Adaptive containment controller design method and related device

Abstract

The invention relates to a self-adaptive containment controller design method and a related device, and belongs to the technical field of artificial intelligence theoretical foundation.The self-adaptive containment controller design method comprises the steps that an initial driving system and an initial response system of a time-delay inertial memristive neural network with a reaction-diffusion term are constructed; the initial response system comprises a controller to be designed; according to a differential inclusion theory, processing orders of the initial driving system and the initial response system by adopting a variable transformation method to obtain a target driving system and a target response system, and calculating a synchronization error; and designing the controller to be designed based on the synchronization error to obtain a self-adaptive containment controller of the time-delay inertial memristor neural network with a reaction-diffusion term, and controlling the target driving system and the target response system to be synchronized by the self-adaptive containment controller. According to the invention, the driving system and the response system of the time-delay inertial memristor neural network with the reaction-diffusion term can be synchronized.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to a design method for an adaptive containment controller and a related device. Background Art

[0002] Memristors are considered to be the fourth basic element in circuits in addition to resistors, capacitors and inductors. Memristors have the characteristics of non-volatility, high integration, low power consumption and good scalability, making them ideal components for simulating neuronal synapses. Subsequently, memristor neural networks were proposed, which have higher practicality and flexibility compared to general neural networks.

[0003] In the hardware implementation of memristor neural networks, the switching speed of electronic devices and the transmission speed of electrical signals are limited, which leads to the inevitable time lag phenomenon in the system. In addition, most existing memristor neural network models are based on the assumption that the state of neurons is only related to time. However, in the actual circuit implementation, due to the movement of electrons in an inhomogeneous electromagnetic field, the structure and dynamic behavior of the system not only depend on time, but also on the spatial position of each variable, so the reaction-diffusion phenomenon is inevitable. Time lag and diffusion phenomena are one of the main factors that may cause poor performance of the system, so it is of practical significance to consider the influence of time lag and reaction-diffusion phenomena at the same time. With the continuous deepening of the study of complex networks, it is difficult for memristor neural networks to achieve certain specific dynamic behaviors by themselves. Therefore, designing an appropriate controller has become a problem of great concern to researchers. Common controllers include feedback control, adaptive control, etc. However, due to the large number of nodes in the neural network and the complex structural relationship, if control is applied to each node, it will not only waste resources but also have poor operability.

[0004] It can be seen that the existing controller cannot synchronize the driving system and the response system of the time-delay inertial memristor neural network with reaction-diffusion terms well. Summary of the invention

[0005] In view of this, it is necessary to provide an adaptive control controller design method and related devices to solve the problem that the existing controller cannot well synchronize the drive system and response system of the time-delay inertial memristor neural network with reaction-diffusion terms.

[0006] In order to solve the above problems, the present invention provides an adaptive pinning controller design method for realizing synchronization of a time-delay inertial memristor neural network with a reaction-diffusion term, the method comprising: Constructing an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term, and determining an initial response system corresponding to the initial driving system based on a preset driving-response strategy; the initial response system includes a controller to be designed; According to the differential inclusion theory, the variable transformation method is used to process the order of the initial drive system and the initial response system, and the target drive system and the target response system are obtained, and the synchronization error of the target drive system and the target response system is calculated; The controller to be designed is designed based on the synchronization error, and an adaptive pinning controller of a time-delay inertial memristor neural network with a reaction-diffusion term is obtained. The target drive system and the target response system of the adaptive pinning controller are synchronized.

[0007] In a possible implementation, the initial driving system for constructing a time-delay inertial memristor neural network with a reaction-diffusion term includes: Based on Kirchhoff’s current law, the i-th subsystem of the memristor neural network circuit is described as:

[0008] in is the inductor, is the inductor current, and are resistance and capacitance respectively, Represents the activation function and the inductor current The memory resistance between Represents the activation function and the inductor current The memristor between , Corresponding to the transmission delay; let , , we can get

[0009] For convenience of expression, let , , , , , it can be simplified to:

[0010] After the reaction-diffusion term is introduced into the memristor neural network circuit, the initial determination system of the time-delay inertial memristor neural network with reaction-diffusion term can be expressed as:

[0011] in , , , , is the reaction-diffusion coefficient, It is iNeurons in space x and time t The state of and is the memristor synaptic connection weight, which should satisfy the following conditions:

[0012]

[0013] in is a normal number, let , .

[0014] In a possible implementation, the initial response system corresponding to the initial drive type system is determined based on a preset drive-response strategy; the initial response system includes a controller to be designed, including: The initial response system corresponding to the initial driving system is determined based on the preset driving-response strategy as follows:

[0015] in, , is the controller to be designed, is the reaction-diffusion coefficient, It is i Neurons in space x and time t The state when.

