Neural networks find an application in a control system as a controller. When used in this manner, the neural network is said to be indirect neural control. In a conventional on/off control system the on and off
The program is user configurable and uses the Microsoft Chart object to trend data as the neural network is being trained in order to assist in the choice of network parameters such as number of iterations, learning rate, momentum rate etc....
The direct application of this framework to general network controllability problems is, however, complicated by several factors13. First, finding the minimum set of driver nodes for an arbitrary network is NP hard14. Second, the design of an appropriate control signal is not specified in ref. ...
In subject area: Physics and Astronomy A neural network is defined as a parallel processing network system that mimics the information processing capabilities of the human brain. It consists of interconnected neurons and can process numerical data, knowledge, thinking, learning, and memory. ...
In order to improve the performances of Switched Reluctance Motor Drive system and to solve the characteristic of discontinuity of variable structure control,a new control scheme based on sliding variable structure and network control is presented.It is applied in switched reluctance motor to control ...
in model predictive control is to determine the neural network plant model (system identification). Next, the plant model is used by the controller to predict future performance. (See the Model Predictive Control Toolbox™ documentation for complete coverage of the application of various model ...
a dual switching system model of network control system. Full size image Motivated by the above observations, the following questions have drawn our attention: (1) How to design an adaptive controller when both unmeasurable states and time-delay exist in a dual-switching nonlinear system? (2) ...
Application, Theoretical or Mathematical/ control engineering computing electronic engineering computing expert systems fuzzy logic neural nets position control power electronics/ neural network applications fuzzy logic applications expert system applications power electronics motion control artificial intelligence tools...
Fujii and Ura (1991) then used both supervised and non-supervised learning system to construct neural network based controller for AUVs and compared the results. After him ANN had been used in different controlling aspects like temperature control (Cui et al., 1992), process control (Lee et al...
A fuzzy neural network is basically a neural network where the inputs as well as the connection weights are fuzzy numbers. On the other hand, a neuro-fuzzy system is basically a FIS where the learning capability of ANN is used. Show moreView chapter Book 2011, Soft Computing in Textile En...