Sequential Linear Quadratic Optimal Control for Nonlinear Switched Systems
For researchers in optimal control and robotics, this work offers a computationally efficient alternative to solving two-point boundary value problems for switched systems, though it is an incremental improvement over existing approaches.
This paper introduces a Sequential Linear Quadratic method for optimal control of nonlinear switched systems with fixed mode sequence but unknown switching times, achieving higher numerical efficiency and scalability to high-dimensional problems compared to baseline methods. The method is demonstrated on three examples, including quadruped robot locomotion.
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.