Recursive Feasibility without Terminal Constraints via Parent-Child MPC Architecture
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916848899981312 |
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| author | Surma, Filip Jamshidnejad, Anahita |
| author_facet | Surma, Filip Jamshidnejad, Anahita |
| contents | This paper proposes a novel hierarchical model predictive control (MPC) framework, called the Parent-Child MPC architecture, to steer nonlinear systems under uncertainty towards a target set, balancing computational complexity and guaranteeing recursive feasibility and stability without relying on conservative terminal constraints in online decision-making. By coupling a small-horizon Child MPC layer with one or more large-horizon Parent MPC layers, the architecture ensures recursive feasibility and stability through adjustable stage-wise constraints derived from tube-based control. As is demonstrated in our case studies, compared to traditional MPC methods, the proposed Parent-Child MPC architecture enhances performance and computational efficiency, reduces conservativeness, and enables scalable planning for certain nonlinear systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_10166 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Recursive Feasibility without Terminal Constraints via Parent-Child MPC Architecture Surma, Filip Jamshidnejad, Anahita Optimization and Control This paper proposes a novel hierarchical model predictive control (MPC) framework, called the Parent-Child MPC architecture, to steer nonlinear systems under uncertainty towards a target set, balancing computational complexity and guaranteeing recursive feasibility and stability without relying on conservative terminal constraints in online decision-making. By coupling a small-horizon Child MPC layer with one or more large-horizon Parent MPC layers, the architecture ensures recursive feasibility and stability through adjustable stage-wise constraints derived from tube-based control. As is demonstrated in our case studies, compared to traditional MPC methods, the proposed Parent-Child MPC architecture enhances performance and computational efficiency, reduces conservativeness, and enables scalable planning for certain nonlinear systems. |
| title | Recursive Feasibility without Terminal Constraints via Parent-Child MPC Architecture |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2507.10166 |