TY - JOUR
T1 - MPC Inspired Dynamical Output Feedback and Adaptive Feedforward Control Applied to Piezo-Actuated Positioning Systems
AU - Nguyen, Manh Linh
AU - Chen, Xinkai
N1 - Funding Information:
Manuscript received September 24, 2018; revised January 14, 2019 and April 3, 2019; accepted April 23, 2019. Date of publication May 17, 2019; date of current version January 3, 2020. This work was supported by the Grants-in-Aid for Scientific Research of Japan Society for the Promotion of Science under Grant C-15K06152, Grant C-18K04212, and Grant 14032011-000073. (Corresponding authors: Manh Linh Nguyen and Xinkai Chen.) M. L. Nguyen is with the School of Electrical Engineering, Hanoi University of Science and Technology, Hanoi 112400, Vietnam (e-mail:, linh.nguyenmanh@hust.edu.vn).
Publisher Copyright:
© 1982-2012 IEEE.
PY - 2020/5
Y1 - 2020/5
N2 - It has been shown that the closed-loop transfer function representation of the unconstrained model predictive control (MPC) for single input single output systems is similar to a two-degree-of-freedom controller, which is capable of improving the tracking performance of positioning systems. Conventionally, the optimal parameters of the above-mentioned transfer function are result of a quite complicated MPC tuning. This paper proposes a new approach to obtain the parameters directly instead, where the input/output constraints are not considered. The method combines conventional feedback and adaptive feedforward techniques to minimize the tracking error as well as mitigate the influence of the load disturbance. Experiments on an ultra precision positioning system actuated by piezoelectric actuator show that the proposed method achieves much better tracking performance over a well-tuned conventional MPC.
AB - It has been shown that the closed-loop transfer function representation of the unconstrained model predictive control (MPC) for single input single output systems is similar to a two-degree-of-freedom controller, which is capable of improving the tracking performance of positioning systems. Conventionally, the optimal parameters of the above-mentioned transfer function are result of a quite complicated MPC tuning. This paper proposes a new approach to obtain the parameters directly instead, where the input/output constraints are not considered. The method combines conventional feedback and adaptive feedforward techniques to minimize the tracking error as well as mitigate the influence of the load disturbance. Experiments on an ultra precision positioning system actuated by piezoelectric actuator show that the proposed method achieves much better tracking performance over a well-tuned conventional MPC.
KW - Model predictive control (MPC)
KW - proportional-integral-differential (PID)
KW - two-degree-of-freedom controller
KW - zero phase error tracking control
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U2 - 10.1109/TIE.2019.2916356
DO - 10.1109/TIE.2019.2916356
M3 - Article
AN - SCOPUS:85072812762
SN - 0278-0046
VL - 67
SP - 3921
EP - 3931
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
IS - 5
M1 - 8718028
ER -