Adaptive Dynamic Surface Integral Sliding Mode Fault-Tolerant Control for Multimachine Excitation Systems with SVC

Author:

Zhu Guoqiang12ORCID,Ji Shuang12,Li Zhiwei12ORCID,Zhang Yilong12

Affiliation:

1. School of Automation Engineering, Northeast Electric Power University, Jilin, China

2. Jilin Province International Research Center of Precision Drive and Intelligent Control, Jilin, China

Abstract

In this paper, an adaptive dynamic surface integral sliding mode fault-tolerant controller is designed for the multimachine power system with static var compensator (SVC) to overcome the problem of actuator failure. The main features of the proposed method are as follows: (1) By combining the dynamic surface control (DSC) method with integral sliding mode (ISM), the tracking errors of the system converge to the neighborhood of zero within a finite time, and the convergence speed, tracking accuracy, and anti-interference ability of the system are also significantly improved. (2) By introducing the failure factors, an adaptive fault-tolerant controller is designed to ensure the stability of the entire system after partial failure of the actuator. (3) By estimating the norm of the ideal weight vector of the radial basis function neural networks (RBFNNs), the computational burden of the controller is reduced. Finally, the simulation results show the effectiveness of the proposed control scheme.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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1. Fixed‐time fault‐tolerant control for power system with multiple actuator constraints;Asian Journal of Control;2024-07-24

2. Finite-time stabilization-based Adaptive Fuzzy Control: Applied to the design of the excitation controller for synchronous generator;2022 2nd International Conference on Electrical Engineering and Mechatronics Technology (ICEEMT);2022-07-01

3. Adaptive Quantization Control for Multi-machine Power System with SVC and Unknown Disturbance;2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms (EEBDA);2022-02-25

4. Fuzzy Adaptive Finite Time Command Filter Backstepping Control of Power System;International Journal of Control, Automation and Systems;2021-09-02

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