To reduce the impact of uncertainties caused by unknown motion parameters on searching plan of moving targets and improve the efficiency of UAV’s searching, a novel distributed Multi-UAVs cooperative search control method for moving target is proposed in this paper. Based on detection results of onboard sensors, target probability map is updated using Bayesian theory. A Gaussian distribution of target transition probability density function is introduced to calculate prediction probability of moving target existence, and then target probability map can be further updated in real-time. A performance index function combining with target cost, environment cost, and cooperative cost is constructed, and the cooperative searching problem can be transformed into a central optimization problem. To improve computational efficiency, the distributed model predictive control method is presented, and thus the control command of each UAV can be obtained. The simulation results have verified that the proposed method can avoid the blindness of UAV searching better and improve overall efficiency of the team effectively.

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Formation flight problem is the most important and interesting problem of multiple UAVs (unmanned aerial vehicles) cooperative control. In this paper, a novel approach for UAV formation flight based on multimodel predictive control is designed. Firstly, the state equation of relative motion is obtained and then discretized. By the geometrical method, the characteristic points of state are determined. Afterwards, based on the linearization technique, the standard linear discrete model is obtained at each characteristic state point. Then, weighted model set is proposed using the idea of T-S (Takagi-Sugeno) fuzzy control and the predictive control is carried out based on the multimodel method. Finally, to verify the performance of the proposed method, two different simulation scenarios are performed.

With unmanned aerial vehicles (UAVs) widely used in both military and civilian fields, many events affecting their safe flying have emerged. That UAV’s entering into the spiral is such a typical safety issue. To solve this safety problem, a novel recovery control approach is proposed. First, the factors of spiral are analyzed. Then, based on control scheduling of state variables and nonlinear dynamic inversion control laws, the spiral recovery controller is designed to accomplish guidance and control of spiral recovery. Finally, the simulation results have illustrated that the proposed control method can ensure the UAV autonomous recovery from spiral effectively.

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