Consistent Approximations for the Optimal Control of Constrained Switched Systems

TL;DR

This paper introduces a convergent algorithm for optimal control of constrained nonlinear switched systems, combining relaxation, traditional control, and projection techniques, validated through simulations.

Contribution

It proposes a novel algorithm that guarantees convergence to local minimizers for constrained switched systems by extending the Chattering Lemma.

Findings

Algorithm converges to local minimizers

Extension of Chattering Lemma for discrete inputs

Validated through four simulation experiments

Abstract

Though switched dynamical systems have shown great utility in modeling a variety of physical phenomena, the construction of an optimal control of such systems has proven difficult since it demands some type of optimal mode scheduling. In this paper, we devise an algorithm for the computation of an optimal control of constrained nonlinear switched dynamical systems. The control parameter for such systems include a continuous-valued input and discrete-valued input, where the latter corresponds to the mode of the switched system that is active at a particular instance in time. Our approach, which we prove converges to local minimizers of the constrained optimal control problem, first relaxes the discrete-valued input, then performs traditional optimal control, and then projects the constructed relaxed discrete-valued input back to a pure discrete-valued input by employing an extension to the classical Chattering Lemma that we prove. We extend this algorithm by formulating a computationally implementable algorithm which works by discretizing the time interval over which the switched dynamical system is defined. Importantly, we prove that this implementable algorithm constructs a sequence of points by recursive application that converge to the local minimizers of the original constrained optimal control problem. Four simulation experiments are included to validate the theoretical developments.