论文部分内容阅读
为了使小型无人直升机在风场环境下稳定飞行,通过将主动建模技术与传统的LQG控制相结合,提出了一种能有效适应模型不确定性的控制方法。该方法将风场对无人直升机的扰动看作随机扰动,并把这种扰动作为参数与机体模型中的状态合并成增广的机体状态量,而后用卡尔曼滤波对其进行实时估计,实时得到扰动的估计值,并将其反馈给控制器以实现对控制器的重构,从而完成对无人直升机的稳定控制。依据建模理论建立了机体的半解耦模型以及大气紊流模型,用该模型进行了仿真,结果表明,本控制方法对大气紊流有一定的抑制作用。
In order to make the small unmanned helicopter fly steadily in the wind field, a control method that can effectively adapt to the uncertainty of the model is proposed by combining the active modeling technique with the traditional LQG control. In this method, the perturbation of unmanned helicopter in the wind field is regarded as random perturbation, and the perturbation is taken as the parameter and the state in the model of the body is merged into an augmented body state quantity, and then real-time estimation is carried out by using Kalman filtering, The perturbed estimate is obtained and fed back to the controller to reconstruct the controller, thus completing the stable control of the unmanned helicopter. Based on the modeling theory, the semi-decoupled model of the airframe and the atmospheric turbulence model are established, and the model is used to simulate the model. The results show that the proposed method can restrain the atmospheric turbulence.