加速收敛的点对点ILC

B. Chu, D. Owens, C. Freeman, Yanhong Liu
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引用次数: 1

摘要

提出了一种新的点对点迭代学习控制(ILC)算法,用于高性能的轨迹跟踪应用。基于对点对点ILC设计问题的连续方案表述,导出了两种点对点ILC设计算法:一种算法恢复了点对点ILC算法的范数最优,具有收敛到最小范数(能量)解的理想物理性质,另一种算法(有趣的是)加快了收敛速度,可以显著减少系统配置时间/成本。数值结果验证了算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Point-to-point ILC with accelerated convergence
This paper proposes a novel point-to-point iterative learning control (ILC) algorithm for high performance trajectory tracking applications. Based on a successive project formulation of the point-to-point ILC design problem, two point-to-point ILC design algorithms are derived: one algorithm reCovers the norm optimal point to point ILC algorithm with a desirable physical property of converging to the minimum norm (energy) solution, and the other one (interestingly) accelerates convergence speed which could lead to significant reduction in system configuration time/cost. Numerical results are provided to demonstrate the proposed algorithms' effectiveness.
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