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A Scheduled Time Projection Synchronization Method for Delayed Memristive Neural Networks with Resilience to Unknown Perturbations

A predetermined time and neural network technology, applied in the direction of instruments, adaptive control, control/regulation systems, etc., can solve problems such as difficult to find the direct relationship between the system gain and the upper limit of the convergence time, interference, etc., to achieve accurate prediction of projection synchronization time, Improve stability and the effect of a wide range of application scenarios

Active Publication Date: 2022-01-04
FUZHOU UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When applying constant-time stability to a control or observation task, it is difficult to find a direct relationship between the system gain and the upper bound on the convergence time
Moreover, in practical applications, it is inevitable to be subject to external unknown interference

Method used

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  • A Scheduled Time Projection Synchronization Method for Delayed Memristive Neural Networks with Resilience to Unknown Perturbations
  • A Scheduled Time Projection Synchronization Method for Delayed Memristive Neural Networks with Resilience to Unknown Perturbations
  • A Scheduled Time Projection Synchronization Method for Delayed Memristive Neural Networks with Resilience to Unknown Perturbations

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Experimental program
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Effect test

specific Embodiment 1

[0148] The state equation of the driving system is:

[0149]

[0150] Among them, the driving system is a 2-dimensional chaotic system, x i The initial state of (t) is set to [3,-2] T . figure 2 Expressed as the chaotic behavior of the system.

[0151] The state equation of the response system is:

[0152]

[0153] Among them, the response system is a 2-dimensional chaotic system, y i The initial state of (t) is set to [-1,1.5] T . Here are the settings for some known parameters:

[0154]

[0155]

[0156]

[0157]

[0158] The projection error of the drive-response system is set as:

[0159] e i (t)=y i (t)-x i (t); (23)

[0160] image 3 Expressed as the response curve of the projected synchronization error in the absence of active controller input.

[0161] (1-1) Assuming that there is no unknown disturbance outside, then there is no need to use the disturbance observer to compensate the error effect caused by the unknown disturbance. At thi...

specific Embodiment 2

[0177] drive systemx i The initial state of (t) is set to [3,-0.5] T , the response system y i The initial state of (t) is set to [-2,4] T . Here are the settings for some known parameters:

[0178]

[0179]

[0180] ω(t)=sint, τ(t)=1, q=2,b 1 =0.2,b2 =0.1,c 1 = 1,c 2 =1.5, w(0)=-0.5,

[0181]

[0182] (2-1) Setting T c1 =T c2 =0.5, according to the satisfaction condition of the gain control parameter in step 5, wherein the gain control parameter is set to k 1 = 3,k 2 = 1,w 1 =11,w 2 =9, h 11 = 2.2, h 12 = 1.4, h 21 = 1.4, h 22 = 2.5. The control parameters are shown in formula (29), and the simulation experiment is carried out. Figure 6 (a) shows the synchronous error response curve projected at a predetermined time under the input of active controllers (14) and (15). exist Figure 6 In (a), the system converges to zero at 0.3759s.

[0183] (2-2) Setting T c1 =T c2 = 1.0, according to the satisfaction condition of the gain control parameter ...

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Abstract

The present invention relates to a predetermined time projection synchronization method of a delayed memristive neural network with resistance to unknown disturbances, comprising the following steps: Step S1: Establish a drive system and a response system based on the delayed memristive neural network; Step S2: Establish according to step S1 The drive system and response system of the system, establish a predetermined time projection synchronization error system; Step S3: Design the disturbance observer to estimate the external unknown disturbance, and compensate the error effect caused by the unknown disturbance on the system synchronization; Step S4: According to different situations, design Different active controllers for balance control of predetermined time projection synchronous error systems. The invention can realize the predetermined time projection synchronization of the time-delayed memristive neural network with anti-unknown disturbance.

Description

technical field [0001] The invention relates to the technical field of automatic control, in particular to a predetermined time projection synchronization method of a delay memristive neural network capable of resisting unknown disturbances. Background technique [0002] Finite-time stability refers to the stability of the state trajectory relative to a certain time interval after the system is subjected to an initial disturbance. The stable establishment time of the system with finite-time stability is closely related to the initial state, but in some practical systems, such as robot operating systems, vehicle monitoring systems, power systems, and spacecraft attitude dynamic systems, it is difficult to obtain the initial state of the system. state. The lack of these initial information directly leads to the inability to estimate the stable establishment time of the system. Therefore, in 2012, Polyakov proposed a special kind of finite-time stability, which he called fixe...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 林立雄吴培鑫何炳蔚张立伟陈彦杰
Owner FUZHOU UNIV
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