Distributed model predictive control without terminal cost under inexact distributed optimization
Fuente:
arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917539178610688 |
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| author | Liu, Xiaoyu Dimarogonas, Dimos V. Liu, Changxin Dabiri, Azita De Schutter, Bart |
| author_facet | Liu, Xiaoyu Dimarogonas, Dimos V. Liu, Changxin Dabiri, Azita De Schutter, Bart |
| contents | This paper presents a novel distributed model predictive control (MPC) formulation without terminal cost and a corresponding distributed synthesis approach for distributed linear discrete-time systems with coupled constraints. The proposed control scheme introduces an explicit stability condition as an additional constraint based on relaxed dynamic programming. As a result, contrary to other related approaches, system stability with the developed controller does not rely on designing a terminal cost. A distributed synthesis approach is then introduced to handle the stability constraint locally within each local agent. To solve the underlying optimization problem for distributed MPC, a violation-free distributed optimization approach is developed, using constraint tightening to ensure feasibility throughout iterations. A numerical example demonstrates that the proposed distributed MPC approach ensures closed-loop stability for each feasible control sequence, with each agent computing its control input in parallel. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_15768 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Distributed model predictive control without terminal cost under inexact distributed optimization Liu, Xiaoyu Dimarogonas, Dimos V. Liu, Changxin Dabiri, Azita De Schutter, Bart Systems and Control This paper presents a novel distributed model predictive control (MPC) formulation without terminal cost and a corresponding distributed synthesis approach for distributed linear discrete-time systems with coupled constraints. The proposed control scheme introduces an explicit stability condition as an additional constraint based on relaxed dynamic programming. As a result, contrary to other related approaches, system stability with the developed controller does not rely on designing a terminal cost. A distributed synthesis approach is then introduced to handle the stability constraint locally within each local agent. To solve the underlying optimization problem for distributed MPC, a violation-free distributed optimization approach is developed, using constraint tightening to ensure feasibility throughout iterations. A numerical example demonstrates that the proposed distributed MPC approach ensures closed-loop stability for each feasible control sequence, with each agent computing its control input in parallel. |
| title | Distributed model predictive control without terminal cost under inexact distributed optimization |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2504.15768 |