Algorithm for Optimal Mode Scheduling in Switched Systems

TL;DR

This paper introduces a new algorithm for optimal mode scheduling in switched systems that directly optimizes the schedule, avoiding the inefficiencies of previous methods that separately optimize switching times and sequences.

Contribution

It proposes a novel schedule space optimization algorithm based on Gateaux derivatives, improving computational efficiency and convergence in mode scheduling problems.

Findings

The algorithm converges to local minima.

It demonstrates fast convergence in simulations.

It avoids complex timing optimization steps.

Abstract

This paper considers the problem of computing the schedule of modes in a switched dynamical system, that minimizes a cost functional defined on the trajectory of the system's continuous state variable. A recent approach to such optimal control problems consists of algorithms that alternate between computing the optimal switching times between modes in a given sequence, and updating the mode-sequence by inserting to it a finite number of new modes. These algorithms have an inherent inefficiency due to their sparse update of the mode-sequences, while spending most of the computing times on optimizing with respect to the switching times for a given mode-sequence. This paper proposes an algorithm that operates directly in the schedule space without resorting to the timing optimization problem. It is based on the Armijo step size along certain Gateaux derivatives of the performance functional, thereby avoiding some of the computational difficulties associated with discrete scheduling parameters. Its convergence to local minima as well as its rate of convergence are proved, and a simulation example on a nonlinear system exhibits quite a fast convergence.