Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach

[1]  Van,et al.  L2-Gain Analysis of Nonlinear Systems and Nonlinear State Feedback H∞ Control , 2004 .

[2]  F.L. Lewis,et al.  Nearly optimal HJB solution for constrained input systems using a neural network least-squares approach , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[3]  S. N. Balakrishnan,et al.  State-constrained agile missile control with adaptive-critic-based neural networks , 2002, IEEE Trans. Control. Syst. Technol..

[4]  George G. Lendaris,et al.  Adaptive dynamic programming , 2002, IEEE Trans. Syst. Man Cybern. Part C.

[5]  H. W. J. LEE,et al.  Construction of Suboptimal Feedback Control for Chaotic Systems using B-splines with Optimally Chosen knot Points , 2001, Int. J. Bifurc. Chaos.

[6]  Frank L. Lewis,et al.  Introduction to the special issue on neural network feedback control , 2001, Autom..

[7]  George G. Lendaris,et al.  Globally convergent approximate dynamic programming applied to an autolander , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[8]  Sergey Edward Lyshevski Control Systems Theory with Engineering Applications , 2001 .

[9]  S. Lyshevski Role of performance functionals in control laws design , 2001, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[10]  Frank L. Lewis,et al.  Intelligent optimal control of robotic manipulators using neural networks , 2000, Autom..

[11]  Tim B. Swartz,et al.  Approximating Integrals Via Monte Carlo and Deterministic Methods , 2000 .

[12]  K. Teo,et al.  Solving Hamilton-Jacobi-Bellman equations by a modified method of characteristics , 2000 .

[13]  F. D. Lio,et al.  On the Bellman Equation for Infinite Horizon Problems with Unbounded Cost Functional , 2000 .

[14]  Andrew W. Moore,et al.  Gradient descent approaches to neural-net-based solutions of the Hamilton-Jacobi-Bellman equation , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[15]  Thomas Parisini,et al.  Neural approximations for infinite-horizon optimal control of nonlinear stochastic systems , 1998, IEEE Trans. Neural Networks.

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

[17]  S. Lyshevski Optimal control of nonlinear continuous-time systems: design of bounded controllers via generalized nonquadratic functionals , 1998, Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207).

[18]  G. Saridis,et al.  Approximate Solutions to the Time-Invariant Hamilton–Jacobi–Bellman Equation , 1998 .

[19]  M. Bardi,et al.  Optimal Control and Viscosity Solutions of Hamilton-Jacobi-Bellman Equations , 1997 .

[20]  Randal W. Beard,et al.  Galerkin approximations of the generalized Hamilton-Jacobi-Bellman equation , 1997, Autom..

[21]  S. Lyashevskiy Constrained optimization and control of nonlinear systems: new results in optimal control , 1996, Proceedings of 35th IEEE Conference on Decision and Control.

[22]  Marios M. Polycarpou,et al.  Stable adaptive neural control scheme for nonlinear systems , 1996, IEEE Trans. Autom. Control..

[23]  Jie Huang,et al.  Numerical approach to computing nonlinear H-infinity control laws , 1995 .

[24]  S. Lyashevskiy,et al.  Control system analysis and design upon the Lyapunov method , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[25]  Andrew R. Teel,et al.  Control of linear systems with saturating actuators , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[26]  Eduardo Sontag,et al.  A general result on the stabilization of linear systems using bounded controls , 1994, IEEE Trans. Autom. Control..

[27]  Chen-Chung Liu,et al.  Adaptively controlling nonlinear continuous-time systems using multilayer neural networks , 1994, IEEE Trans. Autom. Control..

[28]  Manolis A. Christodoulou,et al.  Adaptive control of unknown plants using dynamical neural networks , 1994, IEEE Trans. Syst. Man Cybern..

[29]  Dennis S. Bernstein,et al.  Optimal nonlinear, but continuous, feedback control of systems with saturating actuators , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[30]  Nader Sadegh,et al.  A perceptron network for functional identification and control of nonlinear systems , 1993, IEEE Trans. Neural Networks.

[31]  A. Schaft L/sub 2/-gain analysis of nonlinear systems and nonlinear state-feedback H/sub infinity / control , 1992 .

[32]  Jean-Jacques E. Slotine,et al.  Stable adaptive control and recursive identification using radial Gaussian networks , 1991, [1991] Proceedings of the 30th IEEE Conference on Decision and Control.

[33]  Kurt Hornik,et al.  Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks , 1990, Neural Networks.

[34]  Richard S. Sutton,et al.  Neural networks for control , 1990 .

[35]  George N. Saridis,et al.  An Approximation Theory of Optimal Control for Trainable Manipulators , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[36]  W. Ames The Method of Weighted Residuals and Variational Principles. By B. A. Finlayson. Academic Press, 1972. 412 pp. $22.50. , 1973, Journal of Fluid Mechanics.

[37]  D. Kleinman On an iterative technique for Riccati equation computations , 1968 .

[38]  S. Mikhlin,et al.  Variational Methods in Mathematical Physics , 1965 .

[39]  T. Apostol Mathematical Analysis , 1957 .