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Distributed Cooperative Path Planning for Tracking Ground Moving Target by Multiple Fixed-wing UAVs via DMPC-GVD in Urban Environment

Chaofang Hu*, Zhuo Meng, Ge Qu, Hyo-Sang Shin, and Antonios Tsourdos
International Journal of Control, Automation, and Systems, vol. 19, no. 2, pp.823-836, 2021

Abstract : In this paper, a real-time distributed path planning method is developed for cooperatively tracking ground moving target in urban by multiple fixed-wing unmanned aerial vehicles (UAVs). For reasons of changeable movement of target, the commanded speed and turning rate of each UAV are both taken as control input variables. In urban environment, buildings may occlude the line of sight of on-board sensor. Hence the target coverage degree is proposed as objective function instead of distance. To save energy of UAV system as much as possible, the control input cost and sensor energy consumption are also taken as objectives. For preemptive priority requirement, the objective functions are fuzzified and the satisfactory degree order is designed to model priority. To guarantee the feasibility of solution, the varying domain is introduced to replace the strict order constraint. On this basis, generalized varying domain (GVD) method is developed to balance optimization and priority. In terms of the maneuverability of UAVs, the diverse constraints are considered, including real speed and turning rate, control input saturation, collision avoidance between UAVs, and obstacle avoidance between UAV and buildings. Consequently, distributed model predictive control (DMPC) strategy is designed to calculate the optimal path of each UAV, where the state information in finite period of UAV is transferred to the adjacent ones. The simulations show the effectiveness of proposed method by comparing with hierarchical optimization (HO).

Keyword : Distributed model predictive control, path planning, priority, unmanned aerial vehicle.

 
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