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A simplified adaptive tracking control for nonlinear pure-feedback systems with input delay and full-state constraints
International Journal of Adaptive Control and Signal Processing ( IF 3.1 ) Pub Date : 2021-09-14 , DOI: 10.1002/acs.3335
Nan Wang 1 , Zhumu Fu 1 , Fazhan Tao 1 , Shuzhong Song 1 , Tong Wang 2
Affiliation  

This article investigated the adaptive backstepping tracking control for a class of pure-feedback systems with input delay and full-state constraints. With the help of mean value theorem, the system is transformed into strict-feedback one. By introducing the Pade approximation method, the effect of input delay was compensated. Radial basis function neural networks are utilized to approximate the unknown nonlinear functions. Furthermore, in order to reduce the computational burden by introducing backstepping design technique, dynamic surface control technique was employed. In addition, the number of the adaptive parameters that should be updated online was also reduced. By utilizing the barrier Lyapunov function, the closed-loop nonlinear system is guaranteed to be semi-globally ultimately uniformly bounded. Finally, a numerical simulation example is given to show the effectiveness of the proposed control strategy.

中文翻译:

具有输入延迟和全状态约束的非线性纯反馈系统的简化自适应跟踪控制

本文研究了一类具有输入延迟和全状态约束的纯反馈系统的自适应反步跟踪控制。借助中值定理,系统被转化为严格反馈系统。通过引入Pade逼近方法,补偿了输入延迟的影响。径向基函数神经网络用于逼近未知的非线性函数。此外,为了通过引入反步设计技术来减少计算负担,采用了动态表面控制技术。此外,还减少了应在线更新的自适应参数的数量。通过利用势垒李雅普诺夫函数,可以保证闭环非线性系统是半全局最终一致有界的。最后,
更新日期:2021-09-14
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