Journal Article

Quantized neural adaptive finite-time preassigned performance control for interconnected nonlinear systems

Song, Shuai, Sun, Peng, Stojanovic, Vladimir, Song, Xiaona

2023

Overview

In this article, the issue of neural adaptive decentralized finite-time prescribed performance (FTPP) control is investigated for interconnected nonlinear time-delay systems. First, to bypass the potential singularity difficulties, the hyperbolic tangent function and the radial basis function neural networks are integrated to handle the unknown nonlinear items. Then, an adaptive FTPP control strategy is developed, where an improved fractional-order filter is applied to tackle the tremendous “amount of calculation” and eliminate the filter error simultaneously. Furthermore, by considering the impact of bandwidth limitation, an adaptive self-triggered control law is designed, in which the next trigger instant is determined through the current information. Ultimately, it can be demonstrated that the proposed control scheme not only guarantees that all states of the closed-loop system are semi-globally uniformly ultimately bounded, but also that the system output is confined to a small area in finite time. Two simulation examples are carried out to verify the effectiveness and superiority of the proposed method.

• Publisher: Springer London,Springer Nature B.V
• Subject: Adaptive control / Artificial Intelligence / Bandwidths / Closed loop systems / Closed loops / Communication / Computational Biology/Bioinformatics / Computational Science and Engineering / Computer Science / Control theory / Data Mining and Knowledge Discovery / Feedback control / Hyperbolic functions / Image Processing and Computer Vision / Investigations / Neural networks / Nonlinear control / Nonlinear systems / Original Article / Probability and Statistics in Computer Science / Radial basis function / Time delay systems