[0016] In a possible implementation, the boundary conditions and initial values ​​of the initial response system are as follows:

[0017]

[0018] in, is a continuous and bounded function.

[0019] In one possible implementation, there must be The target drive system is:

[0020] in, ; Must exist The target response system is: .

[0021] In a possible implementation manner, the calculating the synchronization error between the target drive system and the target response system includes: The synchronization error calculation method is defined as: and , then the synchronization error between the target drive system and the target response system is calculated as:

[0022] in,

[0023]

[0024] In a possible implementation manner, the controller to be designed is designed based on the synchronization error to obtain the adaptive pinning controller of the time-delay inertial memristor neural network with reaction-diffusion term, including: For the aforementioned time-delay inertial memristor neural network with reaction-diffusion term The neurons are fixed and the following adaptive control controller is set:

[0025]

[0026]

[0027]

[0028]

[0029]

[0030] in, and is any positive constant, and are the parameters of the adaptive controller.

[0031] The present invention also provides an adaptive control controller design device, comprising: A system building module is used to build an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term, and determine an initial response system corresponding to the initial driving system based on a preset driving-response strategy; the initial response system includes a controller to be designed; The error calculation module is used to process the orders of the initial drive system and the initial response system by using the variable transformation method according to the differential inclusion theory, obtain the target drive system and the target response system, and calculate the synchronization error of the target drive system and the target response system; The controller design module is used to design the controller to be designed based on the synchronization error, and obtain an adaptive control controller of a time-delay inertial memristor neural network with a reaction-diffusion term. The adaptive control controller controls the synchronization of the target drive system and the target response system.

[0032] The present invention also provides an electronic device, comprising a memory and a processor, wherein: Memory, used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the method for designing an adaptive containment controller in any of the above embodiments.

[0033] The present invention also provides a computer-readable storage medium for storing a computer-readable program or instruction, which can implement the steps in the adaptive containment controller design method of any of the above-mentioned embodiments when the program or instruction is executed by a processor.

[0034] The beneficial effects of the present invention are as follows: the adaptive pinning controller design method provided by the present invention provides an initial drive system and an initial response system of a time-delay inertial memristor neural network with a reaction-diffusion term based on a drive-response strategy, analyzes the initial drive system and the initial response system, and combines the differential inclusion theory to obtain a target drive system and a target response system of the time-delay inertial memristor neural network with a reaction-diffusion term by using a variable transformation method, calculates the synchronization error of the target drive system and the target response system, and designs an adaptive pinning controller based on the synchronization error, which can synchronize the drive system and the response system of the time-delay inertial memristor neural network with a reaction-diffusion term, thereby ensuring the synchronization of the time-delay inertial memristor neural network with a reaction-diffusion term. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0036] Figure 1 A schematic flow chart of a method for designing an adaptive control controller provided by an embodiment of the present invention; Figure 2 A schematic diagram of the structure of an adaptive control controller design device provided by an embodiment of the present invention; Figure 3 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of this application and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0038] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0039] A specific embodiment of the present invention, as Figure 1 As shown, a method for designing an adaptive pinning controller is disclosed for realizing synchronization of a time-delay inertial memristor neural network with a reaction-diffusion term, the method comprising: S101, constructing an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term, and determining an initial response system corresponding to the initial driving system based on a preset driving-response strategy; the initial response system includes a controller to be designed; S102, according to differential inclusion theory, a variable transformation method is used to process the orders of the initial drive system and the initial response system, to obtain a target drive system and a target response system, and to calculate synchronization errors of the target drive system and the target response system; S103, designing a controller to be designed based on the synchronization error to obtain an adaptive control controller of a time-delay inertial memristor neural network with a reaction-diffusion term, wherein the adaptive control controller controls the synchronization of the target drive system and the target response system.

[0040] In an embodiment of the present invention, the provided adaptive containment controller design method can be implemented by relying on a computer device. Specifically, it is a design scheme for an adaptive controller for synchronizing a time-delay inertial memristor neural network with a reaction-diffusion term running on a computer device.

