Distributed model predictive energy-saving control of UAVs formation with fuzzy constraints
A distributed model predictive control algorithm with fuzzy constraints is proposed to solve the problem of energy saving in the formation of unmanned aerial vehicles(UAVs).Firstly,the state error space of the wingman relative to the leader is divided into multiple fuzzy sets by using the fuzzy mathematics theory,and the fuzzy constraints of speed and yaw angle commands are designed according to the state errors of each wingman.Secondly,the fuzzy constraints of each wingman relative to the leader are taken as its own constraints in the distributed model predictive control algorithm.By reducing the variation range of speed and yaw angle,the UAV can save energy in formation control.Finally,the proposed algorithm is verified by simulation through compared with the distributed model predictive control algorithm without fuzzy constraints.The statistical results show that this method can shorten the flight distance,reduce the cumulative value of speed and yaw angle change,and has the effect of saving energy.
万方数据
维普
