Document Type : Reseach Article

Authors

1 Department of Automatics, Faculty of Electrical and Computer Engineering, University Mouloud Mammeri of Tizi-Ouzou, Tizi-Ouzou, Algeria.

2 IREENA Laboratory, Department of Electrical Engineering, University of Nantes, Saint-Nazaire, France.

10.30486/mjee.2025.710229

Abstract

In this paper, an intelligent adaptive controller is designed to handle the transmission time delay problem in a complex and nonlinear bilateral teleoperation system with force feedback. The combination of the inference capacities of fuzzy logic reasoning and the learning capacities of neural networks, enable the formation of an adaptive and robust neuro-fuzzy controller ANFIS (Adaptive Neuro-Fuzzy Inference System) which adapts to variations in the dynamics of the system by the automatic adjustment of the parameters of the fuzzy rules and the membership functions using a learning algorithm, thus ensuring compensation of the negative effects of transmission delay in the closed loop system. Thanks to the speed and power of the microprocessor of the Arduino Due board and the functionalities of Matlab-Simulink, a real experimental platform of master-slave teleoperation system with transmission delay and force feedback is designed. In order to demonstrate the efficiency, adaptability and advantages of ANFIS controller, several comparative experiments are carried out using different controllers (ANFIS, conventional PI and PI regulator with the modified wave variable method PI+MWVM). The experimental results clearly show the high system performance achieved with the ANFIS
controller.

Keywords

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