反推
控制理论(社会学)
非线性系统
李雅普诺夫函数
自适应控制
人工神经网络
计算机科学
方案(数学)
控制(管理)
理论(学习稳定性)
控制器(灌溉)
Lyapunov稳定性
控制工程
数学
工程类
人工智能
物理
机器学习
数学分析
量子力学
农学
生物
作者
Xiaolong Zheng,Xinghu Yu,Xuebo Yang,Xuebo Yang
出处
期刊:IEEE Transactions on Circuits and Systems Ii-express Briefs
[Institute of Electrical and Electronics Engineers]
日期:2023-08-28
卷期号:71 (2): 747-751
被引量:7
标识
DOI:10.1109/tcsii.2023.3309335
摘要
This paper presents an adaptive neural network (NN) zeta-backstepping control method for a class of uncertain nonlinear systems with unknown nonlinearities. Different form the traditional adaptive NN backstepping control scheme, the proposed adaptive NN zeta-backstepping control approach can regulate the damping ratio of a system by using prescribed parameter selection rules. To guarantee the stability of the closed-loop system, a second-order Lyapunov function method is presented, which proves that the target signal can be boundedly tracked by the system output with adjustable damping ratios. Finally, experimental results on a real quadrotor hover system are given to show the effectiveness of the proposed control scheme.
科研通智能强力驱动
Strongly Powered by AbleSci AI