Keywords
Self Tuning Regulator
System Identification
Neural Network
Neuro-Control
How to Cite
Abstract
In adaptive control and system identification the self-accuracy regulator has wide range of application Neural network and artificial intelligence are playing big role in this area This paper presents adaptive neural network control based on Self Tuning Regulator (STR) scheme. An On-line identification of process parameters is the key element in adaptive control, the basic idea of online identification is to compare the output of estimated system with the output of model during some time, and the model is describable as a parameter vector. The aim is to adjust parameter until the model output is similar to the observed system output. This paper presents neural network block for online system identification and discrete PID block controller. Modified Zeigler –Nichole method for designing PID controller has been presented and simulated using MATLAB. Analysis of the whole scheme is presented and simulated for different systems. Adequate desired performance is obtained by comparison with the nominal methods for using self-tuning regulator.
References
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