Simulation-based comparison of robust control and deep reinforcement learning control techniques for active suspension systems

Modern vehicular systems rely heavily on suspension performance for ride comfort, handling stability, and safety. Conventional passive suspensions, while common, cannot adapt to changing road conditions. Active suspension systems overcome this limitation by using actuators and control algorithms to...

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Auteurs principaux:	Arya Hariharan, K V S Rajeswara Rao, K K Hruthik, Arya S Patil, Vamshi Krishna, Shravni Kinange, Anamika Yadav
Format:	Artigo
Langue:	Inglês
Publié:	Taylor & Francis Group 2025-12-01
Collection:	Systems Science & Control Engineering
Sujets:	Active suspension system robust controllers H-infinity re-inforcement learning simulink
Accès en ligne:	https://www.tandfonline.com/doi/10.1080/21642583.2025.2600770
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