A servo system control method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application provide a servo system control method and device, electronic equipment and storage medium, applied to an antenna electromechanical servo system, comprising: generating a system state equation according to a moment balance model, and performing variable transformation on the system state equation to obtain a control parameter equation, further, constructing an adaptive sliding mode control law to control the antenna electromechanical servo system, so that based on the above manner, the dynamic adjustment of the uncertain factors in the moment balance model and the dynamic suppression of the influence of system disturbance are realized in the control process, therefore, the above servo system control method proposed in the embodiments of the present application can effectively improve the control performance of the servo system, at the same time, the variable transformation is performed by using the transformation relationship, which simplifies the control law design and further reduces the calculation burden of the servo system.

Description

Technical Field

[0001] This invention relates to the field of antenna servo control technology, and in particular to a servo system control method, device, electronic device, and storage medium. Background Technology

[0002] A servo system is a feedback control system used to accurately follow or reproduce a process. In the field of antenna electromechanical control, it is often used for servo tracking of antenna position or to achieve smooth control of antenna movement.

[0003] However, in reality, the following uncertainties still exist: 1) uncertainty of system modeling parameters, 2) uncertainty of external nonlinear disturbances, and 3) uncertainty of unmodeled system dynamics. These problems can easily cause limit cycle oscillations and low-speed crawling in the servo system, thereby reducing the control performance of the servo system. Summary of the Invention

[0004] This application provides a servo system control method, device, electronic device, and storage medium to improve the control performance of an antenna electromechanical servo system.

[0005] In a first aspect, embodiments of this application provide a servo system control method, which is applied to an antenna electromechanical servo system, including:

[0006] The system state equations are generated based on the torque balance model, wherein the components of the system state equations include at least the specified system state variables;

[0007] The system state equation is transformed by variables to obtain the control parameter equation, wherein the control parameter equation contains control parameters, which are used to characterize the uncertainties of the torque balance model;

[0008] An adaptive sliding mode control law is constructed based on the control parameter equations, and the adaptive sliding mode control law is used to control the antenna electromechanical servo system.

[0009] In one optional embodiment, generating the system state equations based on the torque balance model includes:

[0010] The system state equations are generated based on the initial definition of the torque balance model, wherein the initial definition is: The system state equation is associated with the state generation relationship, and the system state equation is:

[0011]

[0012] The state generation relation includes at least one or a combination of the following:

[0013]

[0014] Where x1 and x2 are specified system state variables, a, b, and Δ are system parameters, J is the moment of inertia of the antenna, u is the control input, k and p are positive constants, d(t) is an uncertainty factor, and d(t) is in a closed real interval.

[0015] In an optional embodiment, the step of performing variable transformation on the system state equations to obtain control parameter equations includes:

[0016] The system state equations are transformed to obtain a first intermediate equation, wherein the first intermediate equation is associated with a first transformation relationship, and the first intermediate equation is: The first transformation relationship includes at least one or a combination of the following:

[0017] z1 = x1 - x 1d z2 = x2 - α1,

[0018] Where, x 1d This serves as the system's reference position signal.

[0019] By performing variable transformations on the first intermediate equation, a second intermediate equation is obtained, wherein the second intermediate equation is associated with a second transformation relationship. The second intermediate equation is:

[0020]

[0021] The second transformation relationship includes at least:

[0022] By performing variable transformation on the second intermediate equation, the control parameter equation is obtained, wherein the control parameter equation is associated with the third transformation relationship, and the control parameter equation is as follows:

[0023]

[0024] The third transformation relationship includes at least one or a combination of the following:

[0025]

[0026] Wherein, β and p are control parameters, and β and p are used to characterize the uncertainties of the torque balance model.

[0027] Secondly, embodiments of this application provide a control device for a servo system, which is applied to an antenna electromechanical servo system, comprising:

[0028] A generation module is used to generate system state equations based on a torque balance model, wherein the components of the system state equations include at least specified system state variables.

[0029] The transformation module is used to perform variable transformation on the system state equation to obtain the control parameter equation, wherein the control parameter equation includes control parameters, which are used to characterize the uncertainties of the torque balance model;

[0030] The control module is used to construct an adaptive sliding mode control law based on the control parameter equations, and to control the antenna electromechanical servo system using the adaptive sliding mode control law.

