1. Optimal Controller Identification for multivariable non-minimum phase systems.
- Author
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Huff, D.D., Campestrini, L., Gonçalves da Silva, G.R., and Bazanella, A.S.
- Subjects
TRANSMISSION zeros ,MONTE Carlo method ,TRANSFER functions ,TRANSFER matrix ,MATRIX functions - Abstract
This work deals with data-driven control for non-minimum phase (NMP) systems, where the goal is to design a controller for a plant whose model is unknown by using a batch of input–output data collected from it. The approach is based on the Model Reference paradigm, where a transfer function matrix – the reference model – is used to specify the desired closed-loop performance. The NMP systems issue in Model Reference approaches is a well-known problem in control literature and it is no different in data-driven methods. This work explains how to adapt the formulation of the Optimal Controller Identification (OCI) method to cope with this class of systems. Considering a convenient parametrization of the reference model and a flexible performance criterion, it is possible to identify the NMP transmission zeros of the plant along with the optimal controller parameters, as it will be shown. Both diagonal and block-triangular reference model structures are treated in detail. Simulation examples show the effectiveness of the proposed approach. • Data-driven control approach to cope with non-minimum phase (NMP) systems. • Knowledge of the NMP transmission zero and/or its direction not required. • Desired closed-loop performance specified by a flexible reference model. • Identification of NMP transmission zeros along with controller parameters. • Monte Carlo simulations show the effectiveness of the method. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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