A second-order improved active disturbance rejection control design method, device and storage medium based on model assistance and Smith-like prediction

Abstract

The present invention discloses a second-order improved auto-disturbance rejection control design method, device and storage medium based on model assistance and Smith-like prediction, wherein the method includes: describing the actual industrial system with a high-order inertial system; designing a Smith-like prediction algorithm based on the input and output of the high-order inertial system; designing an extended state observation algorithm based on the model assistance according to the obtained output of the Smith-like prediction algorithm and the input of the high-order inertial system; designing a control law algorithm according to the obtained output of the extended state observation algorithm and the system setting value; obtaining a new input value of the high-order inertial system, and adjusting and controlling the output of the actual industrial system according to the new input value. The present invention makes full use of known model information, retains the characteristics of simple structure and easy parameter setting of the auto-disturbance rejection control, enables the closed-loop system to better balance tracking capability and anti-interference capability, and enables the closed-loop system to have strong robustness, and can be applied to the field of industrial control.

Description

Technical Field

[0001] The present invention relates to the field of industrial control, and in particular to a second-order improved auto-disturbance rejection control design method, device and storage medium based on model assistance and Smith-like prediction. Background Art

[0002] The active disturbance rejection control algorithm has been widely used and paid attention to due to its strong ability to handle system nonlinearity and system uncertainty, simple structure and high reliability. The active disturbance rejection control algorithm, especially the first-order and second-order active disturbance rejection control algorithm, has been widely used in motion systems, thermal systems, aerospace systems, etc.

[0003] However, the heat transfer and flow processes in process control systems are typical distributed parameters, which are generally described by using high-order inertial systems. Wherein s, K, T and n represent the differential operator, the gain of the high-order inertial system, the time constant of the high-order inertial system, and the order of the high-order inertial system, respectively, and n≥2, Y(s) and U(s) are the output and input of the high-order inertial system, respectively; taking the denitrification system as an example, the meaning of each parameter in the above formula is: the output Y(s) is the output value of the nitrogen oxide concentration of the denitrification system, the input U(s) is the ammonia injection amount of the denitrification system, the gain coefficient K refers to the amplification factor of the high-order system to the input value, and the input value is the change in the nitrogen oxide concentration of the denitrification system corresponding to 1 ton of ammonia injection, and the time constant T refers to the time required for the system response to reach 63.2% of the steady-state value.

[0004] For the above high-order inertial systems, there are standard ADRC algorithms and Smith predictor-like ADRC algorithms (patent application number: 202011125339.6). The latter is a first-order ADRC algorithm based on Smith predictor-like Figure 1 As shown in Figure 2, the second-order active disturbance rejection control algorithm based on Smith-like prediction is effective in controlling high-order inertial systems. There are problems such as the model information is not effectively utilized, the extended state observer is overburdened, the estimation accuracy is not high, and it is not possible to ideally balance the tracking and anti-interference performance. Summary of the invention

[0005] In order to solve at least one of the technical problems existing in the prior art to a certain extent, the object of the present invention is to provide a second-order improved active disturbance rejection control design method, device and storage medium based on model assistance and Smith-like estimation.

[0006] The technical solution adopted by the present invention is:

[0007] A second-order improved active disturbance rejection control design method based on model assistance and Smith-like prediction includes the following steps:

[0008] The actual industrial system is described using a high-order inertial system;

[0009] Design of Smith Prediction algorithm based on input and output of high-order inertial system;

[0010] According to the output of the Smith-like prediction algorithm and the input of the high-order inertial system, a model-assisted extended state observation algorithm is designed.

[0011] Design a control law algorithm based on the output of the extended state observation algorithm and the system setting value;

[0012] Obtain new input values ​​of the high-order inertial system and adjust and control the output of the actual industrial system according to the new input values.

[0013] Furthermore, the mathematical expression described by a high-order inertial system is:

[0014]

[0015] Among them, Y(s) and U(s) represent the output and input of the actual industrial system, s, K, T and n represent the differential operator, the gain of the actual industrial system, the time constant of the actual industrial system, and the order of the actual industrial system, and n ≥ 2. y(Γ-1) and u(Γ-1) represent the output and input of the previous calculation step of the actual industrial system, respectively.

[0016] Furthermore, the expression of the Smith-like prediction algorithm is as follows:

[0017] y p (Γ)=y1(Γ-1)-y2(Γ-1)+y(Γ-1)

[0018] In the formula, y p (Γ) is the output of the Smith-like prediction algorithm at the current calculation step Γ; y1(Γ-1) is the output of G1(s) at the previous calculation step Γ-1, y2(Γ-1) is the output of G2(s) at the previous calculation step Γ-1, and the input of G1(s) is the actual industrial system input u(Γ-1) at the previous calculation step, and the input of G2(s) is y1(Γ-1) at the previous calculation step Γ-1;

[0019] G1(s) and G2(s) are calculation expressions designed for the Smith prediction algorithm:

[0020]

[0021]

[0022] Wherein, k1 is the gain of G1(s), T1 is the time constant of G1(s) and G2(s); generally, k1=K and T1=T.

