Fuzzy and neural network control system of intelligent BLED arm manipulators for dynamic obstacles

This paper presents a fuzzy neural network close loop control system for nonlinear electromechanical systems of an electric motor actuating an arm robot. This control system is applied to the three basic navigation problems of intelligent robot systems in unstructured environments: autonomous planning, fast nonstop navigation without collision with obstacles, and dealing with structured and/or unstructured uncertainties. The simulation results show that the effective intelligent capability of the proposed motion-planning algorithm to deal with moving and unknown obstacles and a new intelligent motion control strategy that makes possible the integration of fuzzy neural networks control has been proposed for autonomous navigation of BLED robot manipulators.