Algorithms for optimal control of hybrid systems with sliding motion

TL;DR

This paper introduces two algorithms for optimal control of hybrid systems, one handling sliding modes with accurate surface tracking and the other for systems without sliding motion, both satisfying the weak maximum principle.

Contribution

It presents novel algorithms for hybrid systems with and without sliding modes, including accurate sliding surface tracking and adjoint-based gradient evaluation.

Findings

Algorithms satisfy the weak maximum principle at accumulation points.

The first algorithm accurately tracks sliding motion using index 2 differential-algebraic equations.

The second algorithm handles measurable control functions in non-sliding hybrid systems.

Abstract

This paper concerns two algorithms for solving optimal control problems with hybrid systems. The first algorithm aims at hybrid systems exhibiting sliding modes. The first algorithm has several features which distinguishes it from the other algorithms for problems described by hybrid systems. First of all, it can cope with hybrid systems which exhibit sliding modes. Secondly, the systems motion on the switching surface is described by index 2 differential--algebraic equations and that guarantees accurate tracking of the sliding motion surface. Thirdly, the gradients of the problems functionals are evaluated with the help of adjoint equations. The adjoint equations presented in the paper take into account sliding motion and exhibit jump conditions at transition times. We state optimality conditions in the form of the weak maximum principle for optimal control problems with hybrid systems exhibiting sliding modes and with piecewise differentiable controls. The second algorithm is for optimal control problems with hybrid systems which do not exhibit sliding motion. In the case of this algorithm we assume that control functions are measurable functions. For each algorithm, we show that every accumulation point of the sequence generated by the algorithm satisfies the weak maximum principle.