Received: 05-08-2021
Accepted: 29-10-2021
DOI:
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Design the Optimal Controller for Cascade Control Systems Based on Experiment Data using Virtual Reference Feedback TuningApproach
,
Le Vu Quan
1
,
Vu Thi Thu Giang
2
Keywords
Optimal control, Data-driven control, cascade control systems, virtual reference feedback tuning
Abstract
The paper introduces the method of designing optimal controllers for cascade control systems based on data obtained from an experiment, which is the Virtual Reference Feedback Tuning (VRFT) method. A special feature of this approach, a mathematical model of the actual plants is not required, only a data set achieved from the experiment is needed for acquiring the inner and outer controllers in cascade control systems. In this study, by using the VRFT method, we will achieve optimal inner and outer controllers of the cascade control system. Using these optimal controllers, the purpose of the control problem will be achieved such as the output of the cascade control system will be close to the desired output. The Matlab software is used for simulation, the simulation results show that with the achieved optimal controllers, the output of the cascade control system is asymptotic to the expected output.
References
Anagha (2014). Cascade speed control of DC motor. International Journal of Electrical, Electronics and data communication. 2(6):78-81.
Bhavina R. (2013). Cascade control of DC motor with advance controller.International Journalof Industrial Electronics and Electrical Engineering. 1(1): 18-20.
Campi M.C., Lecchini A. & Savaresi M.S. (2002). Virtual reference feedback tuning : a direct method for the design of feedback controllers. Automatica Magazine. 38(8): 1337-1346.
Hansen N. (2011). The CMA Evolution Strategy, A Tutorial. Retrieved from http://www.lri.fr/hansen/cmatutorial.pdfon August15, 2021.
Yin Q.C., Wang T.H., Sun Q. & Zhao L.(2019). Improved Cascade Control System for a Class of Unstable Processes with Time Delay. International Journal of Control, Automation and Systems. 17(1): 126-135.