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It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are(More)
This paper considers the problem of using approximate methods for realizing the neural controllers for nonlinear multivariable systems. In [1] the NARMA-L1 and NARMA-L2 models were introduced as approximations of he NARMA model used for the representation of a SISO nonlinear dynamical systems. The advantage obtained from using NARMA-L1 and NARMA-L2 models(More)
The NARMA model is an exact representation of the input-output behavior of finite-dimensional nonlinear discrete-time dynamical systems in a neighborhood of the equilibrium state. However, it is not convenient for purposes of adaptive control using neural networks due to its nonlinear dependence on the control input. Hence, quite often, approximate methods(More)
An attempt is made to indicate how practically viable controllers can be designed using neural networks, based on results in nonlinear control theory. The problem of stabilization of a dynamical system around an equilibrium point when the state of the system is accessible is considered. Simulation results are included to complement the theoretical(More)
For pt. I see ibid., vol. 4 (1993). This paper considers the problems of regulation and tracking of a dynamical system when the state variables of the dynamical system are not accessible. The existence of the nonlinear maps describing the identifier and controller are first established and the implications for neural network realizations are described.(More)
In this paper, adaptive control of a class of nonlinear discrete time dynamical systems with boundedness of all signals is established by using a linear robust adaptive controller and a neural network based nonlinear adaptive controller, and switching between them by a suitably defined switching law. The linear controller, when used alone, assures(More)