Adaptive Fuzzy Control of a Mobile Manipulator Robot

Authors

Shahrood University of Technology

Abstract

A mobile manipulator robot is known as a complex system due to some properties such as coupling between the manipulator and mobile chassis, holonomic and nonholonomic constraints, multivariable and nonlinear dynamics. The control of robot faces the external disturbance, parametric uncertainty and unmodeled dynamics. Therefore, the use of an adaptive fuzzy system is suggested for its capability in overcoming uncertainties and approximating of nonlinear functions based on the universal approximation theorem. However, the tracking error does not converge asymptotically to zero due to the approximation error of the fuzzy system. This paper presents a novel adaptive fuzzy control for a mobile manipulator robot. The novelty of paper is compensating the approximation error of fuzzy system for asymptotic convergence in tracking the desired trajectory in the presence of uncertainties. For this purpose, the closed loop system in the error space converges to a linear system with poles having negative real parts. The control design consists of two parts; the kinematic control and dynamic control in which the novelty is for the dynamic control. The dynamic modeling and motion control of the nonholonomic wheeled mobile manipulator robot is considered in this paper. Advantages of the proposed design are the simplicity and very good performance in tracking of the desired trajectory in the presence of uncertainties. The stability of control system and convergence to the desired trajectory are proven by the Lyapunov method. The simulation results show the superiority of the proposed control over a robust adaptive control.

Main Subjects


[1] White GD, Bhatt RM, Krovi VN (2007) Dynamic redundancy resolution in a nonholonomic wheeled mobile manipulator. Robotica 25(2): 147–156.
[2] Boukattaya M, Jallouli M, Damak T (2012) On trajectory tracking control for a nonholonomic mobile manipulators with dynamic uncertainties and external torque disturbances. Robot Auton Syst 60(12): 1640–1647.
[3] Boukattaya M, Damak T, Jallouli M (2011) Robust adaptive control for mobile manipulators. Int J Autom Comput 8(1): 8–13.
[4] Das T, Kar IN (2006) Design and implementation of an adaptive fuzzy logic-based controller for wheeled mobile robots. IEEE Trans Control Syst Technol 14(3): 501–510.
[5] Chen N, Song F, Li G, Sun X, Ai C (2013) An adaptive sliding mode backstepping control for the mobile manipulator with nonholonomic constraints. Commun Nonlinear Sci Numer Simul 18(10): 2885–2899.
[6] White GD, Bhatt RM, Tang CP, Krovi VN (2009) Experimental evaluation of dynamic redundancy resolution in a nonholonomic wheeled mobile manipulator. IEEE/ASME Trans Mechatronics 14(3): 349–357.
[7] Yamamoto Y, Yun X (1996) Effect of the dynamic interaction on coordinated control of mobile manipulators. IEEE Trans Robotics and Automation 12(5): 816–824.
[8] Li Z, Ge SS, Ming A (2007) Adaptive robust motion/force control of holonomic-constrained nonholonomic mobile manipulators. IEEE Trans Systems Man Cybern Part B 37(3): 607–616.
[9] Li Z, Yang Y, Li J (2010) Adaptive motion/force control of mobile under-actuated manipulators with dynamics uncertainties by dynamic coupling and output feedback. IEEE Trans Control Syst Technolology 18(5): 1068–1079.
[10] Sun F, Sun Z, Feng G (1999) An adaptive fuzzy controller based on sliding mode for robot manipulators. IEEE Trans Syst Man Cybern Part B   29(5): 661–667.
[11] Fateh MM, Fateh S (2012) Decentralized direct adaptive fuzzy control of robots using voltage control strategy. Nonlinear Dyn 70(3): 1919–1930.
[12] Fateh MM (2010) Robust fuzzy control of electrical manipulators. J Intel Robot Syst 60(3-4): 415–434.
[13] Park CW, Park M (2004) Adaptive parameter estimator based on T–S fuzzy models and its applications to indirect adaptive fuzzy control design. Information Sciences 159(1): 125–139.
[14] Fateh MM, Khorashadizadeh S (2012) Robust control of electrically driven robots by adaptive fuzzy estimation of uncertainty. Nonlinear Dyn 69(3): 1465–1477.
[15] Liu Y, Li Y (2006) Dynamic modeling and adaptive neural-fuzzy control for nonholonomic mobile manipulators moving on a slope. Int J Control Autom Syst 4(2): 197.
[16] Li Z, Chen W (2008) Adaptive neural-fuzzy control of uncertain constrained multiple coordinated nonholonomic mobile manipulators. Eng Appl Artifl Intel 21(7): 985–1000.
[17] Lin S, Goldenberg AA (2001) Neural-network control of mobile manipulators. IEEE Trans Neural Networks 12(5): 1121–1133.
[18] Siciliano B, Khatib O (2008) Springer handbook of robotics, Springer.
[19] Sarkar N, Yun X, Kumar V (1994) Control of Mechanical Systems With Rolling Constraints Application to Dynamic Control of Mobile Robots. Int J Robot Research 13(1): 55–69.
[20] Kanayama Y, Kimura Y, Miyazaki F, Noguchi T (1990) A stable tracking control method for an autonomous mobile robot. Proc IEEE Conf on Robotics Automation 13-18 Cincinnati, OH.