一种高超音速飞行器轨迹线性化控制方法研究

Research on Trajectory Linearization Control Method for Hypersonic Vehicle

研究一种新的非线性控制结构。针对强非线性和不确定性高超音速飞行器,对跟踪性能和鲁棒性提出更高要求的特点,内环快回路通过动态逆的方法来设计,保证飞行器的性能,外环慢回路用轨迹线性化的方法进行跟踪控制;并提出了一种基于小脑模型关节控制器(Cerebellar Model Articulation Controller,CMAC)的神经网络自适应逆控制策略以提高系统的鲁棒性,对算法收敛条件和控制器稳定性进行了证明。最后利用改进设计方案在高超音速飞行条件下进行仿真验证。仿真结果表明整个控制系统具有很好的跟踪性能和鲁棒性。

Hypersonic vehicles have the characteristics of non - linear and uncertain and these make a higher demand for tracking performance and robustness. A new control structure based on trajectory linearization control （TLC） method and dynamic inversion technology was proposed. The dynamic inversion was designed to ensure aircraft performance for fast inner loop while trajectory linearization method is used for tracking control at slow outer loop design. However, inherent uncertainties may render it useless. In this paper, a Cerebellar Model Articulation Controller （CMAC） neural network was used to improve overall system performance of robust tracking control. The algorithm convergence condition and controller stability were proved. Finally, the flight control system of the hypersonic vehicle was designed based on the proposed method, and the simulation results demonstrate the excellent performance and robustness of the controllers.