
FOLLOWUS
School of Automation, Northwestern Polytechnical University, Xi'an 710129, China
Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal QC H3G 1M8, Canada
College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
You-min ZHANG, E-mail: ymzhang@encs.concordia.ca
收稿:2018-09-15,
修回:2019-;5-13,
纸质出版:2019-05
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余自权, 刘治湘, 张友民, 等. 有向通信拓扑下具有姿态同步跟踪预设性能的多无人机分散式容错协同控制[J]. 信息与电子工程前沿(英文), 2019,20(5):685-700.
Zi-quan YU, Zhi-xiang LIU, You-min ZHANG, et al. Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(5): 685-700.
余自权, 刘治湘, 张友民, 等. 有向通信拓扑下具有姿态同步跟踪预设性能的多无人机分散式容错协同控制[J]. 信息与电子工程前沿(英文), 2019,20(5):685-700. DOI: 10.1631/FITEE.1800569.
Zi-quan YU, Zhi-xiang LIU, You-min ZHANG, et al. Decentralized fault-tolerant cooperative control of multiple UAVs with prescribed attitude synchronization tracking performance under directed communication topology[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(5): 685-700. DOI: 10.1631/FITEE.1800569.
针对多无人机在有向通信拓扑中遭遇执行器故障问题,提出一种分散式容错协同控制方案。首先,利用神经网络对无人机模型中的固有非线性项和执行器效率下降故障所引起的未知非线性项进行估计。其次,引入干扰观测器对神经网络估计偏差和执行器偏差故障进行估计。再次,设计可反映神经网络和干扰观测器复合估计能力的预测偏差,并将该预测偏差集成至所设计的容错协同控制方案中,以提升复合估计能力。最后,利用预设性能函数对姿态同步跟踪偏差进行变换,实现同步跟踪偏差预设性能控制。该控制方案的一个关键特征是多无人机本身的非线性项和与执行器故障有关的非线性项可被神经网络、干扰观测器、预测偏差组成的复合估计器较好地估计。另一个关键特征是姿态同步跟踪偏差被严格约束在预设性能界限内。仿真结果表明所设计控制方案有效。
In this paper
a decentralized fault-tolerant cooperative control scheme is developed for multiple unmanned aerial vehicles (UAVs) in the presence of actuator faults and a directed communication network. To counteract in-flight actuator faults and enhance formation flight safety
neural networks (NNs) are used to approximate unknown nonlinear terms due to the inherent nonlinearities in UAV models and the actuator loss of control effectiveness faults. To further compensate for NN approximation errors and actuator bias faults
the disturbance observer (DO) technique is incorporated into the control scheme to increase the composite approximation capability. Moreover
the prediction errors
which represent the approximation qualities of the states induced by NNs and DOs to the measured states
are integrated into the developed fault-tolerant cooperative control scheme. Furthermore
prescribed performance functions are imposed on the attitude synchronization tracking errors
to guarantee the prescribed synchronization tracking performance. One of the key features of the proposed strategy is that unknown terms due to the inherent nonlinearities in UAVs and actuator faults are compensated for by the composite approximators constructed by NNs
DOs
and prediction errors. Another key feature is that the attitude synchronization tracking errors are strictly constrained within the prescribed bounds. Finally
simulation results are provided and have demonstrated the effectiveness of the proposed control scheme.
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