This article introduces a novel methodology based on zonotopic Kalman filtering for stabilizing attitude dynamics and estimating flight envelopes of an unmanned helicopter via an observer-based (output) feedback control law and a reachability analysis, respectively. The helicopter dynamics is represented by a linear state-space model, based on which the feedback control law is designed. Since not all state variables are measurable, state information is acquired by applying a zonotopic Kalman filter to yield sets of state-variable estimates of the helicopter in terms of zonotopes. Not only are the resulting zonotopes used for the observer-based feedback control, but also for estimating the flight envelopes of the helicopter based on the reachability analysis. This approach is useful for enhancing pilot’s awareness about dynamic responses of the helicopter, which may undergo unsafe flight conditions due to actuator faults triggered by undesirable perturbations. The efficacy of the proposed methodology is demonstrated via an example, where we also expose the benefits of applying the zonotopic Kalman filter as compared with an ordinary stochastic Kalman filter.

本文介绍了一种基于区域性卡尔曼滤波的新颖方法，分别用于通过基于观察者的（输出）反馈控制律和可达性分析来稳定姿态动力学并估计无人直升机的飞行包络。直升机动力学由线性状态空间模型表示，在该模型的基础上设计了反馈控制律。由于并非所有状态变量都是可测量的，因此通过应用区域局部卡尔曼滤波器获取直升机的状态变量估计值，可以获取状态信息。所得的地带不仅用于基于观察者的反馈控制，而且还用于基于可达性分析来估计直升机的飞行范围。这种方法对于增强飞行员对直升机动态响应的认识很有用，由于不希望的扰动引起的执行器故障，这种动态响应可能会导致飞行不安全。通过一个示例证明了所提出方法的有效性，在该示例中，我们还展示了与常规的随机Kalman滤波器相比，应用区域性Kalman滤波器的好处。