Design Artificial Nonlinear Controller Based on Computed Torque like Controller with Tunable Gain

Abstract

One of the most active research areas in the field of robotics is robot arms control, because these systems are multi-input multi-output (MIMO), nonlinear, time variant and uncertainty. An artificial non linear robust controller design is major subject in this work. At present, robot manipulators are used in unknown and unstructured situation and caused to provide complicated systems, consequently nonlinear classical controllers are used in artificial intelligence control methodologies to design nonlinear robust controller with satisfactory performance (e.g. minimum error, good trajectory, disturbance rejection). Computed torque controller (CTC) is the best nonlinear robust controllers which can be used in uncertainty nonlinear. Computed torque controller works very well when all nonlinear dynamic parameters are known. This research is focused on the applied non- classical method (e.g. Fuzzy Logic) in robust classical method (e.g. computed torque controller) in the presence of uncertainties and external disturbance to reduce the limitations. Applying the Mamdani's error based fuzzy logic controller with minimum rules is the first goal that causes the elimination of the mathematical nonlinear dynamic CTC. Second target focuses on the elimination of oscillation with regard to the variety of uncertainty and external disturbance in computed torque like controller by optimization the tunable gain. Therefore computed torque like controller with tunable gain (GTCTLC) will be presented in this paper.