基于Kalman滤波的变体飞行器T-S模糊控制

针对变体飞行器的跟踪控制问题，提出了一种基于Kalman滤波的T-S模糊控制方法。考虑飞行器系统状态不可测，引入惯导数据作为辅助信息，利用Kalman滤波算法融合飞控信息与惯导信息实现状态估计。由于变体飞行器在不同变形结构下气动特性变化较大，为便于控制器设计，采用小扰动线性化方法得到飞行器在不同平衡点处的局部线性模型，并通过状态反馈方法设计局部控制器，局部线性模型和局部控制器通过模糊集和模糊规则聚合成一个连续光滑的全局T-S模糊模型和T-S模糊控制器。通过综合Kalman滤波器与T-S模糊控制器得到一个基于Kalman滤波的T-S模糊控制器。仿真结果表明，该控制器在变形过程中能够实现状态估计，保证飞机的跟踪性能。

Kalman filter based T-S fuzzy control for morphing aircraft

A Kalman filter based T-S fuzzy controller is proposed to address the tracking control problem of the morphing aircraft. Considering the unmeasurable states of the aircraft, we introduce the inertial navigation data as auxiliary information, and adopt the Kalman filter algorithm to fuse the flight control information and the inertial navigation information to achieve state estimation. Since the aerodynamic characteristics of the morphing aircraft vary considerably with different deformation structures, to facilitate the controller design, we use a small disturbance linearization method to obtain the local linear models of the aircraft at different equilibrium points, and design the local controllers with the state feedback method. The local linear models and local controllers are then aggregated into a continuous and smooth global T-S fuzzy model and a T-S fuzzy controller respectively using the fuzzy sets and fuzzy rules. After the synthesis of the Kalman filter and T-S fuzzy controller, the whole Kalman filter based T-S fuzzy controller is finally developed. The simulation results show that the proposed controller can accurately estimate the states and ensure good tracing performance during the morphing process of the aircraft.