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This edited volume begins with a foreword by Vera John-Steiner; has the obligatory introduction; and consists of a sequenced, diverse, collection of essays focusing on the use of dramatic interacti...
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Jan T. Białasiewicz, Julio C. Proano, Edward T. Wall
It is shown that the neural network can be used as a state estimator in a model-reference intelligent control system. Its learning capability and noise rejection characteristic are illustrated by the results of a simulation study. The implementation of the state estimator …
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T.T. Ho, Hai T. Ho, Jan T. Białasiewicz, Edward T. Wall
A stochastic neural direct adaptive control algorithm for partially known state-space nonlinear time-varying plants is presented. A neural network is used to generate the control signal, which optimizes a quadratic (one-step-ahead prediction) performance index. In comparison to conventional stochastic state-space adaptive control, …
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Margaret K. Farish, Bruce Eilers, Edward T. Wall
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Donald Mackison, Edward T. Wall
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Julio C. Proano, Jan T. Białasiewicz, Edward T. Wall
Precision adaptive control has been accomplished using a neural network to generate the required system dynamics, given the desired input and output.That is, an artificial neural network has been designed and incorporated into an adaptive control system to function as a synthesizer …
Alexandros J. Ampsefidis, Jan T. Białasiewicz, Edward T. Wall
using partial a priori information
T.T. Ho, Shine Tzong HO, Jan T. Białasiewicz, Edward T. Wall
An attempt is made to contribute to the unification of traditional state space adaptive control and neural system theory. A stochastic neural adaptive control algorithm, where the system identification is based on the state space innovations model, which employs a neural network …
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The construction of port facilities in deep water, several miles seaward from the nations's coastline, is one of the measures that have been suggested for reducing oil tanker accidents. This paper briefly describes the issues associated with such ports (referred to as …
A generalized stochastic state space adaptive control algorithm which combines system identification based on minimum variance, Newton, and gradient search approaches, with an original control law derived from a per-interval performance index. This unique approach results in superior accuracy and performance. The …
Jamil M. Bakhashwain, Edward T. Wall
Sebastian Kraft, Edward T. Wall
The performance characteristics of a representative adaptive position control system were investigated using a single-board microprocessor-based controller and a DC motor actuator. The adaptive controller algorithm is capable of compensating for some Coulomb friction effects and will adapt to changes in the …
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