Attack angle tracking for high speed vehicle based on variable structure and Taylor type FLNN neural network

Issue title: Special Section: Recent Advances in Machine Learning and Soft Computing

Guest editors: Srikanta Patnaik

Article type: Research Article

Authors: Song, Chuang^a | Lei, Junwei^{b; *} | Wu, Huali^b

Affiliations: [a] Beijing Electro-mechanical Engineering Institute, Beijing, China | [b] Department of Control Engineering, Naval Aeronautical and Astronautical University, Yantai, Shangdong, China

Correspondence: [*] Corresponding author. Junwei Lei, Department of Control Engineering, Naval Aeronautical and Astronautical University, Yantai, Shangdong 264001, China. E-mail: leijunwei@126.com.

Abstract: Considering the fast time varying characteristic of pitch channel model of hypersonic model with coupling of engine, a kind of hybrid attack angle tracking controller is designed based on variable structure and Taylor type FLNN neural network method. And the adoption of variable structure control method make the system response very fast and robust. The Taylor type FLNN neural network is constructed with the format of fitting function which is used to describe the force and moment caused by attack angle, so it can compensate the interruption caused by the uncertainty and unconsidered factors effectively. At last, detailed numerical simulation is done to testify the rightness of the proposed hybrid method.

Keywords: Variable structure control, hypersonic aircraft, neural network, adaptive, stability

DOI: 10.3233/JIFS-169587

Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 1, pp. 283-291, 2018