Neural-network-based discrete-time variable structure control of robotic manipulators

This paper presents a neural-network-based discrete-time variable structure control for a planar robotic manipulator. Radial basis function neural networks are used to learn about uncertainties affecting the system. The analysis of the control stability is given and the controller is experimentally evaluated on the ERICC robot arm. The experiments show that the proposed controller produces good trajectory tracking performance and is robust in the presence of model inaccuracies.

[1]  Peng-Yung Woo,et al.  An adaptive fuzzy sliding mode controller for robotic manipulators , 2003, IEEE Trans. Syst. Man Cybern. Part A.

[2]  Jun-Ho Oh,et al.  Improvements on VSS-type self-tuning control for a tracking controller , 1998, IEEE Trans. Ind. Electron..

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

[4]  Paramasivan Saratchandran,et al.  Performance evaluation of a sequential minimal radial basis function (RBF) neural network learning algorithm , 1998, IEEE Trans. Neural Networks.

[5]  Corrado Guarino Lo Bianco,et al.  Nonlinear filters for the generation of smooth trajectories , 2000, Autom..

[6]  Frank L. Lewis,et al.  Neural net robot controller: Structure and stability proofs , 1993, J. Intell. Robotic Syst..

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

[8]  Yoshiki Uchikawa,et al.  A neural network compensator for uncertainties of robotics manipulators , 1992, IEEE Trans. Ind. Electron..

[9]  Robert M. Sanner,et al.  Stable Adaptive Control of Robot Manipulators Using Neural Networks , 1995, Neural Computation.

[10]  Okyay Kaynak,et al.  Neuro sliding mode control of robotic manipulators , 2000 .

[11]  A. Zinober.  Variable Structure and Lyapunov Control , 1994 .

[12]  Frank L. Lewis,et al.  Multilayer neural-net robot controller with guaranteed tracking performance , 1996, IEEE Trans. Neural Networks.

[13]  Okyay Kaynak,et al.  Discrete-time sliding mode control in the presence of system uncertainty , 1993 .

[14]  Vadim I. Utkin,et al.  Sliding Modes in Control and Optimization , 1992, Communications and Control Engineering Series.

[15]  Shuzhi Sam Ge,et al.  Adaptive Neural Network Control of Robotic Manipulators , 1999, World Scientific Series in Robotics and Intelligent Systems.

[16]  Xuemei Ren,et al.  Neural Network-Based Compensation Control of Robot Manipulators with Unknown Dynamics , 2007, 2007 American Control Conference.

[17]  S. Nicosia,et al.  Robot control by using only joint position measurements , 1990 .

[18]  G. Feng,et al.  An adaptive fuzzy controller based on sliding mode for robot manipulators , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[19]  Fuchun Sun,et al.  Neural network-based adaptive controller design of robotic manipulators with an observer , 2001, IEEE Trans. Neural Networks.

[20]  Katsuhisa Furuta,et al.  VSS type self-tuning control , 1993, IEEE Trans. Ind. Electron..

[21]  Tzyh Jong Tarn,et al.  Effect of motor dynamics on nonlinear feedback robot arm control , 1991, IEEE Trans. Robotics Autom..

[22]  Toshio Fukuda,et al.  Adaptive quasi-sliding-mode tracking control for discrete uncertain input-output systems , 2001, IEEE Trans. Ind. Electron..

[23]  C.Y. Chan.  Discrete adaptive sliding-mode tracking controller , 1997, Autom..

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

[25]  Sauro Longhi,et al.  Lyapunov-based switching control using neural networks for a remotely operated vehicle , 2007, Int. J. Control.

[26]  G. Oriolo,et al.  Robotics: Modelling, Planning and Control , 2008 .

[27]  F. Girosi,et al.  Networks for approximation and learning , 1990, Proc. IEEE.

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

[29]  Shang-Liang Chen,et al.  Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.

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

[31]  Malur K. Sundareshan,et al.  A recurrent neural network-based adaptive variable structure model following control of multijointed robotic manipulators , 1992, [1992] Proceedings of the 31st IEEE Conference on Decision and Control.

[32]  Sauro Longhi,et al.  Learning control of mobile robots using a multiprocessor system , 2006 .

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

[34]  Maria Letizia Corradini,et al.  A discrete adaptive variable-structure controller for MIMO systems, and its application to an underwater ROV , 1997, IEEE Trans. Control. Syst. Technol..

[35]  Frank L. Lewis,et al.  Neural Network Control Of Robot Manipulators And Non-Linear Systems , 1998 .

[36]  Yoshiki Uchikawa,et al.  Trajectory control of robotic manipulators using neural networks , 1991 .