Research On Collaborative Scheduling Of Uncertain Unmanned Systems For Disaster Emergency Response

In the emergency rescue work for disasters,the communication links are damaged due to the damage caused by the disaster,and the communication system in the environment of the disaster area needs to be restored so that the command center can obtain the information of the disaster area in time and carry out rescue tasks.The traditional disaster emergency deployment communication base station has high communication cost and affects the efficiency of disaster rescue.With the increasing maturity of unmanned system technology,based on unmanned system construction of heterogeneous Internet of Things has become the first choice for disaster relief.In the real disaster scenario,the disaster accident often has the characteristics of suddenness,non-programming of decision-making,and great uncertainty.Therefore,in this thesis,aiming at the uncertainty of caps and collars of the spatial location data and position parameter valuation of emergency heterogeneous Internet of Things nodes,this thesis proposes a heterogeneous Internet of Things model based on Unmanned Aerial Vehicle space-based relay,and uses a robust optimization algorithm to solve the influence of uncertainty parameters on heterogeneous Internet of Things models.The main work and research content of this thesis are as follows:(1)This thesis analyzes the uncertainty factors in the disaster emergency scenario,and the characterization of uncertainty is studied qualitatively and quantitatively.Considering the damage to the ground communication system in the disaster emergency scenario,a heterogeneous Internet of Things deterministic model with Unmanned Aerial Vehicle as the air relay base station is constructed to minimize the communication power between the ground Internet of Things equipment and the air Unmanned Aerial Vehicle relay base station,so as to realize the constraint on the number of terrestrial Internet of Things devices accessed at the same time,time varying cluster full coverage constraints,and reliability communication constraints.The deterministic optimization problem of Unmanned Aerial Vehicle air-based relay based on the augmentation vector is established.This optimization problem is non-convex and nonlinear,it is difficult to obtain the optimal solution directly,so the orthogonal transformation method is used in this thesis to relax the problem in order to transform the non-convex problem into a convex optimization problem for solution.(2)There is a large correlation between the model performance and the positioning accuracy of the ground Internet of Things terminal devices,and the subtle disturbance of the positioning information and the unreasonable valuation of the upper and lower bounds of the parameters may lead to the invalidity of the model solution,so considering the uncertainty of the real-time spatial positioning parameters and the estimation of the upper and lower bounds of the parameters in the model,the ellipsoidal uncertainty set is applied to describe the uncertainty of the positioning data of the Internet of Things device and the valuation of the upper and lower bounds of the parameters,and the optimization model containing parameter uncertainty is converted into an optimization model in deterministic form.In addition,a robust counterpart model of the air-based Unmanned Aerial Vehicle relay communication power optimization problem is obtained,which is solved and the influence of the two types of uncertain parameters on the established model is analyzed.Simulation results show that the robust optimization algorithm used in this thesis has good robust performance and good results in communication energy consumption suppression compared with the Relaxed Quadratic Constraint Quadratic Program(RQCQP)algorithm in the same experimental environment.