Quasi sliding mode‐based single input fuzzy self‐tuning decoupled fuzzy PI control for robot manipulators with uncertainty

SUMMARY This paper presents a robust adaptive control strategy for robot manipulators, based on the coupling of the fuzzy logic control with the so-called sliding mode control (SMC) approach. The motivation for using SMC in robotics mainly relies on its appreciable features. However, the drawbacks of the conventional SMC, such as chattering effect and required a priori knowledge of the bounds of uncertainties can be destructive. In this paper, these problems are suitably circumvented by adopting a reduced rule base single input fuzzy self tuning decoupled fuzzy proportional integral sliding mode control approach. In this new approach a decoupled fuzzy proportional integral control is used and a reduced rule base single input fuzzy self-tuning controller as a supervisory fuzzy system is added to adaptively tune the output control gain of the decoupled fuzzy proportional integral control. Moreover, it is proved that the fuzzy control surface of the single-input fuzzy rule base is very close to the input/output relation of a straight line. Therefore, a varying output gain decoupled fuzzy proportional integral sliding mode control approach using an approximate line equation is then proposed. The stability of the system is guaranteed in the sense of the Lyapunov theorem. Simulations using the dynamic model of a 3DOF planar manipulator with uncertainties show the effectiveness of the approach in high speed trajectory tracking problems. The simulation results that are compared with the results of conventional SMC indicate that the control performance of the robot system is satisfactory and the proposed approach can achieve favorable tracking performance, and it is robust with regard to uncertainties and disturbances. Copyright © 2011 John Wiley & Sons, Ltd.

[1]  Jeang-Lin Chang,et al.  Sliding-Mode Force Control of Manipulators , 1999 .

[2]  Ahmad B. Rad,et al.  Adaptive fuzzy sliding mode control with chattering elimination for nonlinear SISO systems , 2009, Simul. Model. Pract. Theory.

[3]  M. Z. Jahromi,et al.  Chattering-free fuzzy sliding mode control in MIMO uncertain systems , 2009 .

[4]  J. J. Slotine,et al.  Tracking control of non-linear systems using sliding surfaces with application to robot manipulators , 1983, 1983 American Control Conference.

[5]  D. P. Kothari,et al.  Optimal thermal generating unit commitment: a review , 1998 .

[6]  Ahmed El Hajjaji,et al.  Improved fuzzy sliding mode control for a class of MIMO nonlinear uncertain and perturbed systems , 2011, Appl. Soft Comput..

[7]  Yuanchun Li,et al.  Decentralized adaptive fuzzy sliding mode control for reconfigurable modular manipulators , 2010 .

[8]  Hasan Komurcugil,et al.  Decoupled sliding-mode controller based on time-varying sliding surfaces for fourth-order systems , 2010, Expert Syst. Appl..

[9]  Shubhi Purwar Higher Order Sliding Mode Controller for Robotic Manipulator , 2007, 2007 IEEE 22nd International Symposium on Intelligent Control.

[10]  P. Dorato,et al.  Survey of robust control for rigid robots , 1991, IEEE Control Systems.

[11]  Long Cheng,et al.  Adaptive neural network tracking control for manipulators with uncertain kinematics, dynamics and actuator model , 2009, Autom..

[12]  Shay-Ping Thomas Wang Nonlinear robust industrial robot control , 1987 .

[13]  Antonella Ferrara,et al.  Second order sliding mode motion control of rigid robot manipulators , 2007, 2007 46th IEEE Conference on Decision and Control.

[14]  Abdelaziz Hamzaoui,et al.  Fuzzy sliding mode control for a class of non-linear continuous systems , 2006, Int. J. Comput. Appl. Technol..

[15]  Srinivasan Alavandar,et al.  New hybrid adaptive neuro-fuzzy algorithms for manipulator control with uncertainties- comparative study. , 2009, ISA transactions.

[16]  J. Juang,et al.  Predictive feedback and feedforward control for systems with unknown disturbances , 1999 .

[17]  Xingjia Yao,et al.  Adaptive Fuzzy Sliding-mode Control in Variable Speed Adjustable Pitch Wind Turbine , 2007, 2007 IEEE International Conference on Automation and Logistics.

[18]  Ahmed El Hajjaji,et al.  Improved observer-based adaptive fuzzy tracking control for MIMO nonlinear systems , 2009, 2009 IEEE International Conference on Fuzzy Systems.

[19]  K. Shyu,et al.  Control of rigid robot manipulators via combination of adaptive sliding mode control and compensated inverse dynamics approach , 1996 .

[20]  Min Cheol Lee,et al.  PID sliding mode control for steering of lateral moving strip in hot strip rolling , 2009 .

[21]  Leila Notash,et al.  Adaptive sliding mode control with uncertainty estimator for robot manipulators , 2010 .

[22]  Anna Kucerová,et al.  Optimal design and optimal control of structures undergoing finite rotations and elastic deformations , 2009, ArXiv.

[23]  Yeong-Chan Chang,et al.  Robust tracking control for nonlinear MIMO systems via fuzzy approaches , 2000, Autom..

[24]  Hakan Elmali,et al.  Theory and implementation of sliding mode control with perturbation estimation (SMCPE) , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[25]  Hongnian Yu,et al.  Variable structure adaptive control of robot manipulators , 1997 .

[26]  A. B. Rad,et al.  Robust fuzzy tracking control for robotic manipulators , 2007, Simul. Model. Pract. Theory.

[27]  Romeo Ortega,et al.  Adaptive motion control of rigid robots: a tutorial , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[28]  Chun-Yi Su,et al.  A sliding mode controller with bound estimation for robot manipulators , 1993, IEEE Trans. Robotics Autom..

[29]  Nurkan Yagiz,et al.  Robust control of a spatial robot using fuzzy sliding modes , 2009, Math. Comput. Model..