Controller Design and Simulation High-Gain Nonlinear Observer for Three-Joint PUMA Robot Regards to Adaptive Fuzzy Sliding Mode Controller with Uncertainly Condition
محورهای موضوعی : مهندسی هوشمند برقMahsa Motaei 1 , Mehdi Edrisi 2 , Ghazanfar Shahgholian 3
1 - Najafabad Branch, Islamic Azad University
2 - Department of Electronics Engineering, Isfahan University, Isfahan, Iran
3 - Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Isfahan, Iran
کلید واژه: Linearization, adaptive, Observer, Fuzzy Takagi-Sugeno,
چکیده مقاله :
In this study, a novel sliding mode adaptive controller is developed for three-link PUMA robot, regards to high-gain fuzzy observer in an uncertainty condition. The studied system has uncertain nonlinear functions, multiple inputs and outputs, and non-measurable scenarios, and therefore requires an observation design. To design the controller, fuzzy systems were initially utilized to approximate non-linear uncertain functions, and then a sup posable observer is available to estimate non-measurable system states. Finally, by combining the adaptive fuzzy controller and feedback lineari zation method, a high-gain observer-based fuzzy control was developed. In order to this approach is used as enhance performance indicators of the control system. Fuzzy Takagi-Sugeno systems were employed to find the control gain. In the proposed control method, the convergence of tracking the desired reference signal of the system can be guaranteed by designing the adaption's parameters. The simulation results demonstrated the validity of the control method. .
In this study, a novel sliding mode adaptive controller is developed for three-link PUMA robot, regards to high-gain fuzzy observer in an uncertainty condition. The studied system has uncertain nonlinear functions, multiple inputs and outputs, and non-measurable scenarios, and therefore requires an observation design. To design the controller, fuzzy systems were initially utilized to approximate non-linear uncertain functions, and then a sup posable observer is available to estimate non-measurable system states. Finally, by combining the adaptive fuzzy controller and feedback lineari zation method, a high-gain observer-based fuzzy control was developed. In order to this approach is used as enhance performance indicators of the control system. Fuzzy Takagi-Sugeno systems were employed to find the control gain. In the proposed control method, the convergence of tracking the desired reference signal of the system can be guaranteed by designing the adaption's parameters. The simulation results demonstrated the validity of the control method. .