[0023] Furthermore, the expression of the model-assisted extended state observation algorithm is as follows:

[0024]

[0025] Among them, z1(Γ+1) and z1(Γ) are the tracking values ​​of the actual industrial system output y(Γ+1) and y(Γ) at the next calculation step Γ+1 and the current calculation step Γ respectively; z2(Γ+1) and z2(Γ) are the tracking values ​​of the first-order derivatives of the actual industrial system output at the next calculation step Γ+1 and the current calculation step Γ respectively; z3(Γ+1) and z3(Γ) are the observed values ​​of the interference to the actual industrial system at the next calculation step Γ+1 and the current calculation step Γ respectively; h is the sampling step; u(Γ) is the actual industrial system output at the current calculation step Γ; β1, β2, β3 and b0 are calculation coefficients; generally, and where ω o is the bandwidth of the model-assisted extended state observation algorithm and ω o ∈(0,10 10 ], ξ is an adjustable parameter and ξ∈(0.1,10 10 ]; the value range of h is [0.001,100].

[0026] Furthermore, the expression of the control law algorithm is as follows:

[0027]

[0028] or,

[0029]

[0030] Among them, u(Γ+2) is the input of the actual industrial system in the next two calculation steps Γ+2 for the control rate calculation, r(Γ+1) is the set value of the actual industrial system in the next calculation step Γ+1, and k p , k d To calculate the coefficient, we generally have and k d =2ω c , where ω c is the bandwidth of the control law algorithm and ω c ∈(0,10 10 ].

[0031] Furthermore, the obtaining of new input values ​​of the high-order inertial system and adjusting and controlling the output of the actual industrial system according to the new input values ​​include:

[0032] The input quantity u(Γ+2) of the two calculation steps Γ+2 under the high-order inertial system is sent to the actuator to adjust the opening of the actuator to achieve the control quantity adjustment of the closed-loop system, thereby realizing the output quantity adjustment of the actual industrial system.

[0033] Another technical solution adopted by the present invention is:

[0034] A second-order improved active disturbance rejection control design device based on model assistance and Smith-like prediction, comprising:

[0035] at least one processor;

[0036] at least one memory for storing at least one program;

[0037] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0038] Another technical solution adopted by the present invention is:

[0039] A computer-readable storage medium stores a program executable by a processor, wherein the program executable by the processor is used to execute the method described above when executed by the processor.

[0040] The beneficial effects of the present invention are as follows: the present invention can make full use of known model information and retain the characteristics of simple structure and easy parameter adjustment of the self-disturbance rejection control, so that the closed-loop system can better balance the tracking ability and anti-interference ability, and make the closed-loop system have strong robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the embodiments of the present invention or the drawings of related technical solutions in the prior art are introduced below. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 This is the structural block diagram of the existing second-order improved active disturbance rejection control algorithm based on Smith-like prediction;

[0043] Figure 2 It is a structural block diagram of a second-order improved active disturbance rejection control algorithm based on model assistance and Smith-like prediction in an embodiment of the present invention;

[0044] Figure 3 is another structural block diagram of a second-order improved active disturbance rejection control algorithm based on model assistance and Smith-like prediction in an embodiment of the present invention;

[0045] Figure 4 It is a comparison chart of the actual industrial object setting value, the output value of the method of the present invention and the output value of the comparison method in the embodiment of the present invention. DETAILED DESCRIPTION

[0046] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limitations of the present invention. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0047] In the description of the present invention, it should be understood that descriptions involving orientations, such as up, down, front, back, left, right, etc., and orientations or positional relationships indicated are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present invention.

[0048] In the description of the present invention, "several" means one or more, "more" means more than two, "greater than", "less than", "exceed" etc. are understood as not including the number itself, and "above", "below", "within" etc. are understood as including the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing the technical features, and cannot be understood as indicating or implying the relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0049] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0050] like Figure 2 and Figure 3 As shown, this embodiment provides a second-order improved active disturbance rejection control design method based on model assistance and Smith predictor-like estimation, which specifically includes the following steps:

[0051] Step 1: A class of controlled actual industrial systems is described using a high-order inertial system. The mathematical expression is:

[0052]

[0053] Wherein Y(s) and U(s) represent the output and input of the actual industrial system, s, K, T and n represent the differential operator, the gain of the actual industrial system, the time constant of the actual industrial system and the order of the actual industrial system, and n≥2; y(Γ-1) and u(Γ-1) represent the output of the previous calculation step and the input of the previous calculation step of the actual industrial system, respectively. In this embodiment, K=0.5, T=10 and n=3 of the actual industrial system.

