Simple PID Controller Tuning Method for Processes with Inverse Response Plus Dead Time or Large Overshoot Response Plus Dead Time

2003 ◽  
Vol 42 (20) ◽  
pp. 4461-4477 ◽  
Author(s):  
I-Lung Chien ◽  
Yu-Cheng Chung ◽  
Bo-Shuo Chen ◽  
Cheng-Yuan Chuang
Keyword(s):  
Pid Controller ◽  
Dead Time ◽  
Controller Tuning ◽  
Tuning Method ◽  
Pid Controller Tuning ◽  
Inverse Response

A new PID controller tuning method based on multiple integrations

1999 ◽  
Vol 7 (5) ◽  
pp. 623-633 ◽  
Author(s):  
Damir Vrančić ◽  
Youbin Peng ◽  
Stanko Strmčnik
Keyword(s):  
Pid Controller ◽  
Controller Tuning ◽  
Tuning Method ◽  
Pid Controller Tuning

Digital Twin-Driven Controller Tuning Method for Dynamics

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Bin He ◽  
Tengyu Li ◽  
Jinglong Xiao
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Parameter Tuning ◽  
Control Effect ◽  
Controller Tuning ◽  
Digital Twin ◽  
Tuning Method ◽  
Twin Model ◽  
Pid Controller Tuning ◽  
Self Tuning

Abstract The control performance of the control system directly affects the running performance of the product. In order to solve the problem that the dynamics characteristics of mechanical systems are affected by the performance degradation of the controller, a digital twin-driven proportion integration differentiation (PID) controller tuning method for dynamics is proposed. In this paper, first, the structure and operation mechanism of the digital twin model for PID controller tuning are described. Using the advantages of virtual real mapping and data fusion of the digital twin model, combined with the online identification of the controlled object model, the problems of real-time feedback of an actual control effect of the controller and the unreal virtual model of the control system caused by time-varying working conditions are effectively solved, and the closed-loop self-tuning of PID controller is realized. At the same time, intelligent optimization algorithm is integrated to improve the efficiency and accuracy of PID controller parameter tuning. Second, the modeling method of the digital twin model is described from three aspects of physical prototyping, twin service system, and virtual prototyping. Finally, the controller tuning for gear transmission stability is taken as an example to verify the practicability of the proposed method.

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