Position and Angular control using Fuzzy Tuned PID Controller for Mobile Robot Path Tracking

Analyzing unstructured gain data has been a growing interest among researchers, resulting in valuable information in many fields such as path planning, and others. Furthermore, the Fuzzy Logic Controller (FLC) has simplified the managing unstructured gain data on the simulator such as Gazebo. FLC and PID controller can be used as a solution to recognize path planning entities in the collision-free environment based on heuristic solution. However, without proper selection of unstructured gain data of PID such as proportional, derivative and integral, the performance maybe compromised. In this paper, PID and FLC is designed in series for position and angular control to overcome the multi-representation and the problem of uncertainty contexts. It will be able to recognize the Fuzzy Tuned PID controller gains with limited supervised data accurately and take fast and precise intervention. The efficient and precise algorithms help the mobile robot to take immediate and appropriate intervention, thus helping to preserve the path planning. Finally, in line with the FLC and PID controller, this study will fulfill two elements in the Control Signal Distance (CSD) and Control Signal Angle (CSA) to produce precise and optimal mobile robot path tracking.