[0054] Step 2: For a class of actual industrial systems controlled in step 1, design a Smith-like prediction algorithm based on the input and output of the actual industrial system:

[0055] y p (Γ)=y1(Γ-1)-y2(Γ-1)+y(Γ-1)

[0056] y p (Γ) is the output of the Smith-like prediction algorithm at the current calculation step Γ; y1(Γ-1) is the output of G1(s) at the previous calculation step Γ-1, y2(Γ-1) is the output of G2(s) at the previous calculation step Γ-1, and the input of G1(s) is the actual industrial system input u(Γ-1) at the previous calculation step, and the input of G2(s) is y1(Γ-1) at the previous calculation step Γ-1; G1(s) and G2(s) are calculation expressions designed by the Smith-like prediction algorithm, k1 is the gain of G1(s), and T1 is the time constant of G1(s) and G2(s); generally, k1=K and T1=T.

[0057] Step 3: Design a model-assisted extended state observation algorithm based on the input of the actual industrial system in step 1 and the output of the Smith prediction algorithm in step 2:

[0058]

[0059] Among them, z1(Γ+1) and z1(Γ) are the tracking values ​​of the actual industrial system output y(Γ+1) and y(Γ) at the next calculation step Γ+1 and the current calculation step Γ respectively; z2(Γ+1) and z2(Γ) are the tracking values ​​of the first-order derivatives of the actual industrial system output at the next calculation step Γ+1 and the current calculation step Γ respectively; z3(Γ+1) and z3(Γ) are the observed values ​​of the interference to the actual industrial system at the next calculation step Γ+1 and the current calculation step Γ respectively; h is the sampling step; u(Γ) is the actual industrial system output at the current calculation step Γ; β1, β2, β3 and b0 are calculation coefficients; generally, and where ω o is the bandwidth of the model-assisted extended state observation algorithm and ω o ∈(0,10 10 ], ξ is an adjustable parameter and ξ∈(0.1,10 10 ]; the value range of h is [0.001,100]. In this embodiment, ω o =0.4 and ξ=20; h=0.1.

[0060] Step 4: The output of the extended state observation algorithm obtained in step 3 and the set value of the actual industrial system are used to design the control law algorithm as follows:

[0061]

[0062] or,

[0063]

[0064] Where u(Γ+2) is the input of the actual industrial system in the next two calculation steps Γ+2 for the control rate calculation, r(Γ+1) is the set value of the actual industrial system in the next calculation step Γ+1, and k p , k d To calculate the coefficient, we generally have and k d =2ω c , where ω c is the bandwidth of the control law algorithm and ω c ∈(0,10 10 In this embodiment, c =0.5.

[0065] Step 5: Send the input u(Γ+2) of the two calculation steps Γ+2 of the actual industrial system obtained in step 4 to the actuator, adjust the opening of the actuator, and realize the control quantity adjustment of the closed-loop system, thereby realizing the output quantity adjustment of the actual industrial system.

[0066] Figure 4 It is a comparison chart of the actual industrial object setting value, the output value of the method of the present invention and the output value of the comparison method in the embodiment; a first-order active disturbance rejection control algorithm based on Smith-like estimation in the patent with application number 202011125339.6, whose parameters are k1=K, T1=T, β1=1.2, β2=0.48, β3=0.064, b0=0.10, k p = 0.25 and k d =1.0; the thin solid line, the dotted line and the thick solid line are the set value of the actual industrial system in the embodiment, the output value of the comparison method (patent application number: 202011125339.6) and the output value of the method of the present invention, respectively. The specific simulation process is: at the beginning of the simulation, the system is in a steady state, the set value is changed from 0 to 1 at 10s, and the closed-loop control quantity is disturbed at 200s, from 0 to 1, until the simulation ends at 400s. It can be seen from the simulation that the method of the present invention has a relatively fast tracking ability and a strong anti-interference ability by making full use of the known model information.

[0067] In summary, this embodiment proposes a second-order improved ADRC design method based on model-assisted and Smith-predictor-like methods, which retains the advantages of the existing improved ADRC algorithm, such as simple structure and easy tuning, and can make full use of known model information, improve the estimation accuracy of the extended state observer, and enhance the tracking capability and anti-interference capability. This method can provide an effective and reliable control strategy for solving the control problem of a class of high-order inertial industrial systems.

