Zuriati Janin

PID controller tuning for glycerin bleaching process using well-known tuning formulas- a simulation study

This paper presents a simulation study on PID controller tuning for glycerin bleaching process. The tuning was based on Ziegler-Nichols (Z-N), Cohen-Coon, Internal Model Controller (IMC), Integral of Absolute Error (IAE), Integral of Square Error (ISE) and Integral Time-Weight absolute Error (ITAE) methods. The control performance of each method was evaluated in term of percent overshoot, settling time and rise time. The simulated controller parameters were verified by testing on the actual plant using field instrument module and LabVIEW as interfacing system. The results revealed that the process was best tune using ITAE technique.

Process controllability for flow control system using Ziegler-Nichols (ZN), Cohen-Coon (CC) and Chien-Hrones-Reswick (CHR) tuning methods

The controllability of the process depends on the values need to be chosen for the proportional, integral and derivative constants. The value of proportional, integral and derivative can be estimated using various tuning method. The purpose of this study is to compare the performance of various proportional, integral and derivative controller tuning methods for flow control system. A Tangent Method and Reformulation Tangent Method were compared in this paper to perform the open-loop test. From the open-loop test, the value of response rate, dead time and time constant were obtained. The controller parameters from open-loop test were used in tuning rule to get the optimum value of proportional, integral and derivative gains. The tuning methods used in this paper were Ziegler-Nichols, Cohen-Coon and Chien-Hrones-Reswick. Performance comparison and analysis of the three proportional, integral and derivative tuning were based on percent overshoot, settling time, rise time and integral absolute error. The fine tuning technique has used to improve the result which the value of proportional and integral gains were tuned. The result showed that Ziegler-Nichols and Chien-Hrones-Reswick tuning methods provided better performance compared to CC tuning method.

Temperature control tuning for overdamped process response

The main objective of this study is to determine the optimum tuning of temperature process control for overdamped process response. The Ziegler Nichols tuning was used to determine the optimum setting of temperature process control in 30°C – 50°C by varying the PB and I term. The performance of the response is evaluated based on integral absolute error (IAE), settling time (Ts), and rise time (Tr), first overshoot and undershoot.

Application of Fuzzy Logic Controller for glycerin bleaching process

This paper describes the development of Fuzzy Logic Controller (FLC) for a glycerin bleaching process based on simulation study. The first order plus dead time (FPODT) model of the glycerin bleaching temperature is obtained using open loop step test from a glycerin bleaching pilot plant. Fuzzy PI and Fuzzy PD controller was developed to replace the existing PID controller. The performances of the controllers are measured and compared with conventional PID controller. The result shows the fuzzy logic controllers performed much better compared with a PID controller in controlling glycerin bleaching temperature.

Process controllability for air temperature oven system using open-loop Reformulated Tangent Method

This paper presents the effect of various control tuning methods to the controllability of air temperature oven system. The simplest open loop test on actual plant has been performed using a Reformulated Tangent Method (RTM). Three PID tuning rules namely Ziegler Nichols (Z-N), Cohen Coon (C-C), and Chien, Hrones & Reswick (CHR) are used in this work. The plant is connected to Distributed Control System (DCS). The performance of these control tuning rules are evaluated in term of their closed loop characteristics such as percent overshoot (% OS), settling time (Ts), rise time (Tr) and integral absolute error (IAE). The results of this study showed that Cohen-Coon tuning method give best performance to the controllability of air temperature oven system as compared to the other rules.

Application of Fuzzy PD controller with Smith Predictor for glycerin bleaching temperature control

Controlling a temperature for a large system is not an easy task, the lag is big and the overshoot is high. The conventional method of controlling this kind of process is not capable of giving satisfactory result. In this paper the implementation of Fuzzy Logic controller with Smith Predictor is an alternative to control this system. First order plus dead time model (FOPDT) is used for simulation. Fuzzy PD with Smith Predictor is developed using 3 (Fuzzy PD3-SP), 5 (Fuzzy PD5-SP) and 7 (Fuzzy PD7-SP) membership functions. With advantages of Smith Predictor and Fuzzy Logic Controller the purposed control structure is found better compared with conventional PID controller with Smith Predictor for controlling glycerin bleaching temperature.

Self Tuning Fuzzy Logic controller with Smith structure for controlling glycerin bleaching temperature

Controlling process with lag is not an easy task. The lag can easily cause oscillation that lead to instability of the controller response. The conventional method of controlling this kind of system is not capable of giving satisfactory result. Many delay compensator and predictor methods are introduced to handle system with lag and one of the popular methods is a Smith Predictor. The problem with model base control structure is the mismatch or inaccurate model used as a predictor. This work introduced a Self Tuning Fuzzy Logic controller as an alternative method to solve a process with mismatch delays problem. With advantages of Smith Predictor and Self Tuning Fuzzy Logic Controller the purpose control structure is found giving better performance compare with conventional Fuzzy Logic controller with Smith Predictor Structure.

Various PID controller tuning for air temperature oven system

Temperature controllers are needed in any situation requiring a given temperature be kept stable. This can be in a situation where an object is required to be heated, cooled or both and to remain at the desired temperature, regardless of the changing environment around it. The purpose of this study is to compare the performance of three controller tuning methods for an air oven temperature control system. The controller parameters, response rate and dead time are determined by using Reformulated Tangent Method in open-loop test. Then, the optimum Proportional-Integral-Derivative value are determined by using Ziegler-Nichols, Chien et al. and Takahashi tuning methods. The performance of each tuning rule is analyzed in the closed-loop characteristics such as percent overshoot, setting time, rise time and integral absolute error. The fine tuning technique was implemented to improve the result which the value of Proportional-Integral-Derivative gains were tuned. The result presented that the Ziegler-Nichols tuning method give better performance compared to Chien et al. and Takahashi tuning methods.

PID control structure for glycerin bleaching process: A comparative study

This paper is to investigate the best PID control structure for controlling the glycerin bleaching process that would improve the bleached glycerin quality. An ideal and alternative PID control structures is analyzed. The controller parameters are adjusted based on Wangs tuning method and compared to Ziegler-Nichols method. The system performance is evaluated in terms of settling time and percent overshoot. The results showed that the glycerin bleaching process control can best achieve using alternative PID control structure with Ziegler-Nichols tuning.

Fuzzy Logic controller for glycerin bleaching temperature control

Controlling a process with significant lag is always a challenge task. The response is slow and can cause instability of the controller. In this work the Fuzzy Logic controller is purposed to control the heating stage for glycerin bleaching process. The Fuzzy PD and Fuzzy PI controllers are designed with different sets of membership function and rules. 3, 5 and 7 membership functions with 9, 25 and 49 rules are compared and evaluated to find the suitable set for this application. It was found that the implementation of Fuzzy Logic controller with 25 rules is sufficient to give good control for glycerin bleaching heating process.