Fuzzy-PID controller based on variable universe for main steam temperature system

ABSTRACT

The high inertia and long delay characteristics of main steam temperature control system in the thermal power plants will reduce the system control performance. In order to improve the control performance, a Fuzzy-PID control strategy based on variable universe for main steam temperature system is proposed. Variable universe method is adopted to solve the local parameters self-regulation optimisation problem of conventional PID controller. Variable universe guarantees that the parameters of the system are global optimal. It solves the problem that the fuzzy controller cannot guarantee the high accuracy under the given rules. The scale factor is chosen according to fuzzy rules. The advantages of variable universe and Fuzzy-PID are combined. Fuzzy-PID controller based on variable universe is established. Compared with other control methods, the simulation experiments are carried out. Simulation results show that Fuzzy-PID controller based on variable universe has faster response speed, smaller overshoot and error, better tracking performance and reduces the lag effect of the control system.

KEYWORDS:

• Main steam temperature
• Fuzzy Proportional-Integral-Differential (Fuzzy-PID)
• scale factor
• variable universe

Acknowledgements

This work is partially supported by the Science Research Project of Liaoning Education Department: [Grant Number LGD2016009], the Key Project of Natural Science Foundation of Liaoning Province of China: [Grant Number 20170540686] and National Key R&D Program of China: [Grant Number 2016YFD0700104-02].

Additional information

Funding

This work was supported by the Science Research Project of Liaoning Education Department: [Grant Number LGD2016009] and the Key Project of Natural Science Foundation of Liaoning Province of China: [Grant Number 20170540686].

Notes on contributors

Zhongda Tian

Zhongda Tian He received the Ph. D degree in Control Theory and Control Engineering from Northeastern University, China in 2013. He is currently an Associate Professor in College of Information Science and Engineering, Shenyang University of Technology, China. His research interests include predictive control, delay compensation and scheduling for networked control system, time series prediction. 

Yi Ren

Yi Ren He received his B. Eng degree from Liaoning University of Science and Technology in 2016. He is currently a Master student of Control Theory and Control Engineering, College of Information Science and Engineering, Shenyang University of Technology, China. His interests mainly include time series prediction.

Gang Wang

Gang Wang He received his B. Eng degree from Shanxi Datong University in 2016. He is currently a Master student of Control Theory and Control Engineering, College of Information Science and Engineering, Shenyang University of Technology, China. His interests mainly include time series modeling and forecasting.