[0031] In an optional embodiment, generating the system state equations based on the torque balance model further includes:

[0032] The system state equations are generated based on the initial definition of the torque balance model, wherein the initial definition is: The system state equation is associated with the state generation relationship, and the system state equation is:

[0033]

[0034] The state generation relation includes at least one or a combination of the following:

[0035]

[0036] Where x1 and x2 are specified system state variables, a, b, and Δ are system parameters, J is the moment of inertia of the antenna, u is the control input, k and p are positive constants, d(t) is an uncertainty factor, and d(t) is in a closed real interval.

[0037] In an optional embodiment, the step of performing variable transformation on the system state equation to obtain the control parameter equation further includes:

[0038] The system state equations are transformed to obtain a first intermediate equation, wherein the first intermediate equation is associated with a first transformation relationship, and the first intermediate equation is: The first transformation relationship includes at least one or a combination of the following:

[0039] z1 = x1 - x 1d z2 = x2 - α1,

[0040] Where, x 1d This serves as the system's reference position signal.

[0041] By performing variable transformations on the first intermediate equation, a second intermediate equation is obtained, wherein the second intermediate equation is associated with a second transformation relationship. The second intermediate equation is:

[0042]

[0043] The second transformation relationship includes at least:

[0044] By performing variable transformation on the second intermediate equation, the control parameter equation is obtained, wherein the control parameter equation is associated with the third transformation relationship, and the control parameter equation is as follows:

[0045]

[0046] The third transformation relationship includes at least one or a combination of the following:

[0047]

[0048] Wherein, β and p are control parameters, and β and p are used to characterize the uncertainties of the torque balance model.

[0049] In an optional embodiment, the construction of the adaptive sliding mode control law based on the control parameter equation further includes any one of the following:

[0050] Based on the control parameter equations and the Lyapunov function, a first adaptive sliding mode control law is constructed, wherein the Lyapunov function is: The first adaptive sliding mode control law is associated with a first control relationship, and the first adaptive sliding mode control law is:

[0051]

[0052] The first control relationship includes at least:

[0053] in, For the estimated value of β, η≥|p max γ is a positive constant;

[0054] Based on the control parameter equations, the Lyapunov function, and the hyperbolic tangent function, a second adaptive sliding mode control law is constructed, wherein the Lyapunov function is: The hyperbolic tangent function is tanh. The second adaptive sliding mode control law is associated with the second control relationship. The second adaptive sliding mode control law is:

[0055]

[0056] The second control relationship includes at least:

[0057] in, η≥|p max ε>0, γ is a positive constant.

[0058] Thirdly, an electronic device is proposed, comprising a processor and a memory, wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps of the servo system control method described in the first aspect.

[0059] Fourthly, a computer-readable storage medium is provided, comprising program code that, when executed on an electronic device, causes the electronic device to perform the steps of the servo system control method described in the first aspect.

[0060] The technical effects of the embodiments of this application are as follows:

[0061] This application provides a servo system control method, device, electronic device, and storage medium applied to an antenna electromechanical servo system. The method includes: generating a system state equation based on a torque balance model, performing variable transformation on the system state equation to obtain control parameter equations, and further constructing an adaptive sliding mode control law to control the antenna electromechanical servo system. Based on the above method, dynamic adjustment of uncertainties in the torque balance model and dynamic suppression of system disturbances are achieved during the control process. Therefore, the servo system control method proposed in this application can effectively improve the control performance of the servo system. Simultaneously, the use of transformation relationships for variable transformation simplifies the control law design and further reduces the computational burden of the servo system. Attached Figure Description

[0062] Figure 1 A flowchart of a servo system control method provided in an embodiment of this application;

[0063] Figure 2 This is a schematic diagram of the structure of a servo system control device provided in an embodiment of this application;

[0064] Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0065] The technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this invention.

[0066] It should be noted that in the description of this application, "multiple" is understood as "at least two". "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. A connected to B can represent: A and B directly connected, or A and B connected through C. Furthermore, in the description of this application, terms such as "first" and "second" are used only for descriptive purposes and should not be construed as indicating or implying relative importance or order.

