Repetitive process based stochastic iterative learning control design for linear dynamics

摘要

A new set of iterative learning control laws for systems described by stochastic discrete linear dynamics is developed using the passivity based stability theory for discrete nonlinear repetitive processes. This setting allows the application of a nonlinear control law to discrete linear systems. The advantages of such a control law in tuning the performance of the design is demonstrated by a case study that also compares the performance of one member of this class of new laws against an existing design. (C) 2020 Elsevier B.V. All rights reserved.