Adaptive iterative learning control for nonlinearly parameterized systems with unknown time-varying delays
Adaptive iterative learning control for nonlinearly parameterized systems with unknown time-varying delays
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DOI：
10.1007/s12555-010-0201-0
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发表时间：
2010-04
期刊：
影响因子：
--
通讯作者：
Weisheng Chen;Li Zhang
中科院分区：
文献类型：
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作者：
Weisheng Chen;Li Zhang
首先，针对一类具有两个未知时变参数和一个未知时变时滞的非线性参数化系统，提出了一种自适应迭代学习控制策略。所提出的控制律包括一个PID型反馈项在时域和一个自适应学习项用于估计未知的时变向量在迭代域。通过构造Lyapunov-Krasovskii型复合能量函数，证明了闭环系统的稳定性和跟踪误差的收敛性。然后，设计思想进一步扩展到更广泛的一类系统的混合参数，其中未知的时不变向量估计的PI型学习法在时域。针对时延混沌系统的仿真结果证实了所提出的控制方案的有效性。
First of all, an adaptive iterative learning control strategy is developed for a class of nonlinearly parameterized systems with two unknown time-varying parameters and one unknown time-varying delay. The proposed control law includes a PID-type feedback term in time domain and an adaptive learning term used to estimate the unknown time-varying vector in iteration domain. By constructing a Lyapunov-Krasovskii-like composite energy function, we prove the stability of the closed-loop system and the convergence of the tracking error. Then, the design idea is further extended to a broader class of systems with mixed parameters in which the unknown time-invariant vector is estimated by a PI-type learning law in time domain. The simulation results, for a time-delay chaotic system, confirm the effectiveness of the proposed control scheme.