Governed by: Ministry of Industry and Information Technology of the People's Republic of China
Sponsored by: Northwestern Polytechnical University  Chinese Society Aeronautics and Astronautics
Address: Aviation Building,Youyi Campus, Northwestern Polytechnical University
Research on H∞ Adaptive Control of Aero-engine Based on RBF Neural Network Compensation
Author:
Affiliation:

Aircraft Engineering College,Nanchang Hang Kong University

Clc Number:

V235.13

Fund Project:

Double Thousand Plan of Jiangxi Province (jxsq2018106057)

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    Abstract:

    Aero-engine control system is an important system of aircraft, the uncertainties of control gain attenuation and unmodeled dynamics of aero-engine affect control performance, therefore, a controller combining H∞ adaptive control and compensation control is designed in this paper. Firstly, the H∞ adaptive controller is designed based on the mixed sensitivity theory. Then, based on Lyapunov strict stability theory, the RBF neural network compensation controller was designed to compensate the uncertainty, and the fitting speed was adjusted by the linear function related to the error. Finally, the aeroengine is taken as the controlled object to carry out multi-variable simulation test. The results show that the controller in this paper can effectively compensate the uncertainty and reduce the overshoot and adjusting time compared with the H∞ controller.

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Xue Hong yang, Cai Kai long, Li Huang qi, Pu Zhi gang. Research on H∞ Adaptive Control of Aero-engine Based on RBF Neural Network Compensation[J]. Advances in Aeronautical Science and Engineering,2023,14(1):128-134

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History
  • Received:February 28,2022
  • Revised:May 08,2022
  • Adopted:May 10,2022
  • Online: December 15,2022
  • Published: