TELKOMNIKA Telecommunication, Computing, Electronics and Control
An adaptive neural control methodology design for dynamics mobile robot

TELKOMNIKA Telecommunication, Computing, Electronics and Control
An adaptive neural control methodology design for dynamics mobile robot

Mobile robot
Neural network controller
Path planning
Slice genetic algorithm
Trajectory tracking

The paper demonstrates an enhancement in the mobile robot’s performance during trajectory tracking with static obstacles. An adaptive artificial neural network (ANN) control methodology with online tuning evolutionary slice genetic algorithm is used for the motion control of the nonlinear dynamics mobile robot system. This paper aims at locating the optimal path from the starting point to the target point and designing an ANN trajectory tracking control methodology. The algorithm is simulated with fixed-global environment obstacles to demonstate the effectiveness of the ANN controller and the evolutionary optimization algorithm in terms of the shortest path length generated and the minimum number of the evaluation cost function calculated. The simulation results illustrate that the ANN controller’s
parameters are obtained quickly, generating smooth wheels’ torque actions for the mobile robot platform with a minimum cost function evolution that lead to minimize the tracking error to approximately zero with no oscillation in the responses.

Khulood Eskander Dagher, Rabab Alaa Hameed, Ibrahim Amer Ibrahim, Muntaha Razak

Universitas Ahmad Dahlan

April 2022

Sri Wahyuni

ISSN: 1693-6930

PDF

English

Text