Decoupling control for permanent magnet in-wheel motor using internal model control based on back-propagation neural network inverse system

• Autorzy: Li Y. , Zhang B. , Xu X.

Identyfikatory

DOI

10.24425/bpas.2018.125944

• Języki publikacji: EN

Abstrakty

EN

The permanent magnet in-wheel motor (PMIWM) is a nonlinear, multivariable, strongly coupled and highly complex system. The key to the development and application of the PMIWM consists in the improvement of its control accuracy and dynamic performance. In order to effectively decouple the PMIWM, this paper presents a novel internal model control (IMC) approach based on the back-propagation neural network inverse (BPNNI) control method. First, theoretical analysis is conducted to show the existence of the PMIWM inverse system, to be modeled mathematically. The inverse system approximated and identified by the back-propagation neural network (BPNN) constitutes the back-propagation neural network inverse (BPNNI) system. Then, by cascading the BPNNI system on the left side of the original PMIWM system, a new decoupling, pseudo-linear system is established. Moreover, the 2-DOF internal model control (IMC) method is employed to design the extra closed-loop controller that further improves disturbance rejection and robustness of the whole system. Consequently, the proposed decoupling control approach incorporates the advantages of both the BPNNI and the IMC. Effectiveness of thus proposed control approach is verified by means of simulation and real-time hardware-in-the-loop (HIL) experiments.

Słowa kluczowe

EN

electric vehicle; permanent magnet in-wheel motor; back-propagation neural network; inverse system; internal model control

PL

pojazd elektryczny; silnik z napędem na magnesy stałe; inwersja systemu; propagacja wsteczna; model odwrotny; system odwrotny

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2018
• Tom: Vol. 66, nr 6
• Strony: 961--972
• Opis fizyczny: Bibliogr. 50 poz., rys., wykr., tab.

Twórcy

autor

Li Y.

• Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, China
• School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, China

autor

Zhang B.

• School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, China

autor

Xu X.

• Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, China
• School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, 212013, China

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).