Recalde Luis F, Guevara Bryan S, Carvajal Christian P, Andaluz Victor H, Varela-Aldás José, Gandolfo Daniel C
SISAu Research Group, Facultad de Ingeniería y Tecnologías de la Información y Comunicación, Universidad Tecnológica Indoamérica, Ambato 180103, Ecuador.
Instituto de Automática, Universidad Nacional de San Juan-CONICET, Av. San Martín Oeste 1109, San Juan J5400ARL, Argentina.
Sensors (Basel). 2022 Jun 22;22(13):4712. doi: 10.3390/s22134712.
Accurate trajectory tracking is a critical property of unmanned aerial vehicles (UAVs) due to system nonlinearities, under-actuated properties and constraints. Specifically, the use of unmanned rotorcrafts with accuracy trajectory tracking controllers in dynamic environments has the potential to improve the fields of environment monitoring, safety, search and rescue, border surveillance, geology and mining, agriculture industry, and traffic control. Monitoring operations in dynamic environments produce significant complications with respect to accuracy and obstacles in the surrounding environment and, in many cases, it is difficult to perform even with state-of-the-art controllers. This work presents a nonlinear model predictive control (NMPC) with collision avoidance for hexacopters' trajectory tracking in dynamic environments, as well as shows a comparative study between the accuracies of the Euler-Lagrange formulation and the dynamic mode decomposition (DMD) models in order to find the precise representation of the system dynamics. The proposed controller includes limits on the maneuverability velocities, system dynamics, obstacles and the tracking error in the optimization control problem (OCP). In order to show the good performance of this control proposal, computational simulations and real experiments were carried out using a six rotary-wind unmanned aerial vehicle (hexacopter-DJI MATRICE 600). The experimental results prove the good performance of the predictive scheme and its ability to regenerate the optimal control policy. Simulation results expand the proposed controller in simulating highly dynamic environments that showing the scalability of the controller.
由于系统的非线性、欠驱动特性和约束条件，精确的轨迹跟踪是无人机（UAV）的一项关键特性。具体而言，在动态环境中使用配备精确轨迹跟踪控制器的无人旋翼机，有潜力改善环境监测、安全、搜索与救援、边境监视、地质与采矿、农业以及交通管制等领域。在动态环境中进行监测操作，在准确性和周围环境中的障碍物方面会产生重大复杂性，而且在许多情况下，即使使用最先进的控制器也难以执行。这项工作提出了一种用于六旋翼无人机在动态环境中轨迹跟踪的具有避碰功能的非线性模型预测控制（NMPC），并展示了欧拉 - 拉格朗日公式和动态模式分解（DMD）模型准确性之间的比较研究，以便找到系统动力学的精确表示。所提出的控制器在优化控制问题（OCP）中包括对机动性速度、系统动力学、障碍物和跟踪误差的限制。为了展示该控制方案的良好性能，使用六旋翼无人飞行器（六旋翼 - DJI MATRICE 600）进行了计算模拟和实际实验。实验结果证明了预测方案的良好性能及其再生最优控制策略的能力。模拟结果在模拟高动态环境中扩展了所提出的控制器，展示了该控制器的可扩展性。
