NEURO MODELING AND CONTROL STRATEGIES FOR A pH PROCESS

The local linear model tree (LOLIMOT) and neuro-fuzzy systems approaches like ANFIS were used to obtain the direct and inverse models of the nonlinear pH process.. This network was

In this study, a predictive controller using a feed- forward neural network with online adaptation of the parameters was used in the temperature control of a batch process for

In this paper, the adaptive neural network sliding mode controller proposed to control a DC motor, so we compare proposed controller with PID, classic SMC and

This is where the neural network comes into play: The neural network is now facilitated to the workings of the function f in (14) to obtain the predictions y ˆ N .Now

In this paper, two models: regression based model and neural network based model for predicting productivity performance index for construction firms are

With an appropriately designed control scheme with PI and ANN with Hysteresis controller then incorporated, the nine-switch converter is shown to favorably raise the

In this paper, a robust neural network global sliding mode PID-controller is proposed to control a robot manipulator with parameter variations and external disturbances.. In

Abstract: This is a practical approach to control a continuous-time process variable (temperature) using a discrete controller (PLC) and a custom-designed software control