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A PSO–Lyapunov Hybrid Stable Adaptive Fuzzy Tracking Control Approach for Vision-Based Robot Navigation

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3 Author(s)
Das Sharma, K. ; Dept. of Electr. Eng., Kalyani Gov. Eng. Coll., Kalyani, India ; Chatterjee, A. ; Rakshit, A.

This paper proposes a novel methodology for autonomous mobile robot navigation utilizing the concept of tracking control. Vision-based path planning and subsequent tracking are performed by utilizing proposed stable adaptive state feedback fuzzy tracking controllers designed using the Lyapunov theory and particle-swarm-optimization (PSO)-based hybrid approaches. The objective is to design two self-adaptive fuzzy controllers, for -direction and -direction movements, optimizing both its structures and free parameters, such that the designed controllers can guarantee desired stability and, simultaneously, can provide satisfactory tracking performance for the vision-based navigation of mobile robot. The design methodology for the controllers simultaneously utilizes the global search capability of PSO and Lyapunov-theory-based local search method, thus providing a high degree of automation. Two different variants of hybrid approaches have been employed in this work. The proposed schemes have been implemented in both simulation and experimentations with a real robot, and the results demonstrate the usefulness of the proposed concept.

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Instrumentation and Measurement, IEEE Transactions on  (Volume:61 ,  Issue: 7 )