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Integrated 3‐D Flight Trajectory Tracking Control with Aerodynamic Constraints on Attitude and control Surfaces
Author(s) -
Wang Xueyuan,
Fang Hao,
Dou Lihua,
Chen Jie,
Xin Bin
Publication year - 2018
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1696
Subject(s) - control theory (sociology) , backstepping , aerodynamics , trajectory , lyapunov function , aerodynamic force , lyapunov stability , bounded function , computer science , actuator , adaptive control , mathematics , engineering , control (management) , nonlinear system , artificial intelligence , mathematical analysis , physics , astronomy , quantum mechanics , aerospace engineering
In this paper, a new 3‐D trajectory tracking problem for an uncertain high fidelity six‐degree‐of‐freedom (6‐DOF) aerodynamic system is considered. Instead of designing controllers for each subsystem separately, an integrated trajectory tracking control algorithm is proposed to exploit beneficial relationships among interacting subsystems. The high‐order aerodynamic model is first transformed into a quasi‐strict‐feedback form. Then, backstepping technique is utilized to resolve the coupling effect problem of three control channels resulting from the bank‐to‐turn (BTT) control mode. In addition, command filters are introduced to handle state and actuator constraints caused by the physical limitations and the coordinated turn requirement. Furthermore, the uncertain aerodynamic force and moment coefficients are reconstructed by using the B‐spline neural network approximation and adaptive learning approaches. With Lyapunov stability analysis, all the states in the closed‐loop system are shown to be semi‐globally uniformly ultimately bounded (SUUB), and the tracking errors will asymptotically converge into a small compact set around zero by properly adjusting the control parameters. Finally, numerical simulations are conducted to demonstrate the effectiveness of the proposed algorithm.