Fuzzy multi-objective distributed cooperative tracking of ground target for multiple unmanned aerial vehicles

For multiple unmanned aerial vehicle(UAV)cooperative tracking ground target with diverse constrains in urban environment, a fuzzy multi-objective path planning method based on distributed predictive control is proposed to deal with multiple objectives with different importance levels. Firstly, the factors including line of sight occlusion from buildings, energy consumptions of UAVs and sensors are considered. Correspondingly, the objective functions are designed as target coverage degree, control input cost and sensor energy consumption with switch value respectively, so that the multiple UAV cooperative tracking problem is transformed into a multi-objective optimization problem; Then, based on distributed predictive control, the predictive states of each UAV in a finite horizon are exchanged to build up collision avoidance constraint between UAVs. Combining the minimum turning radius constraints, the distributed cooperative path planning model is formulated. Finally, for the different important levels requirement, all the objectives are fuzzified by fuzzy satisfactory optimization concept. According to the principle that the objective with higher priority will have higher satisfactory degree, preemptive priorities are modeled into the relaxed order of satisfactory degrees. The local preferred path of each UAV is worked out online in a finite period. Comparing with the traditional weighted multi-objective optimization algorithm, the simulation results show the effectiveness of the proposed method. The best path satisfying the requirements of multi-objective optimization and importance levels can be obtained. © 2018, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.