Neural Network-Based Adaptive Dynamic Surface Control for an Airbreathing Hypersonic Vehicle
This paper addresses the design of flight control system related to neural network-based adaptive dynamic surface control for the longitudinal motion of an airbreathing hypersonic vehicle. The control objective is to provide adaptive velocity and altitude tracking in the presence of the model uncertainties and unknown nonlinearities caused by changes of flight conditions. By approximating the unknown nonlinear functions by radial basis function networks, we incorporate the dynamic surface technique into a neural network based adaptive control design framework. The framework is adopted to design dynamic statefeedback controllers that provide stable tracking of velocity and altitude subsystems. Stability analysis shows that the control law can guarantee the uniformly ultimate boundedness of the solution of the closed-loop system and make the tracking error arbitrarily small.
Guangbin Cai Guangren Duan Changhua Hu
Center for Control Theory and Guidance Technology,Harbin Institute of Technology,Harbin 150001,China Center for Control Theory and Guidance Technology,Harbin Institute of Technology,Harbin 150001,China Unit 302,Xian Research Institute of High-Tech,Xian 710025,China
国际会议
哈尔滨
英文
575-580
2010-01-08（万方平台首次上网日期，不代表论文的发表时间）