[0067] First, the following explanations are provided for some of the nouns and terms used in the embodiments of this application:

[0068] Adaptive control: refers to a control algorithm that continuously extracts information about the model during system operation and adjusts the variables through adaptive algorithms to make the model more perfect.

[0069] Sliding Mode Control (SMC) refers to variable structure control with sliding modes. The sliding mode is the state of the system when it is restricted to moving on a certain submanifold. The sliding mode control method designs a suitable sliding mode control law so that the system state trajectory reaches the pre-set sliding manifold within a certain time and converges to the equilibrium point on the sliding surface in a designed manner.

[0070] Based on the above definitions, the design concept of this application is as follows:

[0071] In antenna electromechanical servo systems, there are still problems such as uncertainties in system modeling parameters, uncertainties in external nonlinear disturbances, and uncertainties in the dynamics of unmodeled systems, which lead to a reduction in the control performance of the servo system.

[0072] Based on this, the embodiments of this application adopt adaptive control and sliding mode control methods. Through a dedicated adaptive sliding mode control law, the negative impact of relevant uncertainties in the servo system is corrected, thereby improving the control performance of the servo system. At the same time, by using appropriate transformation relationships for variable transformation, the control law design is simplified, the computational complexity brought about by adaptive control is reduced, and the computational burden of the servo system is reduced.

[0073] Furthermore, this application can be applied to application scenarios using antenna servo control systems, such as antenna position tracking in antenna electromechanical servo systems. Taking the above scenario as an example, the servo system control method provided in this application will be further elaborated and explained below with reference to the accompanying drawings. Figure 1 As shown, it includes:

[0074] S101: Generate the system state equations based on the torque balance model.

[0075] Specifically, a torque balance model for the electromechanical servo control of the antenna is established. The initial definition of this torque balance model includes uncertainties.

[0076] Optionally, the system state equations are generated based on the initial definition of the torque balance model of the antenna electromechanical servo control, as shown in equation (1) below:

[0077]

[0078] In one specific implementation, the system state equation is associated with a state generation relation. In S101, the system state equation can be generated through an initial definition and a state generation relation. Specifically, the state generation relation includes at least any one or a combination of the following (2)-(6):

[0079]

[0080]

[0081]

[0082]

[0083]

[0084] Where x1 and x2 are specified system state variables, a, b, and Δ are system parameters, J is the moment of inertia of the antenna, u is the control input, k and p are positive constants, d(t) is an uncertainty factor, and d(t) is in a closed real interval.

[0085] For example, the aforementioned uncertainties d(t) may include: unmodeled nonlinear friction, unmodeled dynamics, external disturbances, etc.

[0086] Based on any one or a combination of the above state generation relationships, the torque balance model can generate the system state equation in the form of equation (7):

[0087]

[0088] As can be seen, in the above equation (7), the torque balance model is indirectly represented according to the specified system state variables such as x1, x2, a, b, Δ, etc., so that the adaptive control method can be used to deal with the uncertainty of the model parameters in the subsequent process, and the sliding mode control method can be used to deal with the uncertainty of external nonlinear disturbances. This reduces the computational burden of the system and improves the control performance of the antenna electromechanical servo system.

[0089] S102: Perform variable transformation on the system state equations to obtain the control parameter equations.

[0090] Specifically, the variable transformation is performed according to the set steps, and the specific process is as follows:

[0091] First, the system state equations are transformed to obtain the first intermediate equation.

[0092] In one specific implementation, the first intermediate equation is associated with a first transformation relation. The first intermediate equation can be obtained from the system state equation and the first transformation relation. Specifically, the first transformation relation includes at least any one or a combination of the following (8)-(12):

[0093] z1 = x1 - x 1d (8)

[0094] z2=x2-α1(9)

[0095]

[0096]

[0097]

[0098] In equations (8) and (11) above, x 1d This serves as the system's reference position signal.

[0099] Based on any one or combination of the above first intermediate relations, variable transformation of the system state equation can be performed to obtain the first intermediate equation in the form of equation (13):

[0100]

[0101] Furthermore, by performing variable transformations on the first intermediate equation, a second intermediate equation is obtained.

