In this paper a new design method of a self-tuning PID controller is proposed. The PID controller is designed based on generalized predictive control (GPC) including a future reference trajectory. The PID controller given in this paper is based on GPC and, is I-PD type controller. It is shown that the design parameter adjusting the future reference trajectory changes only the integral time of t...

In this study, the self-tuning method for fuzzy PID controllers that has been developed in a previous study of the authors is implemented on PLC in order to control some standard processes formed on FEEDBACK PCS 327 Process Control Simulator. In this tuning method, the input scaling factor corresponding to the derivative coefficient and the output scaling factor corresponding to the integral co...

Despite the popularity of PID (Proportional-Integral-Derivative) controllers, their tuning aspect continues to present challenges for researches and plant operators. Various control design methodologies have been proposed in the literature, such as auto-tuning, self-tuning, and pattern recognition. The main drawback of these methodologies in the industrial environment is the number of tuning pa...

In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual out...

This paper studies the fuzzy PID controller design algorithm, and it has set up a hardware platform for the temperature control system thermal analyzer, respectively with MATLAB tools to conventional PID and fuzzy PID control method has carried on the simulation analysis, and in the actual building experiments have been carried out to test system platform. Experimental results show that the fuz...

Since the emergence of PID controllers, control system engineers are in pursuit of more and more sophisticated versions of these controllers to achieve better performance, particularly in situations where providing a control action to even a minimal degree of satisfaction is a problem. This work is an attempt to contribute in this field. Variations in the values of weight, the friction coeffici...

In adaptive control and system identification the self tuning regulator has wide range of applications. Neural network and artificial intelligence have big role in this area. This paper presents adaptive neural network control based on self tuning regulator (STR) scheme. The paper presents neural network block for on line system identification and discrete PID block controller. Analysis for the...

Nowadays the simplest and effective solutions to most of the control engineering applications are provided by PID controllers. However PID controllers are poorly tuned in practice with most of the tuning is done manually which is difficult and time consuming. This article comes up with new approaches of Fuzzy-IMC to design of PID controller for coupled water tank system at tank-1. The coupled w...

The performance optimization of induction motor speed control system is studied and self-tuning PID controller based on diagonal recurrent neural network (DRNN) is presented in this paper. Neural network control does not require the precise mathematical model of the system, and it only needs to train neural network online or offline, then use the training results to design the control system. I...