[0068] This embodiment also provides a second-order improved active disturbance rejection control design device based on model assistance and Smith-like prediction, including:

[0069] at least one processor;

[0070] at least one memory for storing at least one program;

[0071] When the at least one program is executed by the at least one processor, the at least one processor implements the above method.

[0072] A second-order improved auto-disturbance rejection control design device based on model assistance and Smith-prediction quasi-estimation in this embodiment can execute a second-order improved auto-disturbance rejection control design method based on model assistance and Smith-prediction quasi-estimation provided by the method embodiment of the present invention, can execute any combination of implementation steps of the method embodiment, and has the corresponding functions and beneficial effects of the method.

[0073] The present application also discloses a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device can read the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes Figure 2 or Figure 3 The method shown.

[0074] This embodiment also provides a storage medium storing instructions or programs that can execute a second-order improved automatic anti-disturbance control design method based on model assistance and Smith-like estimation provided by the method embodiment of the present invention. When the instructions or programs are run, any combination of implementation steps of the method embodiment can be executed, and the corresponding functions and beneficial effects of the method can be obtained.

[0075] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part for which is described as a larger operation is performed independently.

[0076] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features described may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0077] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0078] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0079] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0080] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0081] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0082] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0083] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the above embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A second-order improved active disturbance rejection control design method based on model assistance and Smith-like prediction, characterized in that: The following steps are involved: The actual industrial system is described using a high-order inertial system; Design of Smith Prediction algorithm based on input and output of high-order inertial system; According to the output of the Smith-like prediction algorithm and the input of the high-order inertial system, a model-assisted extended state observation algorithm is designed. Design a control law algorithm based on the output of the extended state observation algorithm and the system setting value; Obtain new input values ​​of the high-order inertial system and adjust and control the output of the actual industrial system according to the new input values; The mathematical expression described by a high-order inertial system is: Where Y(s) and U(s) represent the output and input of the actual industrial system, s, K, T and n represent the differential operator, the gain of the actual industrial system, the time constant of the actual industrial system and the order of the actual industrial system, respectively. n≥2； The expression of the Smith-like prediction algorithm is as follows: y p (C)=y1(C-1)-y2(C-1)+y(C-1) In the formula, y p (Γ) is the output of the Smith-like prediction algorithm at the current calculation step Γ; y1(Γ-1) is the output of G1(s) at the previous calculation step Γ-1, y2(Γ-1) is the output of G2(s) at the previous calculation step Γ-1, and The input of G1(s) is the actual industrial system input u(Γ-1) at the previous calculation step, and the input of G2(s) is y1(Γ-1) at the previous calculation step Γ-1; G1(s) and G2(s) are calculation expressions designed for the Smith prediction algorithm: Where k1 is the gain of G1(s), T1 is the time constant of G1(s) and G2(s); The expression of the model-assisted extended state observation algorithm is as follows: Among them, z1(Γ+1) and z1(Γ) are the tracking values ​​of the actual industrial system output y(Γ+1) and y(Γ) at the next calculation step Γ+1 and the current calculation step Γ respectively; z2(Γ+1) and z2(Γ) are the tracking values ​​of the first-order derivatives of the actual industrial system output at the next calculation step Γ+1 and the current calculation step Γ respectively; z3(Γ+1) and z3(Γ) are the observed values ​​of the interference to the industrial system at the next calculation step Γ+1 and the current calculation step Γ respectively; h is the sampling step; u(Γ) is the actual industrial system output at the current calculation step Γ; β1, β2, β3 and b0 are calculation coefficients; The expression of the control law algorithm is as follows: or, Among them, u(Γ+2) is the input of the actual industrial system in the next two calculation steps Γ+2 for the control rate calculation, r(Γ+1) is the set value of the actual industrial system in the next calculation step Γ+1, and k p , k d is the calculation coefficient.

2. The second-order improved active disturbance rejection control design method based on model assistance and Smith-predictor-like according to claim 1 is characterized in that: The obtaining of new input values ​​of the high-order inertial system and adjusting and controlling the output of the actual industrial system according to the new input values ​​include: The input quantity u(Γ+2) of the two calculation steps Γ+2 under the high-order inertial system is sent to the actuator to adjust the opening of the actuator to achieve the control quantity adjustment of the closed-loop system, thereby realizing the output quantity adjustment of the actual industrial system.

3. A second-order improved active disturbance rejection control design device based on model assistance and Smith-like prediction, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the method according to any one of claims 1 to 2.

4. A computer-readable storage medium storing a program executable by a processor, characterized in that: The processor-executable program is used to perform the method according to any one of claims 1 to 2 when executed by the processor.

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