[0041] In an embodiment of the present invention, during the hardware implementation of the memristor neural network, the switching speed of the electronic device and the limitation of the transmission speed of the electrical signal cause the system to inevitably have a time lag phenomenon. In addition, most existing memristor neural network models are based on the assumption that the neuron state is only related to time. However, in the actual circuit implementation, due to the movement of electrons in an inhomogeneous electromagnetic field, the structure and dynamic behavior of the system not only depend on time, but also on the spatial position of each variable, so the reaction-diffusion phenomenon is inevitable. Therefore, when designing an adaptive control controller for a memristor neural network, the reaction-diffusion phenomenon needs to be considered. Therefore, an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term is constructed, and the initial response system corresponding to the initial driving system is determined according to the drive-response strategy; the initial response system includes a controller to be designed. Then, based on the differential inclusion theory, the idea of ​​variable transformation is used to process the orders of the initial drive system and the initial response system to obtain the target drive system and the target response system, and the synchronization error of the target drive system and the target response system is calculated; based on the synchronization error, the controller to be designed is designed to obtain an adaptive containment controller of a time-delay inertial memristor neural network with a reaction-diffusion term. Under the control of the adaptive containment controller, the target drive system and the target response system can be synchronized.

[0042] The adaptive pinning controller design method provided by the present invention provides an initial drive system and an initial response system of a time-delay inertial memristor neural network with a reaction-diffusion term based on a drive-response strategy, analyzes the initial drive system and the initial response system, and uses a variable transformation method in combination with differential inclusion theory to obtain a target drive system and a target response system of the time-delay inertial memristor neural network with a reaction-diffusion term, calculates the synchronization error of the target drive system and the target response system, and designs an adaptive pinning controller based on the synchronization error, which can synchronize the drive system and the response system of the time-delay inertial memristor neural network with a reaction-diffusion term, thereby ensuring the synchronization of the time-delay inertial memristor neural network with a reaction-diffusion term.

[0043] As a possible implementation of the present application, the initial driving system for constructing a time-delay inertial memristor neural network with a reaction-diffusion term includes: Based on Kirchhoff’s current law, the i-th subsystem of the memristor neural network circuit is described as:

[0044] in is the inductor, is the inductor current, and are resistance and capacitance respectively, Represents the activation function and the inductor current The memory resistance between Represents the activation function and the inductor current The memristor between , Corresponding to the transmission delay; let , , we can get

[0045] For convenience of expression, let , , , , , it can be simplified to:

[0046] After the reaction-diffusion term is introduced into the memristor neural network circuit, the initial determination system of the time-delay inertial memristor neural network with reaction-diffusion term can be expressed as:

[0047] in , , , , is the reaction-diffusion coefficient, It is i Neurons in space x and time t The state of and is the memristor synaptic connection weight, which should satisfy the following conditions:

[0048]

[0049] in is a normal number, let , .

[0050] Furthermore, an initial response system corresponding to the initial drive type system is determined based on a preset drive-response strategy; the initial response system includes a controller to be designed, including: The initial response system corresponding to the initial drive type system is determined based on a preset drive-response strategy; the initial response system includes a controller to be designed, including: The initial response system corresponding to the initial driving system is determined based on the preset driving-response strategy as follows:

[0051] in, , is the controller to be designed, is the reaction-diffusion coefficient, It is i Neurons in space x and time t The state when.

[0052] The boundary conditions and initial values ​​of the initial response system are as follows:

[0053]

[0054] in, is a Functions with the same characteristics.

[0055] Furthermore, there must be The target drive system is:

[0056] in, ; Must exist The target response system is: .

[0057] Furthermore, the synchronization error between the target drive system and the target response system is calculated, including: The synchronization error calculation method is defined as: and , then the synchronization error between the target drive system and the target response system is calculated as:

[0058] in,

[0059] .

[0060] Furthermore, the controller to be designed is designed based on the synchronization error, and an adaptive control controller of a time-delay inertial memristor neural network with a reaction-diffusion term is obtained, including: For the aforementioned time-delay inertial memristor neural network with reaction-diffusion term The neurons are fixed and the following adaptive control controller is set:

[0061]

[0062]

[0063]

[0064]

[0065]

[0066] in, and is any positive constant, and are the parameters of the adaptive controller.

[0067] In the embodiment of the present invention, in order to verify the above-mentioned adaptive controller, two assumptions are set: Assumption 1: Activation Function is bounded and satisfies the Lipschitz condition,

[0068] There is a positive constant and Make , in, .

[0069] Hypothesis 2: From Hypothesis 1, we can get

[0070] Next, consider an initial driving system with Dirichlet boundary conditions and provide the following boundary conditions and initial values:

[0071]

[0072] in, is a vector-valued continuous bounded function.

[0073] When studying the synchronization problem of time-delay memristor neural networks, in order to avoid resource waste, an adaptive pinning control scheme is considered. The neurons are fixed and the following adaptive controller is designed:

[0074]

[0075]

[0076]

[0077]

[0078]

[0079] in, and is any positive constant.

