Cluster collaborative deployment method based on distributed optimal energy MPC
A distributed and optimal technology, applied in non-electric variable control, complex mathematical operations, instruments, etc., can solve the problems of low UAV density, poor flight trajectory, large control error, etc., and achieve the density of UAVs. High, short flight path, the effect of reducing the amount of calculation
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[0144] Carry out a simulation experiment. In the experiment, 6 UAVs are set for coordinated deployment. The maximum speed of the UAVs is 1m / s, the initial position of the target is [2.5, 2.0], and the UAVs are initially distributed around the target. The cluster is optimal. Collaborate to gather and track the target.
[0145] Each UAV uses the proportional guidance method to plan the predicted trajectory, and sends the predicted trajectory to the adjacent UAVs.
[0146] After each UAV obtains the predicted trajectory of the adjacent UAV, the optimal trajectory is obtained by solving the distributed energy optimal control model. The distributed energy optimal control model is expressed as:
[0147]
[0148] Among them, the terminal cost φ(x i ,t f )Expressed as:
[0149] φ(x i ,t f )=w vc φ vc (x i ,t f )+w va φ va (x i ,t f )+w a φ a (x i ,t f ) (Four)
[0150] Further, in formula (4), φ vc (x i ,t f ) is the cluster speed control item:
[0151]
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