Data-based Receding Horizon Control of Linear Network Systems
| Autor: | Ahmed Allibhoy, Jorge E. Cortes |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Mathematical optimization Control and Optimization Linear programming Computer science 020209 energy Systems and Control (eess.SY) 02 engineering and technology Linear-quadratic regulator Electrical Engineering and Systems Science - Systems and Control 020901 industrial engineering & automation Control theory FOS: Mathematics FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering Computer Science - Multiagent Systems Representation (mathematics) Mathematics - Optimization and Control Horizon Linear system Model predictive control Optimization and Control (math.OC) Control and Systems Engineering Trajectory Multiagent Systems (cs.MA) |
| Popis: | We propose a distributed data-based predictive control scheme to stabilize a network system described by linear dynamics. Agents cooperate to predict the future system evolution without knowledge of the dynamics, relying instead on learning a data-based representation from a single sample trajectory. We employ this representation to reformulate the finite-horizon Linear Quadratic Regulator problem as a network optimization with separable objective functions and locally expressible constraints. We show that the controller resulting from approximately solving this problem using a distributed optimization algorithm in a receding horizon manner is stabilizing. We validate our results through numerical simulations. |
| Databáze: | OpenAIRE |
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