An overview of sensitivity-based distributed optimization and model predictive control

Pierer von Esch M, Völz A, Graichen K (2026)

Publication Type: Journal article

Publication year: 2026

Journal

At-Automatisierungstechnik Oldenbourg Verlag

Book Volume: 74

Pages Range: 182-196

Journal Issue: 3

DOI: 10.1515/auto-2025-0105

Abstract

This paper presents a concise overview of sensitivity-based methods for solving large-scale optimization problems in distributed fashion. The approach relies on sensitivities and primal decomposition to achieve coordination between the subsystems while requiring only local computations with neighbor-to-neighbor communication. We give a brief historical synopsis of its development and apply it to both static and dynamic optimization problems. Furthermore, a real-time capable distributed model predictive controller is proposed which is experimentally validated on a coupled water tank system.

Authors with CRIS profile

Maximilian Pierer von Esch Chair of Automatic Control (LRT/AC) Andreas Völz Chair of Automatic Control (LRT/AC) Knut Graichen Chair of Automatic Control (LRT/AC)

How to cite

APA:

Pierer von Esch, M., Völz, A., & Graichen, K. (2026). An overview of sensitivity-based distributed optimization and model predictive control. At-Automatisierungstechnik, 74(3), 182-196. https://doi.org/10.1515/auto-2025-0105

MLA:

Pierer von Esch, Maximilian, Andreas Völz, and Knut Graichen. "An overview of sensitivity-based distributed optimization and model predictive control." At-Automatisierungstechnik 74.3 (2026): 182-196.

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