Robust fault-tolerant control for wing flutter under actuator failure

Many control laws, such as optimal controller and classical controller, have seen their applications to suppressing the aeroelastic vibrations of the aeroelastic system. However, those control laws may not work effectively if the aeroelastic system involves actuator faults. In the current study for wing flutter of reentry vehicle, the effect of actuator faults on wing flutter system is rarely considered and few of the fault-tolerant control problems are taken into account. In this paper, we use the radial basis function neural network and the finite-time H_∞ adaptive fault-tolerant control technique to deal with the flutter problem of wings, which is affected by actuator faults, actuator saturation, parameter uncertainties and external disturbances. The theory of this article includes the modeling of wing flutter and fault-tolerant controller design. The stability of the finite-time adaptive fault-tolerant controller is theoretically proved. Simulation results indicate that the designed fault-tolerant flutter controller can effectively deal with the faults in the flutter system and can promptly suppress the wing flutter as well.     

Active flutter suppression of a multiple-actuated-wing wind tunnel model

In this study, a multi-input/multi-output（MIMO） time-delay feedback controller is designed to actively suppress the flutter instability of a multiple-actuated-wing（MAW） wind tunnel model in the low subsonic flow regime. The unsteady aerodynamic forces of the MAW model are computed based on the doublet-lattice method（DLM）. As the first attempt, the conventional linear quadratic-Gaussian（LQG） controller is designed to actively suppress the flutter of the MAW model. However, because of the time delay in the control loop, the wind tunnel tests illustrate that the LQG-controlled MAW model has no guaranteed stability margins. To compensate the time delay, hence, a time-delay filter, approximated via the first-order Pade approximation, is added to the LQG controller. Based on the time-delay feedback controller, a new digital control system is constructed by using a fixed-point and embedded digital signal processor（DSP） of high performance. Then, a number of wind tunnel tests are implemented based on the digital control system.The experimental results show that the present time-delay feedback controller can expand the flutter boundary of the MAW model and suppress the flutter instability of the open-loop aeroelastic system effectively.     

Aeroservoelastic stability analysis for flexible aircraft based on a nonlinear coupled dynamic model

A unified theoretical aeroservoelastic stability analysis framework for flexible aircraft is established in this paper. This linearized state space model for stability analysis is based on nonlinear coupled dynamic equations, in which rigid and elastic motions of aircraft are both considered. The common body coordinate system is utilized as the reference frame in the deduction of dynamic equations, and significant deformations of flexible aircraft are also fully concerned without any excessive assumptions. Therefore, the obtained nonlinear coupled dynamic models can well reflect the special dynamic coupling mechanics of flexible aircraft. For aeroservoelastic stability analysis, the coupled dynamic equations are linearized around the nonlinear equilibrium state and together with a control system model to establish a state space model in the time domain. The methodology in this paper can be easily integrated into the industrial design process and complex structures. Numerical results for a complex flexible aircraft indicate the necessity to consider the nonlinear coupled dynamics and large deformation when dealing with aeroservoelastic stability for flexible aircraft.     

战术导弹气动伺服弹性滑模控制技术

为抑制弹体弹性振动引起的控制系统品质恶化,建立了高精度弹性动态模型,采用模态自适应结构滤波技术,在极点配置优化控制参数的基础上,设计了滑模变结构策略,对局部增益进行自适应切换,实现了弹性导弹全包线鲁棒稳定。通过开发弹性弹体非线性集成仿真系统,为导弹气动伺服弹性振荡及失稳现象提供了数字仿真预测与复现手段,以全面验证飞行控制系统的综合性能。高空弹道试验与数字仿真结果表明,开发的非线性仿真系统可信度较高,滑模变结构策略设计合理,控制系统鲁棒性较强,能够抑制包括弹性振动在内的多种不确定性影响。