Adaptive ILC for a Discrete-time Nonlinear System with both Parametric and Non-parametric Uncertainties
In this paper, a discrete adaptive ILC is presented for a time-varying nonlinear system with both parametric and nonparametric uncertainties. A novel estimation of parametric and nonparametric uncertainties is constructed just using the past input and output data, and the uncertainties are completely compensated such that the output tracking error is only affected by external disturbance. As a main contribution of this paper, all the discussions are based on the random initial condition and the iteration-varying target trajectories. When the nonlinear function is generalized Lipschitz continuous and the external disturbance is iteration-varying within a bound, the robust property of the proposed adaptive ILC is guaranteed. And when the nonlinear function is standard Lipschitz continuous and the system is free of external disturbance (or the external disturbance is strictly repeatable), the proposed scheme guarantees an almost perfect tracking over the finite time interval.
Adaptive control Iterative learning control Parametric uncertainty Nonparametric uncertainty Random initial conditions Iteration-varying target trajectories
Ronghu Chi Zhongsheng Hou
Institute of Autonomous Navigation & Intelligent Control, School of Automation & Electrical Engineer Advanced Control Systems Lab, School of Electronics and Information Engineering,Beijing Jiaotong Uni
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
1722-1727
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）