Computer-based Regressor-free Adaptive Control versus Direct Adaptive Fuzzy Control of the Robotic System

Subject Areas :

Mahmood Nadali ¹ , Abolghasem Nadali ² , Maryam Nadali ³

1 - Department of Power Electrical, College of Electrical, West Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Department of Computer Engineering, Garmsar Branch, Islamic Azad University, Garmsar, Iran
3 - Master of Industrial Engineering, Signaling Department of Railway, Iran

Received: 2019-10-24 Accepted : 2020-02-28 Published : 2019-08-01

Keywords: Flexible-joint Robots, Voltage Control Strategy, Actuator Saturation, Direct Adaptive Fuzzy Control, Robust Adaptive Control,

Abstract :

A comprehensive comparison between regressor-free control and direct adaptive fuzzy control of flexible-joint robots is addressed in this paper. In the proposed regressor-free controller, two critical practical situations are considered: the fact that robot actuators have limited voltages, and limitation on the number of measurement devices. However, in the article "decentralized direct adaptive fuzzy control for flexible-joint robots," these limitations have been neglected. It should be noted that a few solutions for the voltage-bounded robust tracking control of flexible joint robots have been proposed. In this paper; we contribute to this subject by presenting a new form of voltage-based controllers. The closed-loop control system stability is proved, and uniformly boundedness of the joint position errors is guaranteed. As a second contribution of this paper, we present a robust adaptive control scheme without the need for computation of the regressor matrix with the same result on the closed-loop system stability. Experimental results of the proposed controller and the decentralized direct adaptive fuzzy controller are produced using MATLAB/SIMULINK external mode control on a single-link flexible-joint electrically driven robot. Experimental and analytical results demonstrate the high performance of the proposed control scheme.

References:

[1] Fateh, M. M. 2012. Robust Control of Fexible-Joint Robots using Voltage Control Strategy. Nonlinear Dynamic. 67: 1525-1537.

[2] Sun, C., Gao, H., He, W. and Yu, Y. 2018. Fuzzy Neural Network Control of a Flexible Robotic Manipulator Using Assumed Mode Method. IEEE Transactions on Neural Networks and Learning Systems. 29(11): 5214-5227.

[3] Gao, H., He, W., Zhou, C. and Sun, C. 2018. Neural Network Control of a Two-link Flexible Robotic Manipulator using Assumed Mode Method. IEEE Transactions on Industrial Informatics. 15(2): 755-765.

[4] Qureshi, M. S., Swarnkar, P. and Gupta, S. 2018. A Supervisory Online Tuned Fuzzy Logic based Sliding Mode Control for Robotics: An Application to Surgical Robots. Robotics and Autonomous Systems. 109: 68-85.

[5] He, W., Yan, Z., Sun, Y., Ou, Y. and Sun, C. 2018. Neural-Learning-Based Control for a Constrained Robotic Manipulator with Flexible Joints. IEEE Transactions on Neural Networks and Learning Systems. 29(12): 5993-6003.

[6] Rahmani, B. and Belkheiri, M. 2018. Adaptive Neural Network output Feedback Control for Flexible Multi-link Robotic Manipulators. International Journal of Control. 92(10): 1-15.

[7] Khorashadizadeh, S. and Sadeghijaleh, M. 2018. Adaptive Fuzzy Tracking Control of Robot Manipulators Actuated by Permanent Magnet Synchronous Motors. Computers & Electrical Engineering. 72: 100-111.

[8] Fateh, M. M. 2012. Nonlinear Control of Electrical Flexible-joint Robots. Nonlinear Dynamic. 67: 2549-2559.

[9] Fateh, M.M. 2013. Decentralized Direct Adaptive Fuzzy Control for Flexible-joint Robots. Control Engineering and Applied Informatics. 15(4): 97-105.

[10] Izadbakhsh, A. 2017. FAT-based Robust Adaptive Control of Electrically Driven Robots without Velocity Measurements. Nonlinear Dynamics. 89: 289-304.

[11] Haung, A. C. and Liao, K. K. 2006. FAT-based Adaptive Sliding Control for Flexible Arms: Theory and Experiments. Journal of Sound and Vibration. 298: 194-205.

[12] Huang, A. C., An-chyau, H., Ming-chih, C., and Chien, M. C. 2010. Adaptive Control of Robot Manipulator: A Unified Regressor Free Approach. World Scientific.

[13] Huang, A. C. and Kuo, Y. S. 2001. Sliding Control of Nonlinear Systems Containing Time-Varying Uncertainties with Unknown Bounds. International Journal of Control. 74: 252–264.

[14] Izadbakhsh, A. 2016. Robust Control Design for Rigid-link Flexible-joint Electrically Driven Robot Subjected to Constraint: Theory and Experimental Verification. Nonlinear Dynamic. 85: 751-765.

[15] Moreno-Valenzuela, J., Campa, R. and Santibáñez, V. 2013. Model-based Control of a Class of Voltage-driven Robot Manipulators with Non-passive Dynamics. Computers & Electrical Engineering. 39: 2086-2099.