基于小波网络的高超音速飞行器鲁棒自适应积分反步控制

Robust Adaptive Integrator Backstepping Control Based on Wavelet Network for A Hypersonic Vehicle

针对高超音速飞行器非线性模型具有不确定性的问题,提出一种基于小波网络的鲁棒自适应积分反步控制方法。该方法运用反步法设计非线性控制律,并引入积分项以减小系统跟踪误差;用小波网络在线逼近系统不确定项,提高系统鲁棒性;设计鲁棒项消除小波网络逼近误差。通过Lyapunov稳定性分析,该方法能够保证闭环系统跟踪误差最终收敛。通过与常规反步、积分反步、自适应反步进行仿真对比,结果表明:所设计的控制律可以有效抑制系统不确定性的影响,设计方法可行。

To solve the control problem of a general hypersonic vehicle, which is a complex nonlinear uncertain system, a robust adaptive integrator backsetpping control strategy based on wavelet neural network is proposed. Integrator is used to decrease tracking error of the system. The system asymptotically tracks the desired output by means of on -line studying uncertainties and the derivative of virtual item via wavelet neural network, so robustness is en- hanced. Robust items are designed to eliminate approximate error of the wavelet network. Theoretical analysis is done to validate Lyapunov stability of the system. The simulation results show that the developed method is effective and can be used to deal with the problem of uncertain parameters preferably.