基于CFD降阶模型的阵风减缓主动控制研究

飞行器飞行时会受到大气紊流的影响,降低飞行品质。阵风减缓控制是改善飞行器飞行性能的关键技术。现有的阵风响应分析多以离散阵风为研究对象,对更加真实描述大气紊流的连续型阵风时域分析关注较少。采用成形滤波器方法将频域形式给出的大气紊流信号转换为时域信号。在跨声速区域内,利用系统辨识技术,基于计算流体力学(CFD)方法建立阵风激励下的气动载荷状态空间降阶模型(ROM)。为方便控制器设计,借助平衡模态法进行模型的进一步降阶。使用模型预测控制(MPC)算法通过控制操纵面偏转实现阵风减缓主动控制。以AGARD445.6标模作为仿真算例,验证基于ROM设计的阵风减缓控制律的有效性。仿真结果表明,在跨声速飞行状态下,模型预测控制器能够在满足操纵面偏转范围的约束下,对连续阵风激励下的翼根弯矩输出进行有效抑制。

Gust alleviation active control based on CFD reduced-order models

In flight, aircraft suffers atmospheric turbulence and the flight quality degrades. Gust load alleviation is an important technique for improving the performance of aircraft. Most of the existing gust response analysis focuses on discrete gust while study on continuous gust attracts little attention. The continuous turbulence time domain signals can be obtained with the shaping filter. In transonic regime, computational fluid dynamics (CFD)-based gust loads reduced-order models (ROM) in the state-space form are built by the system identification method. Furthermore, to design a feasible controller, the balanced truncation approach is used to reduce the model order. Model predictive control (MPC) algorithm is adopted to control the deflection of the control surface so that gust load alleviation is realized. The AGARD445.6 wing configuration is used as a numerical example to demonstrate the present gust ROM methodology and alleviation effects. It has been shown that the gust ROM with MPC law can suppress the wing root bending moment effectively; meanwhile, the deflection of the control surface can satisfy the hard constrain.