反推
控制理论(社会学)
李雅普诺夫函数
计算机科学
滤波器(信号处理)
非线性系统
理论(学习稳定性)
可靠性(半导体)
Lyapunov稳定性
非参数统计
人工神经网络
模糊逻辑
自适应控制
控制工程
控制(管理)
工程类
数学
人工智能
机器学习
功率(物理)
物理
量子力学
计算机视觉
统计
作者
Xiaolong Zheng,Xinghu Yu,Xuebo Yang,Juan J. Rodrıguez-Andina
出处
期刊:IEEE transactions on cybernetics
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:: 1-13
被引量:6
标识
DOI:10.1109/tcyb.2023.3323664
摘要
In this article, a practical finite-time command-filtered adaptive backstepping (PFTCFAB) control method is presented for a class of uncertain nonlinear systems with nonparametric unknown nonlinearities and external disturbances. Unlike PFTCFAB control techniques that use neural networks (NNs) or fuzzy-logic systems (FLSs) to deal with system uncertainties, the proposed method is capable of handling such uncertainties without the need for NNs or FLSs, thus reducing complexity and increasing reliability. In the proposed approach, novel function adaptive laws are designed to directly estimate unknown nonparametric nonlinearities and external disturbances by means of command filter techniques, and a type of practical finite-time command filters is proposed to obtain such laws. Moreover, the PFTCFAB controllers and finite-time command filters are designed with practical finite-time Lyapunov stability, which ensures finite-time stability of system tracking and filter estimation errors. Experimental results with a quadrotor hover system are presented and discussed to demonstrate the advantages and effectiveness of the proposed control strategy.
科研通智能强力驱动
Strongly Powered by AbleSci AI