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首页> 外文期刊>International Journal of Adaptive Control and Signal Processing >Robust adaptive iterative learning control for discrete-time nonlinear systems with both parametric and nonparametric uncertainties
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Robust adaptive iterative learning control for discrete-time nonlinear systems with both parametric and nonparametric uncertainties

机译：具有参数和非参数不确定性的离散时间非线性系统的鲁棒自适应迭代学习控制

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摘要

A new robust adaptive iterative learning control approach is proposed for discrete-time nonlinear systems with both parametric and nonparametric uncertainties. By virtue of a well-designed dead-zone function, the learning of the parametric and nonparametric uncertainties can be performed concurrently. Rigorous Lyapunov function-based analysis ensures that the effect of system uncertainties can be fully compensated, and the tracking error will converge to zero asymptotically in the iteration domain, even under random initial conditions and iteration-varying reference trajectories. The efficacy of the proposed controller is demonstrated by simulating a single-link robot manipulator with unknown frictions. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译：针对具有参数和非参数不确定性的离散时间非线性系统，提出了一种新的鲁棒自适应迭代学习控制方法。通过设计良好的死区功能，可以同时进行参数和非参数不确定性的学习。基于严格的Lyapunov函数的分析可确保系统不确定性的影响得到充分补偿，并且即使在随机初始条件和迭代变化的参考轨迹下，跟踪误差也会在迭代域中渐近收敛至零。通过模拟摩擦未知的单连杆机器人操纵器，证明了所提出控制器的功效。版权所有（c）2015 John Wiley＆Sons，Ltd.

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