College of Big Data and Information Engineering, Guizhou University, Guiyang, 550025, Guizhou, China.
School of Mathematics and Big Data, Guizhou Education University, Guiyang, 550018, Guizhou, China.
Sci Rep. 2023 May 19;13(1):8132. doi: 10.1038/s41598-023-35307-0.
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.
本文研究了一类具有时滞的双切换非线性系统的自适应神经网络规定性能控制问题。通过使用神经网络 (NNs) 的逼近，设计了一个自适应控制器来实现跟踪性能。本文的另一个研究点是跟踪性能约束，它可以解决实际系统中的性能降级问题。因此，通过将规定性能控制 (PPC) 和反推法相结合，研究了一种自适应神经网络输出反馈跟踪方案。通过所设计的控制器和切换规则，闭环系统的所有信号都是有界的，并且跟踪性能满足规定的性能要求。
