarily selected within the range of 10<α<100; if the controlled object belongs to a slow system, 0<α Any value within the range of <100. 4 . The automatic control system according to claim 2 or 3 , wherein the transition process time T _t is determined based on the time scale characteristics of the controlled object. 5 .

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