Tao, Xinyue ; Tao, Hongfeng ; Gao, Luyuan ; Paszke, Wojciech (1975- ) ; Rogers, Eric
Tytuł:Predictive Optimal Iterative Learning Control for Nonlinear Systems using the Koopman Operator
Temat i słowa kluczowe:iterative learning control ; nonlinear systems ; Koopman operator ; predictive action
Abstract:This paper develops a predictive optimal iterative learning control design for nonlinear systems based on the Koopman operator. Iterativa learning control applies to systems that make repeated executions, known as trials, over a finite duration, termed the trial length. Once a trial is complete, all information generated is available to update the control signal for the subsequent trial. ; The first step in design is to approximately model the nonlinear system as a high-dimensional linear model using the Koopman operator and extended dynamic mode decomposition, which is applied on each trial. ; Then, an iterative learning control law is designed with predictive action over an infinite duration in the trial-to-trial direction. The robust convergence of the tracking error is analyzed, and a numerical case study highlights the design`s effectiveness.
Opis:artykuł zamieszczony w: "International Journal of Adaptive Control and Signal Processing"
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