An adaptive neural control methodology design for dynamics mobile robot

Autor:	Khulood Eskander Dagher, Rabab Alaa Hameed, Ibrahim Amer Ibrahim, Muntaha Razak
Rok vydání:	2022
Předmět:	neural network controller Computer Science::Neural and Evolutionary Computation slice genetic algorithm tajectory tracking Electrical and Electronic Engineering mobile robot path planning
Zdroj:	TELKOMNIKA (Telecommunication Computing Electronics and Control). 20:392
ISSN:	2302-9293 1693-6930
DOI:	10.12928/telkomnika.v20i2.20923
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b04b355e6f70a9d0a52daa189b6ac363 https://doi.org/10.12928/telkomnika.v20i2.20923 Zobrazit plný text záznamu Plný text ve formátu PDF