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为避免子控制器切换时控制量的跳变,提出了一种非线性自适应切换控制混合方法。针对输入输出反馈线性化子控制器在使用中存在的逆误差及模型不确定性,采用多层神经网络进行在线补偿,为实现此类非线性自适应子控制器的平滑切换,实际控制律采用各子控制律的凸组合,各组合系数值由切换参数确定。通过合适的设计参数选取与神经网络权值更新律设置,寻找到了闭环切换系统的公共Lyapunov函数,保证了此类系统在切换控制混合下的稳定性。在倾转旋翼机轨迹跟踪控制的应用中,设计了直升机模式、过渡模式与飞机模式的非线性子控制器,应用神经网络在线补偿与随短舱角的控制混合,仿真结果表明该方法具有对系统不确定性的鲁棒性及平滑切换的特性。
In order to avoid the jump of the control quantity when the sub-controller is switched over, a hybrid nonlinear adaptive switching control method is proposed. Aiming at the inverse error and model uncertainty of the input-output feedback linearization sub-controller in use, a multi-layer neural network is used to carry out on-line compensation. To realize the smooth switching of such nonlinear adaptive sub-controller, the actual control law The convex combination of each sub-control law, the value of each combination coefficient is determined by the switching parameters. Through the selection of appropriate design parameters and the renewal law of neural network weight, we find the common Lyapunov function of the closed-loop switched system, which guarantees the stability of such systems under the switching control hybrid. The nonlinear sub-controller of helicopter mode, transition mode and airplane mode is designed in the application of the track-following control of tiltrotor. The neural network online compensation and the control with the angle of the cabin are mixed. The simulation results show that this method has the advantages of System Uncertainty Robustness and Smooth Switching Characteristics.