Multiobjective strict dissipativity via a weighted sum approach

TL;DR

This paper explores how to ensure strict dissipativity in multiobjective nonlinear MPC using a weighted sum approach, providing conditions for stability and performance in both linear and nonlinear cases.

Contribution

It establishes conditions under which convex combinations of strictly dissipative costs remain strictly dissipative, aiding the design of stable multiobjective MPC algorithms.

Findings

Conditions for strict dissipativity in linear systems

Necessary and sufficient conditions for nonlinear systems

Numerical examples illustrating theoretical results

Abstract

We consider nonlinear model predictive control (MPC) with multiple competing cost functions. This leads to the formulation of multiobjective optimal control problems (MO OCPs). Since the design of MPC algorithms for directly solving multiobjective problems is rather complicated, particularly if terminal conditions shall be avoided, we use an indirect approach via a weighted sum formulation for solving these MO OCPs. This way, for each set of weights we obtain an optimal control problem with a single objective. In economic MPC it is known that strict dissipativity is the key assumption for concluding performance and stability results. We thus investigate under which conditions a convex combination of strictly dissipative stage costs is strictly dissipative again. We first give conditions for problems with linear dynamics and then move on to consider fully nonlinear optimal control problems. We derive both necessary and sufficient conditions on the individual cost functions and on the weights to conclude strict dissipativity and illustrate our findings with numerical examples.