NLq Theory: A Neural Control Framework with Global Asymptotic Stability Criteria

[1]  J. Suykens,et al.  Discrete Time Interconnected Cellular Neural Networks Within NLq Theory , 1996, Int. J. Circuit Theory Appl..

[2]  Johan A. K. Suykens,et al.  Control of a recurrent neural network emulator for the double scroll , 1996 .

[3]  Johan A. K. Suykens,et al.  Absolute stability criterion for a Lur'e problem with multilayer perceptron nonlinearity , 1996 .

[4]  Johan A. K. Suykens,et al.  Artificial neural networks for modelling and control of non-linear systems , 1995 .

[5]  Stephen P. Boyd,et al.  A primal—dual potential reduction method for problems involving matrix inequalities , 1995, Math. Program..

[6]  J. Suykens,et al.  Nonlinear system identification using neural state space models, applicable to robust control design , 1995 .

[7]  Johan A. K. Suykens,et al.  Static and dynamic stabilizing neural controllers, applicable to transition between equilibrium points , 1994, Neural Networks.

[8]  Ah Chung Tsoi,et al.  Locally recurrent globally feedforward networks: a critical review of architectures , 1994, IEEE Trans. Neural Networks.

[9]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[10]  Yurii Nesterov,et al.  Interior-point polynomial algorithms in convex programming , 1994, Siam studies in applied mathematics.

[11]  P. Gahinet,et al.  General-Purpose LMI solvers with benchmarks , 1993, Proceedings of 32nd IEEE Conference on Decision and Control.

[12]  Russell Reed,et al.  Pruning algorithms-a survey , 1993, IEEE Trans. Neural Networks.

[13]  E. Kaszkurewicz,et al.  Robust stability and diagonal Lyapunov functions , 1993 .

[14]  Allan Pinkus,et al.  Multilayer Feedforward Networks with a Non-Polynomial Activation Function Can Approximate Any Function , 1991, Neural Networks.

[15]  Leon O. Chua,et al.  Stability analysis of generalized cellular neural networks , 1993, Int. J. Circuit Theory Appl..

[16]  Andrew Packard,et al.  The complex structured singular value , 1993, Autom..

[17]  Peter J. Gawthrop,et al.  Neural networks for control systems - A survey , 1992, Autom..

[18]  A. Michel,et al.  Asymptotic stability of discrete-time systems with saturation nonlinearities with applications to digital filters , 1992 .

[19]  L. Ljung,et al.  Overtraining, Regularization, and Searching for Minimum in Neural Networks , 1992 .

[20]  M Maarten Steinbuch,et al.  Uncertainty modelling and structured singular-value computation applied to an electromechanical system , 1992 .

[21]  Jacek M. Zurada,et al.  Introduction to artificial neural systems , 1992 .

[22]  George Cybenko,et al.  Approximation by superpositions of a sigmoidal function , 1992, Math. Control. Signals Syst..

[23]  Stephen A. Billings,et al.  Properties of neural networks with applications to modelling non-linear dynamical systems , 1992 .

[24]  A. Stoorvogel.  The discrete time H∞ control problem with measurement feedback , 1992 .

[25]  Kumpati S. Narendra,et al.  Gradient methods for the optimization of dynamical systems containing neural networks , 1991, IEEE Trans. Neural Networks.

[26]  Stephen P. Boyd,et al.  Linear controller design: limits of performance , 1991 .

[27]  B. Widrow,et al.  Neural networks for self-learning control systems , 1990, IEEE Control Systems Magazine.

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

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

[30]  Maciejowsk.  Multivariable Feedback Design , 1989 .

[31]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[32]  Ken-ichi Funahashi,et al.  On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.

[33]  E. Polak,et al.  On the design of linear multivariable feedback systems via constrained nondifferentiable optimization in H/sup infinity / spaces , 1989 .

[34]  M. Overton.  On minimizing the maximum eigenvalue of a symmetric matrix , 1988 .

[35]  Lennart Ljung,et al.  System Identification: Theory for the User , 1987 .

[36]  R. Offereins.  Book review: Digital control system analysis and design , 1985 .

[37]  Graham C. Goodwin,et al.  Adaptive filtering prediction and control , 1984 .

[38]  Elijah Polak,et al.  Nondifferentiable optimization algorithm for designing control systems having singular value inequalities , 1982, Autom..

[39]  Philip E. Gill,et al.  Practical optimization , 1981 .

[40]  P. Moylan,et al.  Connections between finite-gain and asymptotic stability , 1980 .

[41]  C. A. Desoer,et al.  Nonlinear Systems Analysis , 1978 .

[42]  Lennart Ljung,et al.  The Extended Kalman Filter as a Parameter Estimator for Linear Systems , 1979 .

[43]  David J. Hill,et al.  Stability results for nonlinear feedback systems , 1977, Autom..

[44]  P. Moylan,et al.  The stability of nonlinear dissipative systems , 1976 .

[45]  J. Willems.  Dissipative dynamical systems part I: General theory , 1972 .

[46]  J. H. Wilkinson.  The algebraic eigenvalue problem , 1966 .