Novel Multi-objective Switched Model Predictive Control with Feasibility and Stability Guarantees

TL;DR

This paper introduces two innovative multi-objective switched Model Predictive Control frameworks that ensure feasibility and stability, enabling complex control objectives with guaranteed performance in switching systems.

Contribution

The paper presents a nominal and a robust framework for multi-objective switched MPC that guarantees recursive feasibility and stability, advancing control methods for complex systems.

Findings

Frameworks ensure recursive feasibility under arbitrary switching.

Nominal framework guarantees asymptotic stability.

Robust framework guarantees Input-to-State stability.

Abstract

As the relevance of control systems capable of dealing with multiple objectives rises (e.g. being economic while maintaining a certain performance), multi-objective Switched Model Predictive Control combines all the advantages of Model Predictive Control while dealing with multiple objectives. We propose two novel frameworks, a nominal and a robust framework to guarantee recursive feasibility of each Model Predictive Controller under arbitrary switching and assure asymptotic stability of the closed-loop system applying the nominal framework and Input-to-State stability using the robust framework. The presented frameworks employ methods from switched systems, enabling the utilization of a supervisor control instance which allows for complex objectives and multi-objective control. Our numerical example confirms the superior performance of our proposed frameworks compared to a standard Model Predictive Control approach.