[0102] In one specific implementation, the second intermediate equation is associated with a second transformation relation. The second intermediate equation can be obtained from the second intermediate equation and the second transformation relation. Specifically, the second transformation relation includes at least the following equation (14):

[0103]

[0104] Based on the second intermediate relationship mentioned above, by transforming the variables of the first intermediate equation, we can obtain the first intermediate equation in the form shown in equation (15):

[0105]

[0106] Finally, the second intermediate equation is transformed to obtain the control parameter equation.

[0107] In one specific implementation, the control parameter equation is associated with a third transformation relation. The control parameter equation can be obtained from the second intermediate equation and the third transformation relation. Specifically, the third transformation relation includes at least any one or a combination of the following equations (16)-(18):

[0108]

[0109]

[0110]

[0111] In equations (16) and (18) above, β and p are control parameters, and β and p are used to characterize the uncertainty factors of the torque balance model.

[0112] Based on the aforementioned third intermediate relationship, by transforming the variables of the second intermediate equation, we can obtain the control parameter equation in the form shown in equation (19):

[0113]

[0114] As can be seen from equation (19) above, the above variable transformation transforms the uncertainty of model parameters a and b in the initial definition into the uncertainty of vector β in the control parameter equation; and transforms the uncertainty factor d(t) in the initial definition into the control parameter p in the control parameter equation, thereby realizing the integrated calculation of uncertainty factors and their corresponding dynamic adjustment in the control parameter equation, thereby ensuring the simplified design of the control law and reducing the computational burden required by the subsequent system.

[0115] S103: Construct an adaptive sliding mode control law based on the control parameter equations, and use the adaptive sliding mode control law to control the antenna electromechanical servo system.

[0116] Specifically, it includes any of the following situations:

[0117] Case 1: Construct the first adaptive sliding mode control law based on the control parameter equations and Lyapunov functions.

[0118] In one specific implementation, the first adaptive sliding mode control law can be associated with a first control relationship. The first adaptive sliding mode control law can then be obtained through the control parameter equations, the Lyapunov function, and the first control relationship. Specifically, the Lyapunov function is shown in equation (20) below:

[0119]

[0120] The first control relationship includes at least the defined relationship shown in equation (21) below:

[0121]

[0122] in, For the estimated value of β, η≥|p max γ is a positive constant.

[0123] Based on the first control relationship, the first adaptive sliding mode control law can be constructed as follows (22):

[0124]

[0125] To demonstrate the stability of the antenna electromechanical servo system's control state when controlled using the aforementioned first adaptive sliding mode control law, the following steps are performed: First, differentiate equation (20) to obtain equation (23) as follows:

[0126]

[0127] Based on the above equation (23), it can be seen that after substituting the first adaptive sliding mode control law, the control state of the antenna electromechanical servo system is as shown in the following equation (24):

[0128]

[0129] From the above equation (24), it can be seen that the control state of the antenna electromechanical servo system is stable when the first adaptive sliding mode control law is used for control.

[0130] Case 2: Construct a second adaptive sliding mode control law based on the control parameter equations, Lyapunov function, and hyperbolic tangent function.

[0131] To mitigate input chattering caused by the discontinuous switching characteristics of the sign function in the adaptive sliding mode control law, a second adaptive sliding mode control law is constructed using control parameter equations, Lyapunov functions, and hyperbolic tangent functions.

[0132] In one specific implementation, the second adaptive sliding mode control law can be associated with a second control relationship.

[0133] The second adaptive sliding mode control law can be obtained through the control parameter equations, the Lyapunov function, and the second control relationship. Specifically, the Lyapunov function is shown in equation (20) above, which is:

[0134]

[0135] The second control relationship includes at least the defined relationship shown in equation (25) below:

[0136]

[0137] in, For the estimated value of β, η≥|p max ε>0, γ is a positive constant.

[0138] Based on the control parameter equations, Lyapunov functions, and the second control relationship, the second adaptive sliding mode control law can be constructed as follows (26):

[0139]

[0140] To demonstrate the stability of the antenna electromechanical servo system's control state when controlled using the aforementioned second adaptive sliding mode control law, the following steps are performed: First, based on the derivative equation shown in equation (23) above, the result is:

[0141]

[0142] Substituting the above second adaptive sliding mode control law, the control state of the antenna electromechanical servo system is as shown in equation (27):

[0143]

[0144] Based on the above equation (27), it can be seen that the control state of the antenna electromechanical servo system is stable when the second adaptive sliding mode control law is used for control.