[0080] If the above adaptive pinning controller can synchronize the target drive system and the target response system of the time-delay inertial memristor neural network with reaction-diffusion term, the synchronization error should satisfy Assumptions 1 and 2, then 1) When , if the following inequality holds: (1) (2) (3) 2) When , satisfying the above inequalities (1) and (2) and satisfying (4) The synchronization error is asymptotically stable, and the target drive system and the target response system of the time-delay inertial memristor neural network with reaction-diffusion term can be synchronized through the adaptive control controller (6). Now let’s prove the above assumptions: Construct the Lyapunov-Krasovskii functional:

[0081] in

[0082] right The derivative is:

[0083]

[0084] but It is expressed as:

[0085]

[0086] in

[0087]

[0088]

[0089]

[0090]

[0091] The following discusses the following situations: 1) When According to inequalities (1), (2), and (3), we know that .

[0092] 2) When According to conditions (1), (2), and (4), we know .

[0093] Therefore, the target driving system and the target responding system of the time-delay inertial memristor neural network with reaction-diffusion term can be synchronized through an adaptive pinning controller.

[0094] The present invention takes into account the reaction diffusion of the time-delay inertial memristor neural network to simulate the effect of electrons moving in an inhomogeneous electric field. By designing an adaptive containment controller and using inequality technology and Lyapunov stability theory, the effect of the adaptive controller designed in this application is fully demonstrated.

[0095] In order to better implement the adaptive control controller design method in the embodiment of the present invention, based on the adaptive control controller design method, correspondingly, Figure 2 As shown, the embodiment of the present invention further provides an adaptive control controller design device, and the adaptive control controller design device 200 includes: The system construction module 201 is used to construct an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term, and determine an initial response system corresponding to the initial driving system based on a preset driving-response strategy; the initial response system includes a controller to be designed; The error calculation module 202 is used to process the orders of the initial drive system and the initial response system using the variable transformation method according to the differential inclusion theory, obtain the target drive system and the target response system, and calculate the synchronization error of the target drive system and the target response system; The controller design module 203 is used to design the controller to be designed based on the synchronization error to obtain an adaptive control controller of a time-delay inertial memristor neural network with a reaction-diffusion term, and the adaptive control controller controls the synchronization of the target drive system and the target response system.

[0096] The adaptive control controller design device 200 provided in the above embodiment can implement the technical solution described in the above adaptive control controller design method embodiment. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above adaptive control controller design method embodiment, which will not be repeated here.

[0097] like Figure 3 As shown, the present invention also provides an electronic device 300. The electronic device 300 includes a processor 301, a memory 302 and a display 303. Figure 3 Only some components of the electronic device 300 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0098] In some embodiments, the processor 301 may be a central processing unit (CPU), a microprocessor or other data processing chip, and is used to run program codes or process data stored in the memory 302, such as the adaptive control controller design method of the present invention.

[0099] In some embodiments, the processor 301 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, the processor 301 may be local or remote. In some embodiments, the processor 301 may be implemented in a cloud platform. In some embodiments, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-cloud, etc., or any combination thereof.

[0100] In some embodiments, the memory 302 may be an internal storage unit of the electronic device 300, such as a hard disk or memory of the electronic device 300. In other embodiments, the memory 302 may also be an external storage device of the electronic device 300, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the electronic device 300.

[0101] Furthermore, the memory 302 may include both an internal storage unit of the electronic device 300 and an external storage device. The memory 302 is used to store application software installed in the electronic device 300 and various data.

[0102] In some embodiments, the display 303 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 303 is used to display information of the electronic device 300 and to display a visual user interface. The components 301-303 of the electronic device 300 communicate with each other through a system bus.

[0103] In some embodiments, when the processor 301 executes the time-delay inertial memristor neural network synchronization program in the memory 302, the following steps may be implemented: Constructing an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term, and determining an initial response system corresponding to the initial driving system based on a preset driving-response strategy; the initial response system includes a controller to be designed; According to the differential inclusion theory, the variable transformation method is used to process the order of the initial drive system and the initial response system, and the target drive system and the target response system are obtained, and the synchronization error of the target drive system and the target response system is calculated; The controller to be designed is designed based on the synchronization error, and an adaptive pinning controller of a time-delay inertial memristor neural network with a reaction-diffusion term is obtained. The adaptive pinning controller controls the synchronization of the target drive system and the target response system.

[0104] It should be understood that: when the processor 301 executes the time-delay inertia memristor neural network synchronization program in the memory 302, in addition to the above functions, other functions can also be implemented. For details, please refer to the description of the corresponding method embodiment above.

