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In this paper, theoretical formulation and implementation results of an intelligent approach to develop a power system stabilizer are proposed. In this approach, a novel methodology that designs a hybrid controller with two algorithms, namely, a neural-network (NN)-based controller with explicit neuroidentifier and an adaptive controller that evolved from a model reference adaptive controller, is...
This paper presents a new adaptive predictive control algorithm which consists of an on-line process identification part and a predictive control strategy which is updated every time a process model change is identified. The identification method is based on recurrent neural network (RNN) nonlinear AutoRegressive with eXternal input (NARX) model derived from dynamic feedforward neural network by adding...
An extended control plant is introduced to substitute the plant used in ordinal adaptive cancellation system. All of the inputs and outputs of such an extended plant are online available and hence its model can be identified online conveniently. Based on the static nonlinear feedforward neural network model of this extended plant, a new adaptive cancellation system structure and algorithm are proposed...
In this work, a neural network (NN) based adaptive controller is developed and implemented for precise temperature control of a benchmark thermal system in cold climate. The newly devised NN controller is capable of overcoming the limitations of model dependent conventional fixed gain temperature controllers. The proposed NN controller is designed using the combination of off-line and on-line trainings...
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