[0145] As can be seen, the servo system control method provided in this application generates system state equations based on a torque balance model, performs variable transformation on the system state equations to obtain control parameter equations, and further constructs an adaptive sliding mode control law to control the antenna electromechanical servo system. Thus, based on the above method, dynamic adjustment of uncertainties in the torque balance model and dynamic suppression of system disturbance effects are achieved in stable control. Therefore, the servo system control method proposed in this application can effectively improve the control performance of the servo system. At the same time, the use of transformation relationships for variable transformation simplifies the control law design and further reduces the computational burden of the servo system.

[0146] Furthermore, based on the same technical concept, embodiments of this application also provide a servo system control device, which is applied to an antenna electromechanical servo system and used to implement the above-described method flow of embodiments of this application. See also... Figure 2 As shown, the device includes: a generation module 201, a transformation module 202, and a control module 203, wherein:

[0147] The generation module 201 is used to generate system state equations based on the torque balance model, wherein the components of the system state equations include at least specified system state variables.

[0148] The transformation module 202 is used to perform variable transformation on the system state equation to obtain the control parameter equation, wherein the control parameter equation includes control parameters, which are used to characterize the uncertainties of the torque balance model.

[0149] The control module 203 is used to construct an adaptive sliding mode control law based on the control parameter equation, and to control the antenna electromechanical servo system using the adaptive sliding mode control law.

[0150] In an optional embodiment, generating the system state equations based on the torque balance model further includes:

[0151] The system state equations are generated based on the initial definition of the torque balance model, wherein the initial definition is: The system state equation is associated with the state generation relationship, and the system state equation is:

[0152]

[0153] The state generation relation includes at least one or a combination of the following:

[0154]

[0155] Where x1 and x2 are specified system state variables, a, b, and Δ are system parameters, J is the moment of inertia of the antenna, u is the control input, k and p are positive constants, d(t) is an uncertainty factor, and d(t) is in a closed real interval.

[0156] In an optional embodiment, the step of performing variable transformation on the system state equation to obtain the control parameter equation further includes:

[0157] The system state equations are transformed to obtain a first intermediate equation, wherein the first intermediate equation is associated with a first transformation relationship, and the first intermediate equation is: The first transformation relationship includes at least one or a combination of the following:

[0158]

[0159] Where, x 1d This serves as the system's reference position signal.

[0160] By performing variable transformations on the first intermediate equation, a second intermediate equation is obtained, wherein the second intermediate equation is associated with a second transformation relationship. The second intermediate equation is:

[0161]

[0162] The second transformation relationship includes at least:

[0163] By performing variable transformation on the second intermediate equation, the control parameter equation is obtained, wherein the control parameter equation is associated with the third transformation relationship, and the control parameter equation is as follows:

[0164]

[0165] The third transformation relationship includes at least one or a combination of the following:

[0166]

[0167] Wherein, β and p are control parameters, and β and p are used to characterize the uncertainties of the torque balance model.

[0168] In an optional embodiment, the construction of the adaptive sliding mode control law based on the control parameter equation further includes any one of the following:

[0169] Based on the control parameter equations and the Lyapunov function, a first adaptive sliding mode control law is constructed, wherein the Lyapunov function is: The first adaptive sliding mode control law is associated with a first control relationship, and the first adaptive sliding mode control law is:

[0170]

[0171] The first control relationship includes at least:

[0172] in, For the estimated value of β, η≥|p max γ is a positive constant;

[0173] Based on the control parameter equations, the Lyapunov function, and the hyperbolic tangent function, a second adaptive sliding mode control law is constructed, wherein the Lyapunov function is: The hyperbolic tangent function is tanh. The second adaptive sliding mode control law is associated with the second control relationship. The second adaptive sliding mode control law is:

[0174]

[0175] The second control relationship includes at least:

[0176] in, η≥|p max ε>0, γ is a positive constant.

[0177] Based on the same inventive concept as the embodiments described above, this application also provides an electronic device that can be used for servo system control. In one embodiment, the electronic device can be a server, a terminal device, or other electronic equipment. In this embodiment, the structure of the electronic device can be as follows: Figure 3 As shown, it includes a memory 301, a communication interface 303, and one or more processors 302.

