Patent ID: 11887485
Assignee: CHONGQING UNIVERSITY
Field: Control (Instruments)
Classification: CPC G  B | IPC B  G

Claim 4:
5. The control method of claim 4, wherein the determining the training sample of the ith unmanned surface vessel comprises:
obtaining task environment information of each unmanned surface vessel in the unmanned surface vessel group at a tth moment;
estimating interception point information of the intruding target at the tth moment by using the Kalman filter according to the task environment information of all unmanned surface vessels at the tth moment; wherein the interception point information comprises the predicted position of the intruding target and the predicted velocity of the intruding target;
determining process state information of the ith unmanned surface vessel at the tth moment according to the task environment information of the ith unmanned surface vessel at the tth moment and the interception point information of the intruding target at the tth moment;
obtaining an execution action of the ith unmanned surface vessel at the tth moment;
calculating a reward of the ith unmanned surface vessel at the tth moment according to a formula of, r
      1
    
    =
    
      
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          b
          j
        
      
      ⁢
      
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  ;

 wherein rl is the reward of the ith unmanned surface vessel at the tth moment, Ui, is the ith unmanned surface vessel, bj is a jth intruding target, y′ui, bj (t) is a distance between the jth intruding target and the ith unmanned surface vessel at the tth moment, y′ui, bj(t+1) is a distance between the jth intruding target and the ith unmanned surface vessel at a (t+1)th moment;
obtaining task environment information of each unmanned surface vessel in the unmanned surface vessel group at the (t+1)th moment;
estimating interception point information of the intruding target at the (t+1)th moment by using the Kalman filter according to the task environment information of all unmanned surface vessels at the (t+1)th moment; wherein the interception point information comprises the predicted position of the intruding target and the predicted velocity of the intruding target;
determining process state information of the ith unmanned surface vessel at the (t+1)th moment according to the task environment information of the ith unmanned surface vessel at the (t+1)th moment and the interception point information of the intruding target at the (t+1)th moment;
combining the process state information of the ith unmanned surface vessel at the tth moment, the execution action of the ith unmanned surface vessel at the tth moment, the reward of the ith unmanned surface vessel at the tth moment, and the process state information of the ith unmanned surface vessel at the (t+1)th moment into a sample set of the ith unmanned surface vessel at the tth moment;
storing the sample set of the ith unmanned surface vessel at the tth moment in an experience pool; and
stopping storing when data stored in the experience pool reach a set amount; wherein the data in the experience pool after stopping storing are the training sample of the ith unmanned surface vessel.