An Overview of Sensitivity-Based Distributed Optimization and Model Predictive Control
Year: 2025
Type: preprint
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 watertank system.
Source: arXiv (Cornell University)
Authors: von Esch, Maximilian Pierer, Völz, Andreas, Graichen, Knut
Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7114767330
Cites:
Cited by:
Related to: