Unmanned helicopters are widely used in military and civil fields. One of the most important applications is flying with an underslung load, but the pendulum-like behavior of the load can cause damage or even forced landing to the helicopter. To solve this problem, a control strategy to stabilize the helicopter/load system based on active disturbance rejection control (ADRC) and improved sliding mode control (ISMC) algorithms is proposed in this paper. First, the helicopter/load system is modelled using Newton-Euler equations according to the multi-body dynamics theory. Then a manipulation strategy which can reduce the swing angle of the load and an overall control strategy for the helicopter/load system are presented. Specifically, ADRC is applied to attitude control due to its ability to regard the pendulum-like behavior as the internal uncertainties of the system, meanwhile ISMC to position control. Within ISMC, two sliding surfaces with adjustable weights are constructed by employing the position of the helicopter as well as the swing angle of the load. In addition, a real-time beetle antennae search algorithm is designed to online modify the weights by taking the minimum error at current time as the optimization objective. Besides, the radial basis function neural network is introduced to approach the uncertainty coefficients considering the system’s complexity. At last, relevant simulations are carried out and the results indicate that the system is capable of not only controlling the attitude and position of the helicopter precisely but also stabilizing the underslung load rapidly with ADRC and ISMC.

无人直升机被广泛用于军事和民用领域。最重要的应用之一是在负重负载下飞行，但是这种类似摆的行为会导致损坏甚至迫使直升机降落。针对这一问题，提出了一种基于主动抗扰控制（ADRC）和改进的滑模控制（ISMC）算法的稳定直升机/负荷系统的控制策略。首先，根据多体动力学理论，使用牛顿-欧拉方程对直升机/负载系统进行建模。然后，提出了一种可以减小负载摆动角度的操纵策略以及直升机/负载系统的总体控制策略。具体来说，由于ADRC具有将类摆行为视为系统内部不确定性的能力，而将其应用于ISMC进行位置控制，因此ADRC被应用于姿态控制。在ISMC中，通过利用直升机的位置以及负载的摆动角度来构造两个可调整重量的滑动表面。此外，设计了一种实时的甲虫天线搜索算法，以当前时间的最小误差为优化目标，在线修改权重。此外，引入了径向基函数神经网络来考虑系统的复杂度来确定不确定性系数。终于，