Iterative Learning Controller with Causal Learning Function for a Class of Linear Mon-minimum Phase Systems

E. Kurniawan, Dimas W. Ramadhan, Elvan Yuniarti, H. Septanto
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Abstract

This paper presents a design strategy of an iterative learning controller (ILC) with a causal filter-based learning function for a class of non-minimum phase systems. The learning function is part of the ILC used to stabilize the ILC closed-loop system and determine the convergence rate of the system output. In this paper, we present the design of ILC’s learning function in the form of a stable and causal filter. An ILC’s stability condition in the frequency domain is employed to formulate the minimization problem. Then, an optimization tool is used to solve the minimization problem. Simulation on non-minimum phase plant with a relative degree one demonstrates the effectiveness of the proposed design.
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一类线性非最小相位系统的带因果学习函数的迭代学习控制器
针对一类非最小相位系统,提出了一种基于因果滤波器学习函数的迭代学习控制器的设计策略。学习函数是ILC的一部分,用于稳定ILC闭环系统并确定系统输出的收敛速度。在本文中,我们以稳定的因果滤波器的形式设计了ILC的学习函数。利用线性控制在频域上的稳定性条件来表述最小化问题。然后,利用优化工具求解最小化问题。对相对度数为1的非最小相位电厂进行了仿真,验证了该设计的有效性。
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