A long range predictive pid controller with application to an industrial chemical process

Author(s):  
R.M. Miller ◽  
A. Uda ◽  
S.L. Shah ◽  
R.K. Wood
1996 ◽  
Vol 22 (1) ◽  
pp. 150-155
Author(s):  
Yoshitomo Hanakuma ◽  
Kazutoyo Nakaya ◽  
Takeshi Takeuchi ◽  
Takashi Sasaki ◽  
Eiji Nakanishi

Author(s):  
Oladimeji Ibrahim ◽  
Sulyman A. Y. Amuda ◽  
Olatunji O. Mohammed ◽  
Ganiyu A. Kareem

Accurate tuning of controller in industrial process operation is prerequisite to system smooth operation which directly reduce process variability, improved efficiency, reduced energy costs, and increased production rates. Performance evaluation of a model based PID controller tuning algorithm on a chemical process plant is presented in this paper. The control action of three different PID controller tuning algorithms namely; Hagglund-Astrom, Cohen and Coon, and Ziegler-Nichols on the process plant was examined in a closed loop control configuration under normal operating condition and in the face of disturbance. LabVIEW software was used to model a chemical process plant from open loop control test data. The time domain response analysis of the controllers shows that each tuning algorithm exhibit different time response. Ziegler-Nichols algorithm shows the best performance with fastest rise time, settling time and was able to restore the system back to normal operating condition in a short time when subjected to disturbance compare to Cohen & Coon controller and Hagglund-Astrom algorithm settings.


2011 ◽  
Vol 87 ◽  
pp. 123-128 ◽  
Author(s):  
Li Ting Sun ◽  
Jing Shu Wang ◽  
Zhong Qing Han ◽  
Chang An Zhu

Vibration is a significant factor that influences the performance of the long-range ultra-precise positioning system. Due to the intense nonlinearity and parameter uncertainties, it is difficult to eliminate the vibration by using a conventional PID controller. In this paper, the intelligent PID controller based on BP neural network with the ability of self-learning and strong robustness is introduced into the positioning system. Simulation and experiment are conducted and the results show that the vibration is effectively suppressed and the positioning accuracy has reached within 5.8nm.


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