Revamping of PID Controller via Artificial Intelligent Technique
Keywords:
Neural network, PID controller, Mat-lab, ANN,BNN.Abstract
There are comparative advantages derived from the revamped proportional integral derivative PID Controller using Neural Network over the traditional controller. A few of them include increase in precision, cutback in time and uncomplicated hardware implementation. Ultimately, these advantages improve the control system in our industries. This paper recommends a non-linear control of stochastic differential equation to Neural Network matching. There was a validation, evaluation and comparison with other existing controllers. The essence is to get control systems suitable enough to achieve efficiency and improve on the performance of the traditional control systems. It is also to have control systems that reduce wastage and be more elastic in the level of conversion. More so, the initiative is to produce control systems that are competent in tracking set point change and discard load disturbance in our production industries. This paper is groundwork to devise a basic neural network and proportional integral derivative PID control system to model its operational distinctiveness for a class of straightforward process. Eventually, we recorded a laudable outcome by revamping the proportional integral derivative PID controller with Neural Network technique. The plant process control was also connected and the unique characteristics of the traditional proportional integral derivative PID were maintained. There was also an enhancement of PID controller. Finally, a rewarding result was recorded as the loss due to wastage encored by the process industries condensed significantly
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