This paper proposes a robust formation control scheme for networked multi-tilt tricopter UAVs utilizing the Negative Imaginary (NI) and Positive Real (PR) theory. A Sliding Mode Control (SMC) scheme is designed for a multi-tilt tricopter to ensure stable hovering at a desired height. Then, a modified Subspace-based system identification algorithm is devised to identify a six-by-six NI model of the inner-loop-SMC-controlled tricopter in the continuous-time domain by exploiting the Laguerre filter. A two-loop formation control scheme has been developed for networked multi-tilt tricopters where the inner loop of each tricopter applies the SMC scheme, and the outer loop implements a distributed output feedback controller that satisfies the ‘mixed’ Strictly NI (SNI) + Strictly PR (SPR) system properties. Subsequently, we have established the robustness of the proposed scheme against NI/PR-type uncertainties and sudden loss of agents. The eigenvalue loci (also known as characteristic loci) technique is used instead of the Lyapunov-based approach to prove the asymptotic stability of the formation control scheme. An in-depth simulation case study was performed on a group of six inner-loop-SMC-controlled multi-tilt tricopters connected via a network to achieve a formation control mission, even in the presence of uncertainties.

中文翻译：

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利用内环滑模控制技术的网络化多倾斜三轴飞行器负虚鲁棒编队控制方案


本文利用负虚数（NI）和正实数（PR）理论，提出了一种网络化多倾斜三轴无人机的鲁棒编队控制方案。滑模控制（SMC）方案专为多倾斜三轴飞行器设计，以确保稳定悬停在所需高度。然后，设计了一种改进的基于子空间的系统识别算法，利用拉盖尔滤波器在连续时间域中识别内环SMC控制的三轴飞行器的6×6 NI模型。针对网络化多倾斜三轴飞行器开发了一种双环编队控制方案，其中每个三轴飞行器的内环采用SMC方案，外环采用分布式输出反馈控制器，满足“混合”严格NI（SNI）+严格的PR（SPR）系统属性。随后，我们建立了所提出的方案针对 NI/PR 型不确定性和代理突然流失的稳健性。使用特征值轨迹（也称为特征轨迹）技术代替基于李亚普诺夫的方法来证明编队控制方案的渐近稳定性。对通过网络连接的六架内环 SMC 控制的多倾斜三轴飞行器进行了深入的仿真案例研究，以实现编队控制任务，即使存在不确定性。