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Article type: Research Article
Authors: Bharathi, V.a; * | Sakthivel, K.b
Affiliations: [a] Department of Electronics and Communication Engineering, Kongunadu College of Engineering and Technology, Thottiam, Trichy, Tamilnadu, India | [b] Department of Computer Science and Engineering, K.S. Rangasamy College of Technology, Tiruchengode, Namakkal, Tamilnadu, India
Correspondence: [*] Corresponding author. V. Bharathi, Department of Electronics and Communication Engineering, Kongunadu College of Engineering and Technology, Thottiam, Trichy, Tamilnadu, India. E-mail: [email protected].
Abstract: This paper focuses on a wheeled mobile robot that utilizes the Adaptive Nonlinear Sliding mode control technique for trajectory tracking and obstacle avoidance control. A parallel wheeled differential drive Mobile robot’s trajectory tracking control problem is investigated. For diverse initial conditions, the robot must follow a given course to reach it’s destination. To monitor and identify the obstacles in the path, an obstacle micro-controller is fixed to decide quick crash avoidance and follow the obstacle limit at a predetermined distance. It depends on the robot’s vector connections. An Adaptive Nonlinear Sliding Mode (ANSM) control concept is used for continuous trajectory tracking or object monitoring in the path to avoid it. A Lapunov function control gives stability to each controller. The proposed simulation results demonstrate that the mobile robot can be applied to guarantee its protected development in an obscure obstacle environment. In detail, the proposed control gives another, more straightforward methodology with application esteems for tracking critical thinking in an obscure obstacle environment. Finally, based on these above characteristics, the proposed control strategy’s efficiency, simplicity, and accuracy prove. The steady-state error and mean squared error of the proposed ANSM are 6% and 0.07db, respectively.
Keywords: Adaptive nonlinear sliding, trajectory tracking, collision avoidance, Lyapunov function
DOI: 10.3233/JIFS-213588
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3513-3525, 2022
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