【摘要】 倾转旋翼机具有在复杂环境下执行任务的能力，逐渐成为新构型飞行器领域研究的热点。针对风干扰下倾转旋翼机直升机模态的建模与跟踪控制问题，提出一种基于神经网络干扰观测器与预设性能方法的跟踪控制方法。首先，对倾转旋翼机进行分体建模，并将地面风对机体的影响设定成有界外部干扰的形式，建立了风干扰下的直升机模态动力学模型。其次，为了提高直升机模态跟踪控制的鲁棒性，采用神经网络逼近系统中的未知函数，并利用干扰观测器估计机体所受扰动。再次，基于上述设计，提出一种基于预设性能函数的抗干扰跟踪控制器，并通过Lyapunov方法证明跟踪误差是有界的。最后，仿真结果表明，所提方法的位置、角度跟踪误差在2 s内就能快速收敛，并且始终位于预设的性能界内。进一步表明所提算法能够有效实现倾转旋翼机的稳定跟踪控制，并具有良好的环境适应能力与鲁棒性。更多还原

【Abstract】 Tiltrotor aircraft has the ability to perform tasks in complex environments, and has gradually become a research hotspot in the field of new configuration aircraft. Aiming at the modeling and tracking control of tiltrotor helicopter modes under wind disturbance, a tracking control method based on neural network disturbance observer and prescribed performance method is proposed. Firstly, the tiltrotor is modeled separately, and the influence of ground wind on the body is sorted into the form of bounded external disturbance, and the modal dynamic model of the helicopter under wind disturbance is established. Secondly,in order to improve the robustness of helicopter modal tracking control, the neural network is used to approximate the unknown function in the system, and the disturbance observer is used to estimate the disturbance suffered by the aircraft. Thirdly, based on the above design, an anti-disturbance tracking controller based on a prescribed performance function is proposed, and the tracking error is proved to be bounded by the Lyapunov method. Finally, the simulation results show that the position and angle tracking errors of the proposed method can quickly converge within 2 s, and are always within the prescribed performance bounds. It further shows that stable tracking control of the tiltrotor is available by the proposed algorithm with excellent environmental adaptability and robustness.更多还原