Adaptive network controller

Strang. G., Wavelets and dilation equations A brief introduction. SIAM Rev. 31, 614 (1989). Ungar, L. H., Powell, B. A., and Kamens, S. N., Adaptive Networks for fault diagnosis and process control. Comput. Chem. Eng. 14, 561 (1990). 

Model-Free Adaptive and Artificial Neural Network Control... 

In this paper we describe the application of an adaptive network based fuzzy inference system (ANFIS) predictor to the estimation of the product compositions in a binary methanol-water continuous distillation column from available on-line temperature measurements. This soft sensor is then applied to train an ANFIS model so that a GA performs the searching for the optimal dual control law applied to the distillation column. The performance of the developed ANFIS estimator is further tested by observing the performance of the ANFIS based control system for both set point tracking and disturbance rejection cases. 

Meggers, J. Adaptive admission control and scheduling for wireless packet communication. In Proceedings of the IEEE International Conference on Networks (ICON 99), Brisbane, Australia, IEEE Computer Society Press, Los Alamitos (1999)... 

Neural networks have also been used in model reference adaptive control (MRAC) structures (Figure 12.4) [Naranedra and Parthasarathy, 1990 Narendra, 1992]. This approach builds upon established techniques for adaptive linear control and incorporates neural networks to address the problem of controlling nonlinear systems. The MRAC approach is directed at adapting the controlled system such... 

A biomedical control system that utilizes a neurophysiologically-based approach has been developed for use in Functional Neuromuscular Stimulation (FNS) systems [Abbas, 1995 Abbas and Chizeck, 1995). FNS is a rehabilitation engineering technique that uses computer-controlled electrical stimuli to activate paralyzed muscle. The task of a control system is to determine appropriate stimulation levels to generate a given movement or posture. The neural network control system utilizes a block diagram structure that is based on hierarchical models of the locomotor control system. It also utilizes a heterogenous network of neurons, some of which are capable of endogenous oscillation. This network has been shown to provide rapid adaptation of the control system parameters [Abbas and Chizeck, 1995 Abbas and Triolo, 1997] and has been shown to exhibit modulation of reflex responses [Abbas, 1995]. 

Cheng-Jian L, Chin-Teng L (1997) An art-based fuzzy adaptive learning control network IEEE Trans Fuzzy Syst 5(4) 477 96... 

Choi, T., Dooley, K., Rungtusanatham, M. (2001). Supply networks and complex adaptive systems Control versus emergence. Journal ( Operations Management, 19, 351-366. 

Ydstie, B. E., Forecasting and control using adaptive coimectionist networks. Comput. Chem. Eng. 14, 583 (1990). 

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