Sequential Linear Quadratic Optimal Control for Nonlinear Switched Systems

TL;DR

This paper presents a novel Sequential Linear Quadratic method for efficiently solving optimal control problems in nonlinear switched systems, especially when switching times are unknown, demonstrating improved scalability and performance.

Contribution

It introduces a Sequential Linear Quadratic approach for optimal control of nonlinear switched systems, replacing boundary value problem solutions with a more efficient method.

Findings

The method is numerically more efficient than traditional boundary value approaches.

It scales well to high-dimensional problems.

Successfully applied to quadruped robot locomotion control.

Abstract

In this contribution, we introduce an efficient method for solving the optimal control problem for an unconstrained nonlinear switched system with an arbitrary cost function. We assume that the sequence of the switching modes are given but the switching time in between consecutive modes remains to be optimized. The proposed method uses a two-stage approach as introduced by Xu and Antsaklis (2004) where the original optimal control problem is transcribed into an equivalent problem parametrized by the switching times and the optimal control policy is obtained based on the solution of a two-point boundary value differential equation. The main contribution of this paper is to use a Sequential Linear Quadratic approach to synthesize the optimal controller instead of solving a boundary value problem. The proposed method is numerically more efficient and scales very well to the high dimensional problems. In order to evaluate its performance, we use two numerical examples as benchmarks to compare against the baseline algorithm. In the third numerical example, we apply the proposed algorithm to the Center of Mass control problem in a quadruped robot locomotion task.