[0105] Furthermore, the embodiment of the present invention does not specifically limit the type of the electronic device 300 mentioned, and the electronic device 300 may be a portable electronic device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, etc. Exemplary embodiments of portable electronic devices include but are not limited to portable electronic devices equipped with IOS, Android, Microsoft or other operating systems. The above-mentioned portable electronic devices may also be other portable electronic devices, such as a laptop computer with a touch-sensitive surface (e.g., a touch panel). It should also be understood that in some other embodiments of the present invention, the electronic device 300 may not be a portable electronic device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0106] Accordingly, an embodiment of the present application also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, the steps or functions in the adaptive containment controller design method provided by the above-mentioned method embodiments can be implemented.

[0107] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0108] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for designing an adaptive pinning controller for realizing synchronization of a time-delay inertial memristor neural network with a reaction-diffusion term, characterized in that: The method comprises: Constructing an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term, and determining an initial response system corresponding to the initial driving system based on a preset driving-response strategy; the initial response system includes a controller to be designed; According to differential inclusion theory, a variable transformation method is used to process the orders of the initial drive system and the initial response system to obtain a target drive system and a target response system, and a synchronization error of the target drive system and the target response system is calculated; The controller to be designed is designed based on the synchronization error to obtain an adaptive control controller of the time-delay inertial memristor neural network with reaction-diffusion terms; the adaptive control controller controls the synchronization of the target drive system and the target response system.

2. The method for designing an adaptive control controller according to claim 1, characterized in that: The initial driving system for constructing a time-delay inertial memristor neural network with a reaction-diffusion term comprises: Based on Kirchhoff’s current law, the i-th subsystem of the memristor neural network circuit is described as: in is the inductor, is the inductor current, and are resistance and capacitance respectively, Represents the activation function and the inductor current The memory resistance between Represents the activation function and the inductor current The memristor between , Corresponding to the transmission delay; let , , we can get For convenience of expression, let , , , , , it can be simplified to: After the reaction-diffusion term is introduced into the memristor neural network circuit, the initial determination system of the time-delay inertial memristor neural network with reaction-diffusion term can be expressed as: in, is the reaction-diffusion coefficient, It is i Neurons in space x and time t The state of and is the memristor synaptic connection weight, which should satisfy the following conditions: in is a normal number, let , .

3. The method for designing an adaptive control controller according to claim 2, characterized in that: Determining an initial response system corresponding to the initial driving system based on a preset driving-response strategy; The initial response system includes a controller to be designed, including: The initial response system corresponding to the initial driving system is determined based on the preset driving-response strategy as follows: in, , is the controller to be designed, is the reaction-diffusion coefficient, It is i Neurons in space x and time t The state when.

4. The method for designing an adaptive pinning controller according to claim 3, characterized in that: The boundary conditions and initial values ​​of the initial response system are as follows: in, is a continuous and bounded function.

5. The method for designing an adaptive pinning controller according to claim 4, characterized in that: Must exist The target drive system is: in, ; Must exist The target response system is: 。 6. The method for designing an adaptive pinning controller according to claim 5, characterized in that: The calculating the synchronization error between the target drive system and the target response system comprises: The synchronization error calculation method is defined as: and , then the synchronization error between the target drive system and the target response system is calculated as: in, 。 7. The method for designing an adaptive pinning controller according to claim 6, characterized in that: The step of designing the controller to be designed based on the synchronization error to obtain the adaptive control controller of the time-delay inertial memristor neural network with reaction-diffusion term includes: For the aforementioned time-delay inertial memristor neural network with reaction-diffusion term The neurons are fixed and the following adaptive control controller is set: in, and is any positive constant, and are the parameters of the adaptive controller.

8. An adaptive control controller design device, characterized in that: include: A system construction module, used to construct an initial driving system of a time-delay inertial memristor neural network with a reaction-diffusion term, and determine an initial response system corresponding to the initial driving system based on a preset driving-response strategy; the initial response system includes a controller to be designed; An error calculation module is used to process the orders of the initial drive system and the initial response system using a variable transformation method according to differential inclusion theory to obtain a target drive system and a target response system, and calculate the synchronization error of the target drive system and the target response system; A controller design module is used to design the controller to be designed based on the synchronization error to obtain an adaptive control controller of the time-delay inertial memristor neural network with a reaction-diffusion term, under the control of the adaptive control controller, the target drive system and the target response system can be synchronized.

9. An electronic device, characterized in that: comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the adaptive containment controller design method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Used to store computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the adaptive containment controller design method as claimed in any one of claims 1 to 7.

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