Sliding mode recurrent wavelet neural network control for robust positioning of uncertain dynamic systems

Abstract For an uncertain dynamic system, a hybrid control system composed of sliding mode and recurrent wavelet neural network control with friction estimation (SRWNF) has been proposed to achieve robust motion performance. In the present study, a model-free adaptive controller that does not require the system dynamics to be determined in advance is developed by the proposed recurrent wavelet neural network (RWNN). The adaptive laws of the SRWNF control system and friction estimator have been constructed from the approximation theory and the sense of the Lyapunov stability analysis for RWNN technology to mimic ideal control laws in a sliding-mode control. In addition, an adaptive bound estimation law is employed to estimate the upper boundary of approximation errors. The friction state and parameters are estimated using an adaptive friction estimation based on the LuGre friction model. The boundary of the constraint sets has also been studied. The performance of the proposed control scheme in the presence of uncertainty and friction has been verified by some simulation and an experiment.

[1]  Jan Swevers,et al.  An integrated friction model structure with improved presliding behavior for accurate friction compensation , 1998, IEEE Trans. Autom. Control..

[2]  Jin Bae Park,et al.  Adaptive Dynamic Surface Control of Flexible-Joint Robots Using Self-Recurrent Wavelet Neural Networks , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[3]  Qinghua Zhang,et al.  Using wavelet network in nonparametric estimation , 1997, IEEE Trans. Neural Networks.

[4]  Carlos Canudas de Wit,et al.  A new model for control of systems with friction , 1995, IEEE Trans. Autom. Control..

[5]  Faa-Jeng Lin,et al.  Recurrent wavelet neural network controller with improved particle swarm optimisation for induction generator system , 2009 .

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

[7]  Hualin Tan,et al.  Adaptive backstepping control and friction compensation for AC servo with inertia and load uncertainties , 2003, IEEE Trans. Ind. Electron..

[8]  Rajnikant V. Patel,et al.  Friction Identification and Compensation in Robotic Manipulators , 2007, IEEE Transactions on Instrumentation and Measurement.

[9]  Chi-Huang Lu,et al.  Design and Application of Stable Predictive Controller Using Recurrent Wavelet Neural Networks , 2009, IEEE Transactions on Industrial Electronics.

[10]  Carlos Canudas-de-Wit,et al.  Friction compensation for an industrial hydraulic robot , 1999 .

[11]  Kwang Y. Lee,et al.  Diagonal recurrent neural networks for dynamic systems control , 1995, IEEE Trans. Neural Networks.

[12]  Tommy W. S. Chow,et al.  A recurrent neural-network-based real-time learning control strategy applying to nonlinear systems with unknown dynamics , 1998, IEEE Trans. Ind. Electron..

[13]  Vincent Hayward,et al.  Single state elastoplastic friction models , 2002, IEEE Trans. Autom. Control..

[14]  Jan Swevers,et al.  The generalized Maxwell-slip model: a novel model for friction Simulation and compensation , 2005, IEEE Transactions on Automatic Control.

[15]  Daniel W. C. Ho,et al.  Fuzzy wavelet networks for function learning , 2001, IEEE Trans. Fuzzy Syst..

[16]  Bernard Delyon,et al.  Accuracy analysis for wavelet approximations , 1995, IEEE Trans. Neural Networks.

[17]  P. Dupont,et al.  Single State Elasto-Plastic Friction Models , 2002 .

[18]  Carlos Canudas de Wit,et al.  Adaptive friction compensation with partially known dynamic friction model , 1997 .

[19]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[20]  Faa-Jeng Lin,et al.  Field-programmable gate array-based recurrent wavelet neural network control system for linear ultrasonic motor , 2009 .

[21]  Hendrik Van Brussel,et al.  Friction characterization and compensation in electro-mechanical systems , 2007 .

[22]  Wen-Fang Xie,et al.  Sliding-Mode Observer Based Adaptive Control for Servo Actuator with Friction , 2007, 2007 International Conference on Mechatronics and Automation.

[23]  T.H. Lee,et al.  Adaptive friction compensation of servo mechanisms , 1999, Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328).

[24]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control - design and stability analysis , 1994 .

[25]  Rong-Jong Wai,et al.  Adaptive backstepping control using recurrent neural network for linear induction motor drive , 2002, IEEE Trans. Ind. Electron..