Enhanced model-free adaptive iterative learning control with load disturbance and data dropout 期刊名称： International Journal of Systems Science
作者： Changchun Hua,Yunfei Qiu,Xinping Guan
年份： 2020年
期号： 第4期
关键词： Model-free adaptive control;iterative learning control;data
dropout;time-varying parameters
摘要：In this paper, an enhanced model-free adaptive iterative learning control (EMFAILC) method is proposed, which is applied for a class of nonlinear discrete-time systems with load disturbance and random data dropout. This method is a data-driven control strategy and only the I/O data are required for the controller design. Data are lost at every time instance and iteration instance independently, which allows successive data dropout both in time and iterative axes. By compensating the missing dat
a, the proposed EMFAILC algorithm can track the desired time-varying trajectory. The convergence and effectiveness of the proposed approach are verified by both the rigorous mathematical analysis and the simulation results.
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