为解决折叠翼飞行器在发射段各项特性变化较大、对飞行控制律鲁棒性要求较高的问题,设计了一种以块控反步法为基础的自适应鲁棒非线性控制器。在发射段动态模型基础上,该控制器采用径向基函数(RBF)神经网络自适应逼近飞行器特性变化时的系统未知不确定性和干扰,通过在虚拟控制律中引入动态面控制技术避免多重微分运算,克服了传统反步法所带来的"项数膨胀"问题。利用Lyapunov稳定性定理证明了闭环系统有界且跟踪误差指数收敛于零的一个小邻域。在考虑未知不确定性的情况下,对某型折叠翼飞行器进行的6自由度(DOF)飞行仿真结果验证了所设计控制器的有效性和鲁棒性。
The characteristics of a folding-wing aerial vehicle undergo fairly great changes during its launching time. To fulfill the high robustness requirements of a flight control system, an adaptive robust nonlinear flight controller based on block backstepping is designed. A variable dynamic model is established, and the unknown uncertainty and disturbance caused by aerodynamic characteristic changes are adaptively approximated by radial basis function (RBF) neural networks. Dynamic surface control is employed to replace the differentiations of the virtual control law in traditional backstepping to overcome the problem of "term explosion". The closed-loop system is guaranteed to be bounded and the tracking errors are also proved to converge exponentially to a small neighborhood around zero by the Lyapunov approach. Furthermore,the effectiveness and robustness of the designed flight controller are verified by six degree-of-freedom (DOF) nonlinear flight simulations for the folding-wing aerial vehicle with unknown uncertainty.
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