Radial basis function network approximation and learning in task-dependent feedforward control of nonlinear dynamical systems
暂无分享,去创建一个
[1] M. Spong. Modeling and Control of Elastic Joint Robots , 1987 .
[2] James D. Keeler,et al. Predicting the Future: Advantages of Semilocal Units , 1991, Neural Computation.
[3] Suguru Arimoto,et al. Bettering operation of Robots by learning , 1984, J. Field Robotics.
[4] Andrew A. Goldenberg,et al. Radial basis function network architecture for nonholonomic motion planning and control of free-flying manipulators , 1996, IEEE Trans. Robotics Autom..
[5] Suguru Arimoto,et al. Learning control theory for robotic motion , 1990 .
[6] Jooyoung Park,et al. Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.
[7] D.M. Gorinevsky. Learning and approximation in database for feedforward control of flexible manipulator , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.
[8] M. J. D. Powell,et al. Radial basis functions for multivariable interpolation: a review , 1987 .
[9] Snehasis Mukhopadhyay,et al. Disturbance rejection in nonlinear systems using neural networks , 1993, IEEE Trans. Neural Networks.
[10] Nira Dyn,et al. Interpolation of scattered Data by radial Functions , 1987, Topics in Multivariate Approximation.
[11] Il Hong Suh,et al. An iterative learning control method with application to robot manipulators , 1988, IEEE J. Robotics Autom..
[12] Lyle H. Ungar,et al. Using radial basis functions to approximate a function and its error bounds , 1992, IEEE Trans. Neural Networks.
[13] Andrew A. Goldenberg,et al. Neural network architecture for trajectory generation and control of automated car parking , 1996, IEEE Trans. Control. Syst. Technol..
[14] Visakan Kadirkamanathan,et al. Sequential Adaptation of Radial Basis Function Neural Networks and its Application to Time-series Prediction , 1990, NIPS 1990.
[15] Christopher G. Atkeson,et al. Generalization Properties of Radial Basis Functions , 1990, NIPS.
[16] Dimitry Gorinevsky,et al. RBF network feedforward compensation of load disturbance in idle speed control , 1996 .
[17] D. Gorinevsky. An approach to parametric nonlinear least square optimization and application to task-level learning control , 1997, IEEE Trans. Autom. Control..
[18] David J. Reinkensmeyer,et al. Task-level robot learning , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.
[19] John B. Moore,et al. Exponential convergence of a learning controller for robot manipulators , 1991 .
[20] Nader Sadegh,et al. Experimental evaluation of a new robot learning controller , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.
[21] Peter J. Gawthrop,et al. Neural networks for control systems - A survey , 1992, Autom..
[22] Stephen A. Billings,et al. International Journal of Control , 2004 .
[23] S. Hara,et al. Repetitive control system: a new type servo system for periodic exogenous signals , 1988 .
[24] Chris Bishop,et al. Improving the Generalization Properties of Radial Basis Function Neural Networks , 1991, Neural Computation.
[25] F. Girosi,et al. Networks for approximation and learning , 1990, Proc. IEEE.
[26] Nader Sadegh,et al. A perceptron network for functional identification and control of nonlinear systems , 1993, IEEE Trans. Neural Networks.
[27] R. V. Dooren,et al. A Chebyshev technique for solving nonlinear optimal control problems , 1988 .
[28] John C. Platt. A Resource-Allocating Network for Function Interpolation , 1991, Neural Computation.
[29] D. Gorinevsky. Learning task-dependent input shaping control using radial basis function network , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).
[30] Dimitry M. Gorinevsky. Direct learning of feedforward control for manipulator path tracking , 1992, Proceedings of the 1992 IEEE International Symposium on Intelligent Control.
[31] Roberto Horowitz,et al. A new adaptive learning rule , 1991 .
[32] O Bock,et al. Parametric motion control of robotic arms: a biologically based approach using neural networks , 1993 .
[33] Richard Franke,et al. Recent Advances in the Approximation of surfaces from scattered Data , 1987, Topics in Multivariate Approximation.
[34] Dimitry Gorinevsky,et al. Control of flexible spacecraft using nonlinear approximation of input shape dependence on reorientation maneuver parameters , 1996 .
[35] Sheng Chen,et al. Recursive hybrid algorithm for non-linear system identification using radial basis function networks , 1992 .
[36] Dimitry M. Gorinevsky,et al. On the persistency of excitation in radial basis function network identification of nonlinear systems , 1995, IEEE Trans. Neural Networks.
[37] Michael S. Branicky. Task-level learning: experiments and extensions , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.
[38] Mitsuo Kawato,et al. Adaptation and learning in control of voluntary movement by the central nervous system , 1988, Adv. Robotics.
[39] Christopher G. Atkeson,et al. Using locally weighted regression for robot learning , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.
[40] Robert M. Sanner,et al. Gaussian Networks for Direct Adaptive Control , 1991, 1991 American Control Conference.
[41] Leonard S. Haynes,et al. Learning control system design based on 2D theory-an application to parallel link manipulator , 1990, Proceedings., IEEE International Conference on Robotics and Automation.
[42] Dimitry Gorinevsky,et al. An algorithm for on-line parametric nonlinear least square optimization , 1994, Proceedings of 1994 33rd IEEE Conference on Decision and Control.
[43] C. Micchelli. Interpolation of scattered data: Distance matrices and conditionally positive definite functions , 1986 .
[44] Thomas H. Connolly,et al. Comparison of Some Neural Network and Scattered Data Approximations: The Inverse Manipulator Kinematics Example , 1994, Neural Computation.
[45] Tadashi Ishihara,et al. A discrete-time design of robust iterative learning controllers , 1992, IEEE Trans. Syst. Man Cybern..
[46] E. Kansa. Multiquadrics—A scattered data approximation scheme with applications to computational fluid-dynamics—I surface approximations and partial derivative estimates , 1990 .
[47] Shang-Liang Chen,et al. Orthogonal least squares learning algorithm for radial basis function networks , 1991, IEEE Trans. Neural Networks.
[48] John Moody,et al. Fast Learning in Networks of Locally-Tuned Processing Units , 1989, Neural Computation.
[49] Enis Ersü,et al. Learning control with interpolating memories―general ideas, design lay-out, theoretical approaches and practical applications , 1992 .
[50] R. Franke. Scattered data interpolation: tests of some methods , 1982 .