Synthesis and Verification of Finite-Time Rudder Control with GA Identification for Electric Rudder System

Zhihong Wu, Ruifeng Yang, Chenxia Guo, Shuangchao Ge and Xiaole Chen
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Zhihong Wu: Automatic Test Equipment and System Engineering Research Center of Shanxi Province, North University of China, Taiyuan 030051, China
Ruifeng Yang: Automatic Test Equipment and System Engineering Research Center of Shanxi Province, North University of China, Taiyuan 030051, China
Chenxia Guo: Automatic Test Equipment and System Engineering Research Center of Shanxi Province, North University of China, Taiyuan 030051, China
Shuangchao Ge: Automatic Test Equipment and System Engineering Research Center of Shanxi Province, North University of China, Taiyuan 030051, China
Xiaole Chen: Automatic Test Equipment and System Engineering Research Center of Shanxi Province, North University of China, Taiyuan 030051, China

Energies, 2020, vol. 13, issue 6, 1-18

Abstract: The electric rudder system (ERS) is the executive mechanism of the flight control system, which can make the missile complete the route correction according to the control command. The performance and quality of the ERS directly determine the dynamic quality of the flight control system. However, the transient and static characteristic of ERS is affected by the uncertainty of physical parameters caused by nonlinear factors. Therefore, the control strategy based on genetic algorithm (GA) identification method and finite-time rudder control (FTRC) theory is studied to improve the control accuracy and speed of the system. Differently from the existing methods, in this method, the difficulty of parameter uncertainty in the controller design is solved based on the ERS mathematical model parameter identification strategy. Besides, in this way, the performance of the FTRC controller was verified by cosimulation experiments based on automatic dynamic analysis of mechanical systems (ADAMS) (MSC software, Los Angeles, CA, USA) and matrix laboratory (MATLAB)/Simulink (MathWorks, Natick, MA, USA). In addition, the advantages of the proposed method are verified by comparing with the existing strategy results on the rudder test platform, indicating that the control accuracy is improved by 70% and the steady-state error is reduced by at least 50%.

Keywords: electric rudder system; finite time rudder control; genetic algorithm; parameter identification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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