Adaptive neural network prescribed performance control for dual switching nonlinear time-delay system

被引：0
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作者：
Qianqian Mu
Fei Long
Bin Li
机构：
[1] Guizhou University,College of Big Data and Information Engineering
[2] Guizhou Education University,School of Mathematics and Big Data
[3] Guizhou Institute of Technology,School of Artificial Intelligence and Electrical Engineering
[4] Guizhou Key Laboratory of Artificial Intelligence and Intelligent Control,undefined
[5] China Tower Corporation Limited Guizhou Provincial Branch,undefined
来源：
Scientific Reports | / 13卷
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摘要：
This paper investigates the adaptive neural network prescribed performance control problem for a class of dual switching nonlinear systems with time-delay. By using the approximation of neural networks (NNs), an adaptive controller is designed to achieve tracking performance. Another research point of this paper is tracking performance constraints which can solve the performance degradation in practical systems. Therefore, an adaptive NNs output feedback tracking scheme is studied by combining the prescribed performance control (PPC) and backstepping method. With the designed controller and the switching rule, all signals of the closed-loop system are bounded, and the tracking performance satisfies the prescribed performance.
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