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为解决折叠翼飞行器初段飞行中气动特性变化大且易受环境扰动影响、控制鲁棒性要求高的问题,将飞行器物理模型的实时辨识与非线性动态逆方法相结合,设计可重构飞行控制器。基于迭代扩展卡尔曼滤波与渐消记忆最小二乘,将气动特性辨识一步方法分解为状态量和参数值的两步辨识,算法更易于在线实现。通过实时辨识更新动态逆控制器参考模型,消除模型逆误差,实现可重构控制。针对某型折叠翼飞行器的6自由度仿真结果表明,在飞行器自身气动特性大幅变化且考虑外界未知扰动情况下,控制器满足设计要求,具有较强的鲁棒性。
In order to solve the problem that the aerodynamic characteristics of the folded wing aircraft vary greatly and are easily affected by environmental disturbances and the control robustness is high, the real-time identification of the aircraft physical model and the nonlinear dynamic inverse method are combined to design the reconfigurable flight control Device. Based on the iterative extended Kalman filter and fading memory least squares, the aerodynamic characteristic identification method is decomposed into two-step identification of state variables and parameter values, and the algorithm is easier to implement online. Through real-time identification update dynamic inverse controller reference model, eliminating the model error, to achieve reconfigurable control. The simulation result of 6 DOF of a certain type of folded-wing aircraft shows that the controller meets the design requirements with strong robustness under the condition that the aerodynamic characteristics of the aircraft vary greatly and the unknown disturbance is considered.