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Configuration-Constrained Tube MPC for Tracking

2024-05-06Code Available0· sign in to hype

Filippo Badalamenti, Sampath Kumar Mulagaleti, Alberto Bemporad, Boris Houska, Mario Eduardo Villanueva

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Abstract

This paper proposes a novel tube-based Model Predictive Control (MPC) framework for tracking varying setpoint references with linear systems subject to additive and multiplicative uncertainties. The MPC controllers designed using this framework exhibit recursively feasible for changing references, and robust asymptotic stability for piecewise constant references. The framework leverages configuration-constrained polytopes to parameterize the tubes, offering flexibility to optimize their shape. The efficacy of the approach is demonstrated through two numerical examples. The first example illustrates the theoretical results, and the second uses the framework to design a lane-change controller for an autonomous vehicle.

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