Assessment of gradient-based iterative learning controllers using a multivariable test facility with varying interaction

Abstract

A multi-variable input, multi-variable output (MIMO) experimental test facility is developed for the evaluation, benchmarking and comparison of iterative learning control (ILC) strategies. The system addresses the distinct lack of experimental studies for the multivariable case and enables controller performance and robustness to be rigorously investigated over a broad range of operating conditions. The electromechanical facility is multi-configurable with up to 3 inputs and permits both exogenous disturbance injection and a variable level of coupling to be applied between input and output pairs. Experimental results confirm its suitability as a benchmarking platform for evaluation and comparison of ILC. The paper concentrates on two popular forms of gradient-type algorithm which both involve the same objective function. The test facility is used to compare robustness and performance over a wide range of operating conditions, and establish how well theoretical convergence rates and input norms match observed results. Relaxing the need to track the reference at all time points is then shown to address the poor performance and low robustness observed at high levels of interaction.

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ORCID for P.L. Lewin: orcid.org/0000-0002-3299-2556

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