Investigation on the influence of parameter uncertainties in the position tracking of robot manipulators

This paper presents a novel trajectory tracking method for robot arms with uncertainties in parameters. The new controller applies the robust output feedback linearization method and is designed so that it is robust to the variation of parameters. Robustness of the algorithm is evaluated when the parameters of the system are floating over 10 percent up and down. An Unscented Kalman Filter (UKF) is applied for state and parameter estimation purposes. As the considered system has 8 unknown parameters while only 5 of them are independent parameters, UKF is applied only to the augmented system with independent parameters. Three types of simulations are applied depending on sensor groups – first with both position and joint sensors, second with only position sensors and third with only joint sensors. The observation of parameters in these groups is discussed. Simulation results show that when both position sensors and joint sensors are used, all the parameters and states are observable and good tracking performances are obtained. When only position sensors are used, the accuracy of the estimated parameters is reduced, and low tracking performances are revealed. Finally, when only joint sensors are applied, the lengths of robot arms are unobservable, but other parameters related to the dynamic system are observable, and poor tracking performances are given.

[1]  Hassan K. Khalil,et al.  Adaptive output feedback control of robot manipulators using high-gain observer , 1997 .

[2]  Suguru Arimoto,et al.  Experiments in adaptive model-based force control , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[3]  M. C. Obaiah Multiobjective output feedback controller compare with IMC-based PID controller , 2014 .

[4]  Jianfeng Huang,et al.  Nonlinear pd controllers with gravity compensation for robot manipulators , 2014 .

[5]  Amar Goléa,et al.  Observer-based adaptive control of robot manipulators: Fuzzy systems approach , 2008, Appl. Soft Comput..

[6]  Chintae Choi,et al.  Practical Nonsingular Terminal Sliding-Mode Control of Robot Manipulators for High-Accuracy Tracking Control , 2009, IEEE Transactions on Industrial Electronics.

[7]  Shuzhi Sam Ge,et al.  Adaptive neural network control of robot manipulators in task space , 1997, IEEE Trans. Ind. Electron..

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

[9]  Yin Yanling Model Free Adaptive Control for Robotic Manipulator Trajectory Tracking , 2015 .

[10]  T. S. Chandar,et al.  Robust control of robot manipulators based on uncertainty and disturbance estimation , 2013 .

[11]  Rudolph van der Merwe,et al.  The square-root unscented Kalman filter for state and parameter-estimation , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[12]  Lakmal Seneviratne,et al.  Adaptive Control Of Robot Manipulators , 1992, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Hugh F. Durrant-Whyte,et al.  A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..

[14]  Juan A. Méndez,et al.  Adaptive robust controller for robot manipulators: experiments on a PUMA 560 robot , 2006 .

[15]  Paolo Rocco,et al.  Revising the Robust-Control Design for Rigid Robot Manipulators , 2007, IEEE Transactions on Robotics.

[16]  Homayoun Seraji A new class of nonlinear PID controllers with robotic applications , 1998, J. Field Robotics.

[17]  Roberto Horowitz,et al.  Stability and Robustness Analysis of a Class of Adaptive Controllers for Robotic Manipulators , 1990, Int. J. Robotics Res..

[18]  Sandip Ghosh Multiobjective Output Feedback Controller Compare with IMC-Based PID Controller , 2014 .

[19]  Maruthi R. Akella,et al.  Non-certainty equivalent adaptive control for robot manipulator systems , 2009, Syst. Control. Lett..

[20]  Ricardo O. Carelli,et al.  A class of nonlinear PD-type controllers for robot manipulators , 1996, J. Field Robotics.

[21]  Phillip J. McKerrow,et al.  Introduction to robotics , 1991 .

[22]  S. Shankar Sastry,et al.  Adaptive Control of Mechanical Manipulators , 1987, Proceedings. 1986 IEEE International Conference on Robotics and Automation.

[23]  Suguru Arimoto,et al.  A New Feedback Method for Dynamic Control of Manipulators , 1981 .

[24]  Mahmoud M. Al Ashi,et al.  Trajectory Tracking Control of A 2-DOF Robot Arm Using Neural Networks , 2014 .

[25]  K. Youcef-Toumi,et al.  Robustness and Stability Analysis of Time Delay Control , 1992, 1992 American Control Conference.

[26]  Davoud Fani,et al.  Two-link Robot Manipulator using Fractional Order PID Controllers Optimized by Evolutionary Algorithms , 2016 .

[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]  Seid H. Pourtakdoust,et al.  UD Covariance Factorization for Unscented Kalman Filter using Sequential Measurements Update , 2007 .

[29]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

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

[31]  有本 卓,et al.  Control theory of non-linear mechanical systems : a passivity-based and circuit-theoretic approach , 1996 .

[32]  Jin S. Lee,et al.  Control of flexible joint robot system by backstepping design approach , 1997, Proceedings of International Conference on Robotics and Automation.

[33]  Tien C. Hsia Robustness analysis of a pd controller with approximate gravity compensation for robot manipulator control , 1994, J. Field Robotics.