[0178] The memory 301 is used to store computer programs executed by the processor 302. The memory 301 may mainly include a program storage area and a data storage area. The program storage area may store the operating system and programs required to run instant messaging functions, etc.; the data storage area may store various instant messaging information and operation instruction sets, etc.

[0179] Memory 301 may be volatile memory, such as random-access memory (RAM); memory 301 may also be non-volatile memory, such as read-only memory, flash memory, hard disk drive (HDD), or solid-state drive (SSD); or memory 301 may be any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. Memory 301 may be a combination of the above-described memories.

[0180] The processor 302 may include one or more central processing units (CPUs) or digital processing units, etc. The processor 302 is used to implement the aforementioned servo system control method when it calls the computer program stored in the memory 301.

[0181] Communication interface 303 is used to communicate with terminal devices and other servers.

[0182] This application embodiment does not limit the specific connection medium between the memory 301, communication interface 303, and processor 302 described above. This application embodiment... Figure 3 The memory 301 and the processor 302 are connected via a bus 304, and the bus 304 is in Figure 3 The connections between other components are shown in thick lines only and are not intended to be limiting. Bus 304 can be divided into address bus, data bus, control bus, etc. For ease of illustration, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0183] Based on the same inventive concept, embodiments of this application also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform a servo system control method described above.

[0184] It should be noted that although several units or sub-units of the device have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of this application, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units.

[0185] Furthermore, although the operations of the method of this application are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0186] This application provides a servo system control method, device, electronic device, and storage medium applied to an antenna electromechanical servo system. The method includes: generating a system state equation based on a torque balance model, performing variable transformation on the system state equation to obtain control parameter equations, and further constructing an adaptive sliding mode control law to control the antenna electromechanical servo system. Based on the above method, dynamic adjustment of uncertainties in the torque balance model and dynamic suppression of system disturbances are achieved during the control process. Therefore, the servo system control method proposed in this application can effectively improve the control performance of the servo system. Simultaneously, the use of transformation relationships for variable transformation simplifies the control law design and further reduces the computational burden of the servo system.

[0187] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0188] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0189] Program code for performing the operations of this application can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0190] In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0191] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0192] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0193] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A servo system control method, characterized in that, Applications include antenna electromechanical servo systems, including: The system state equations are generated based on the torque balance model, wherein the components of the system state equations include at least the specified system state variables; The system state equation is transformed by variables to obtain the control parameter equation, wherein the control parameter equation contains control parameters, which are used to characterize the uncertainties of the torque balance model; An adaptive sliding mode control law is constructed based on the control parameter equations, and the adaptive sliding mode control law is used to control the antenna electromechanical servo system. If the adaptive sliding mode control law is the second adaptive sliding mode control law, then the step of constructing the adaptive sliding mode control law according to the control parameter equation includes: constructing the second adaptive sliding mode control law according to the control parameter equation, the Lyapunov function, and the hyperbolic tangent function; The second adaptive sliding mode control law is constructed based on the control parameter equations, the Lyapunov function, and the hyperbolic tangent function, wherein the Lyapunov function is: The hyperbolic tangent function is tanh. The second adaptive sliding mode control law is associated with the second control relationship. The second adaptive sliding mode control law is: ， The second control relationship includes at least: , in, , , For positive integers, V To construct the Lyapunov function, , , , , , , For system parameters, For the system reference position signal, , For the specified system state variables.

2. The method as described in claim 1, characterized in that, The generation of system state equations based on the torque balance model includes: The system state equations are generated based on the initial definition of the torque balance model, wherein the initial definition is: The system state equation is associated with the state generation relationship, and the system state equation is: ， The state generation relation includes at least one or a combination of the following: ， ， ， ， ， in, , For the specified system state variables, , , For system parameters, Let be the moment of inertia of the antenna. To control the input, , For positive integers, As an uncertain factor, It lies within a closed interval of real numbers.

