Adaptive modified Stanley controller with fuzzy supervisory system for trajectory tracking of an autonomous armoured vehicle

In developing path tracking controller for autonomous vehicles, a properly tuned controller will work well for a certain range of driving conditions but may need to be re-tuned for others. This study presents the development of an adaptive controller with fuzzy supervisory system for trajectory trac...

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Bibliographic Details
Main Authors: Amer, Noor Hafizah, Hudha, Khisbullah, Zamzuri, Hairi, Aparow, Vimal Rau, Zainal Abidin, Amar Faiz, Abdul Kadir, Zulkiffli, Murrad, Muhamad
Format: Article
Published: Elsevier B. V. 2018
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Summary:In developing path tracking controller for autonomous vehicles, a properly tuned controller will work well for a certain range of driving conditions but may need to be re-tuned for others. This study presents the development of an adaptive controller with fuzzy supervisory system for trajectory tracking control of an autonomous armoured vehicle. A knowledge database is built using Particle Swarm Optimisation which is the mainframe of the Fuzzy supervisory system in adapting to various trajectories and speed. The proposed controller is simulated on a nonlinear vehicle model, and experimental results for the controller are presented to evaluate the proposed controller.