Abstract
In the industrial process, there is a type of production load that changes with the process and the environment control system. In this paper, an adaptive fuzzy PID algorithm control scheme was proposed and verified when we took the heat exchanger as an example. We have analyzed the problems existing in the dynamic adjustment process of fixed parameter mechanism adopted by traditional incremental PID under complex working conditions, and studied a control scheme combining adaptive fuzzy controller with traditional PID controller. Based on the PCS7 (one advanced process control system designed by SIEMENS), we designed two control loops. One is traditional PID and another is adaptive fuzzy PID. After that the control system proposed was simulated on an advanced process control system named SMPT-1000. To find out the performance of the adaptive fuzzy controller, one experiment by using three conditions, normal control, disturbance control and load change control, has been carried out. The results show that the adaptive fuzzy PID controller has excellent performance and robustness compared with the traditional PID and the fuzzy controller is especially suitable for complex time-delay systems.
Project of middle-aged and young backbone teachers of CDUT (KYGG201513). Self-determined Project of SKLGP (SKLGP2014Z013).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Roy, P., Roy, B.K.: Fractional order PI control applied to level control in coupled two tank MIMO system with experimental validation. Control Eng. Pract. 48, 119–135 (2016)
Li, Z., Xiao, D.: A fuzzy adaptive PID controller based on neural network. Control Decis. 3, 340–345 (1996)
Wang, Y.-G., Xu, X.-M.: Adaptive and optimal PI controller with robustness. Acta Autom. Sin. 35(10), 1352–1356 (2009)
Yang, X.-J.: The design of intelligent PID controller based on fuzzy theory. Manuf. Autom. 35(3), 115–117 (2013)
Zou, T., Sun, H.-J., Zhang, X., et al.: An implementation of split control strategy for multi-variable predictive control. Control Decis. 32(4), 746–750 (2017)
Cherrat, N., Boubertakh, H., Arioui, H.: An adaptive fuzzy PID control for a class of uncertain nonlinear underactuated systems. In: International Conference on Modelling, Identification and Control. IEEE, pp. 677–682 (2017)
Ji, H., Tian, M.: Analysis and Calculation of Shell and Tube Heat Exchanger. Science Press (1996)
Yu, L.: Engineering Fluid Mechanics. China Machine Press (2015)
Ding, D.-J., Wang, Y.-G.: Modeling in frequency domain and controller parameter tuning for industrial processes. Control Eng. China 23(11), 1714–1718 (2016)
Mahapatro, S.R., Subudhi, B., Ghosh, S.: Adaptive fuzzy PI controller design for coupled tank system: an experimental validation. IFAC Proc. Vol. 47(1), 878–881 (2014)
Wang, H., Zhao, S., Gu, J.: Development and application of fuzzy adaptive PID function block based on SCL. Ind. Control Comput. 25(2), 73–74 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, H., Meng, L., Wang, X., Nie, D. (2019). One Temperature Control Method of Heat Exchanger Using Adaptive Fuzzy PID Theory. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 869. Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_47
Download citation
DOI: https://doi.org/10.1007/978-3-030-01057-7_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01056-0
Online ISBN: 978-3-030-01057-7
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)