3. The method as described in claim 2, characterized in that, The process of transforming the system state equations to obtain the control parameter equations includes: The system state equations are transformed to obtain a first intermediate equation, wherein the first intermediate equation is associated with a first transformation relationship, and the first intermediate equation is: The first transformation relationship includes at least one or a combination of the following: ， ， ， ， ， in, This serves as the system's reference position signal. By performing variable transformations on the first intermediate equation, a second intermediate equation is obtained, wherein the second intermediate equation is associated with a second transformation relationship. The second intermediate equation is: ， The second transformation relationship includes at least: ; By performing variable transformation on the second intermediate equation, the control parameter equation is obtained, wherein the control parameter equation is associated with the third transformation relationship, and the control parameter equation is as follows: ， The third transformation relationship includes at least one or a combination of the following: ， ， in, , To control parameters, and , Used to characterize the uncertainties in the torque balance model.

4. The method according to any one of claims 1-3, characterized in that, If the adaptive sliding mode control law is the first adaptive sliding mode control law, then the construction of the adaptive sliding mode control law based on the control parameter equation includes: Based on the control parameter equations and the Lyapunov function, a first adaptive sliding mode control law is constructed, wherein the Lyapunov function is: The first adaptive sliding mode control law is associated with the first control relationship, and the first adaptive sliding mode control law is: ， The first control relationship includes at least: , in, for The estimated value, , It is a positive number.

5. A servo system control device, characterized in that, Applications include antenna electromechanical servo systems, including: A generation module is used to generate system state equations based on a torque balance model, wherein the components of the system state equations include at least specified system state variables. The transformation module is used to perform variable transformation on the system state equation to obtain the control parameter equation, wherein the control parameter equation includes control parameters, which are used to characterize the uncertainties of the torque balance model; The control module is used to construct an adaptive sliding mode control law based on the control parameter equations, and to use the adaptive sliding mode control law to control the antenna electromechanical servo system. If the adaptive sliding mode control law is the second adaptive sliding mode control law, then the step of constructing the adaptive sliding mode control law according to the control parameter equation includes: constructing the second adaptive sliding mode control law according to the control parameter equation, the Lyapunov function, and the hyperbolic tangent function; The second adaptive sliding mode control law is constructed based on the control parameter equations, the Lyapunov function, and the hyperbolic tangent function, wherein the Lyapunov function is: The hyperbolic tangent function is tanh. The second adaptive sliding mode control law is associated with the second control relationship. The second adaptive sliding mode control law is: ， The second control relationship includes at least: , in, , , For positive integers, V To construct the Lyapunov function, , , , , , , For system parameters, For the system reference position signal, , For the specified system state variables.

6. The apparatus as claimed in claim 5, characterized in that, The step of generating the system state equation based on the torque balance model further includes: The system state equations are generated based on the initial definition of the torque balance model, wherein the initial definition is: The system state equation is associated with the state generation relationship, and the system state equation is: ， The state generation relation includes at least one or a combination of the following: ， ， ， ， ， in, , For the specified system state variables, , , For system parameters, Let be the moment of inertia of the antenna. To control the input, , For positive integers, As an uncertain factor, It lies within a closed interval of real numbers.

7. The apparatus as claimed in claim 6, characterized in that, The step of transforming the system state equations to obtain the control parameter equations further includes: The system state equations are transformed to obtain a first intermediate equation, wherein the first intermediate equation is associated with a first transformation relationship, and the first intermediate equation is: The first transformation relationship includes at least one or a combination of the following: ， ， ， ， ， in, This serves as the system's reference position signal. By performing variable transformations on the first intermediate equation, a second intermediate equation is obtained, wherein the second intermediate equation is associated with a second transformation relationship. The second intermediate equation is: ， The second transformation relationship includes at least: ; By performing variable transformation on the second intermediate equation, the control parameter equation is obtained, wherein the control parameter equation is associated with the third transformation relationship, and the control parameter equation is as follows: ， The third transformation relationship includes at least one or a combination of the following: ， ， ， in, , To control parameters, and , Used to characterize the uncertainties in the torque balance model.

8. The apparatus according to any one of claims 5-7, characterized in that, If the adaptive sliding mode control law is the first adaptive sliding mode control law, then the step of constructing the adaptive sliding mode control law based on the control parameter equation further includes: Based on the control parameter equations and the Lyapunov function, a first adaptive sliding mode control law is constructed, wherein the Lyapunov function is: The first adaptive sliding mode control law is associated with the first control relationship, and the first adaptive sliding mode control law is: ， The first control relationship includes at least: , in, for The estimated value, , It is a positive number.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1-4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-4.

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