For model-free optimal control design, this paper proposes an approach based on optimizing the reference model that is used in direct data-driven controller synthesis. Optimality is defined with respect to suitable cost functions reflecting desired performance and control objectives. We rely on the well-known Virtual Reference Feedback Tuning technique and on a direct control design approach that ensures stability of the resulting closed-loop system. The proposed design method leads to a non-convex optimization problem with a small number of variables that can be easily solved by a global optimizer, such as by particle swarm optimization. The effectiveness of the proposed solution is illustrated in simulation examples.

Optimal direct data-driven control with stability guarantees

Bemporad A.
2020

Abstract

For model-free optimal control design, this paper proposes an approach based on optimizing the reference model that is used in direct data-driven controller synthesis. Optimality is defined with respect to suitable cost functions reflecting desired performance and control objectives. We rely on the well-known Virtual Reference Feedback Tuning technique and on a direct control design approach that ensures stability of the resulting closed-loop system. The proposed design method leads to a non-convex optimization problem with a small number of variables that can be easily solved by a global optimizer, such as by particle swarm optimization. The effectiveness of the proposed solution is illustrated in simulation examples.
Data-driven control
Model-free control design
Optimal control
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11771/17223
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