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| Main Author: | |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.18399 |
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| _version_ | 1866913807618539520 |
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| author | Tahirovic, Adnan |
| author_facet | Tahirovic, Adnan |
| contents | This paper presents a nonlinear control framework for steering networks of coupled oscillators toward desired phase-locked configurations. Inspired by brain dynamics, where structured phase differences support cognitive functions, the focus is on achieving synchronization patterns beyond global coherence. The Kuramoto model, expressed in phase-difference coordinates, is used to describe the system dynamics. The control problem is formulated within the State-Dependent Riccati Equation (SDRE) framework, enabling the design of feedback laws through state-dependent factorisation. The unconstrained control formulation serves as a principled starting point for developing more general approaches that incorporate coupling constraints and actuation limits. Numerical simulations demonstrate that the proposed approach achieves robust phase-locking in both heterogeneous and large-scale oscillator networks, highlighting its potential applications in neuroscience, robotics, and distributed systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_18399 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Optimal Control for Network of Coupled Oscillators Tahirovic, Adnan Systems and Control This paper presents a nonlinear control framework for steering networks of coupled oscillators toward desired phase-locked configurations. Inspired by brain dynamics, where structured phase differences support cognitive functions, the focus is on achieving synchronization patterns beyond global coherence. The Kuramoto model, expressed in phase-difference coordinates, is used to describe the system dynamics. The control problem is formulated within the State-Dependent Riccati Equation (SDRE) framework, enabling the design of feedback laws through state-dependent factorisation. The unconstrained control formulation serves as a principled starting point for developing more general approaches that incorporate coupling constraints and actuation limits. Numerical simulations demonstrate that the proposed approach achieves robust phase-locking in both heterogeneous and large-scale oscillator networks, highlighting its potential applications in neuroscience, robotics, and distributed systems. |
| title | Optimal Control for Network of Coupled Oscillators |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2504.18399 |