Robust control of mobile robot in presence of disturbances using neural network and global fast sliding mode

Article type: Research Article

Authors: Mallem, Ali^{a; *} | Slimane, Noureddine^b | Benaziza, Walid^b

Correspondence: [*] Corresponding author: Ali Mallem, Electronics Department, Batna 2 University, street Chahid Boukhlouf M^edEl Hadi,Batna, Algeria. E-mail: ali_mallem@hotmail.fr.

Abstract: In this paper a dynamic tracking control of mobile robot using neural network global fast sliding mode (NN-GFSM) is presented. The proposed strategy combines two control approaches, kinematic control and dynamic control. The laws of kinematic control are based on GFSM in order to determine the adequate velocities for the system stability in finite time. The dynamic controller combines two control techniques, the GFSM to stabilize the velocities errors, and a neural network controller in order to approximate a nonlinear function and to deal the disturbances. This dynamic controller allows the robots to follow the desired trajectory even in the presence of disturbances. The designed controller is dynamically simulated by using Matlab/ Simulink and the simulations results show the efficiency and robustness of the proposed control strategy.

Keywords: Kinematic model, dynamic model, RBF neural network, sliding mode, tracking control, Lyapunov stability

DOI: 10.3233/JIFS-17864

Journal: Journal of Intelligent & Fuzzy Systems, vol. 34, no. 6, pp. 4345-4354, 2018