Abstract

Virtual reference feedback tuning (VRFT) is a data-driven control method that optimises the response of a closed-loop system to reference tracking at the expense of a not optimised response to disturbance rejection. This work presents the application of VRFT to two cascade control structures usually considered in the control literature to improve the overall closed-loop performance for single-input systems. For both structures, the authors derive the optimal and practical filter formulation to cope with the case where the controller to be designed is underparameterised. Also, in the case where the internal controller is at the feedback path, they derive a new approach that uses data from a single experiment and considers a unique reference model. Simulation examples illustrate the importance of using the VRFT filter, along with the performance improvements obtained from both cascade loops in terms of reference tracking and disturbance rejection.

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