Distributed Model Predictive Control of Spatially Interconnected Systems Using Switched Cost Functions

TL;DR

This paper introduces a distributed model predictive control scheme with switched cost functions for spatially interconnected systems, ensuring stability and convergence while handling communication constraints and safety-related spatial constraints.

Contribution

It presents a novel DMPC approach using switched cost functions and a non-iterative, parallel communication strategy for improved stability and safety in interconnected systems.

Findings

Ensures stability of the origin via a terminal control law.

Establishes convergence conditions for the optimal cost to zero.

Maintains quadratic program structure for practical implementation.

Abstract

This note proposes a distributed model predictive control (DMPC) scheme with switched cost functions for a class of spatially interconnected systems with communication constraints. Non-iterative and parallel communication strategy is considered to ensure that all distributed controllers complete input updates at each single information exchange step. The proposed DMPC scheme switches the optimization index on a switching surface generated by control invariant sets. With the index-switching strategy, stability of the origin is ensured by a terminal control law. Convergence conditions of the optimal cost to zero are established taking into account the causal link between the presumed trajectory and the optimized trajectory of the previous step. The compatibility constraints preserve the quadratic program property that is desired in practical applications. It is also observed that the proposed DMPC scheme has benefits dealing with systems that need to take into account safety-related spatial constraints.