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2002•Unpublished venueRequires access

Nonlinear Control Systems Based on NN Internal Model

Jun Zhou

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Abstract

In this article, the authors introduce a method of controlling certain types of nonlinear dynamical systems whose dynamics can be modelled by a multilayer BP neural network. A PID controller is added to improve the IMC controller .Simulation results demonstrate that the efficiency of BP network is like an IMC method. The controller is of the faster and better tracking performance than that of the conventional controller.

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What this paper is about

In this article, the authors introduce a method of controlling certain types of nonlinear dynamical systems whose dynamics can be modelled by a multilayer BP neural network. A PID controller is added to improve the IMC controller .Simulation results demonstrate that the efficiency of BP network is like an IMC method. The controller is of the faster and better tracking performance than that of the conventional controller.

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Available abstract

In this article, the authors introduce a method of controlling certain types of nonlinear dynamical systems whose dynamics can be modelled by a multilayer BP neural network. A PID controller is added to improve the IMC controller .Simulation results demonstrate that the efficiency of BP network is like an IMC method. The controller is of the faster and better tracking performance than that of the conventional controller.

Key concepts: Internal model, Control theory (sociology), Nonlinear system, Controller (irrigation), PID controller, Artificial neural network, Control engineering, Computer science

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