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This paper proposes a new nonlinear neural controller with a neural Smith predictor for time-delay compensation of nonlinear processes.
Abstract. This paper proposes a new nonlinear neural controller with a neural Smith predictor for time-delay compensation of nonlinear processes.
In this strategy, a dynamic neural network based nonlinear Smith predictor is constructed to compensate for the effect of time-delay of a class of nonlinear ...
This paper presents a work in progress concerning the use of neuro-fuzzy based non-linear Smith predictor for control a real system with a large and variant ...
Missing: Nonlinear | Show results with:Nonlinear
In this strategy, a dynamic neural network based nonlinear Smith predictor is constructed to compensate for the effect of time-delay of a class of nonlinear.
The proposed nonlinear predictive controller and its variations use neural networks to online estimate the dynamics of the slave and environment allowing ...
A dynamic neural network based nonlinear Smith predictor is constructed to compensate for the effect of time-delay of a class of nonlinear processes to ...
An extension of the Smith predictor principle to the nonlinear case is proposed. This nonlinear predictor can be constructed using neural networks.
The remote controller is a modified Smith predictor that provides prediction and maintains the desired tracking performance; an extra robustifying term is ...
Results of simulations show that NCS using the Neural-Smith predictor has better performance in comparison to the common Smith predictor and the novel ...