Research On UUV Collaborative Online Optimization Search Based On Predictive Control

In recent years,with the development and utilization of marine resources,how to use existing resources to quickly search for underwater targets has become an urgent problem.Unmanned Underwater Vehicle,as an intelligent carrier with its own energy source,equipped with detection equipment,and autonomously completing tasks,provides new ideas for solving this problem.This topic researches the problem of collaborative online search of underwater targets by unmanned underwater vehicles,so that it can quickly complete the search task for underwater targets.When solving the system collaborative online optimization search problem,considering the UUV’s endurance and economy,the working mode is divided into: economic mode and search mode,and the guidance strategy in economic mode and the collaborative framework in search mode are developed in this way.And optimization of decision-making algorithms.The main research contents of this article:First,analyze the UUV collaborative online optimization search problem,formulate the search process,divide the UUV working mode,and propose a search scheme for collaborative online optimization search decision under the model predictive control framework.Model the elements involved in the search problem,including the task area modeling method,the UUV collaborative search architecture and kinematics model,the detection device model,and the definition of communication messages in the system.Secondly,for the UUV collaborative search decision problem,an improved particle swarm optimization algorithm is proposed.First-order prediction and backtracking constraints are implanted in the update iteration process of particles to avoid infeasible solutions generated by the iteration process of particle update.When the objective function is used,the system searches for the end distance constraint.The simulation is based on the sea area near the island as the application background.The simulation results show that the search route of the optimal decision planning can maintain different search strengths for sea areas with different hydrological information.At the end of the search task,the system search endpoint distance is shortened.Then,for the UUV collaborative online optimization search problem,a guidance strategy in economic mode and a system model predictive control framework in search mode are designed.Based on predictive control,an improved particle swarm algorithm is used to optimize the control input set.The first step of the optimal control input set is the control input instruction at the current moment of the system,which decomposes an overall continuous time optimization problem into continuous finite time.Optimization issues within the segment.In the communication information fusion process,the concept of time stamp is introduced to improve the fusion efficiency.The simulation results show that the guidance strategy in the economic mode can guide the UUV into the range of the target and improve the search accuracy;the collaborative online optimization search algorithm in the search mode improves the search efficiency and economy.Finally,based on the GUI design of MATLAB,the system construction of the UUV collaborative online optimization search based on the predictive control mechanism is completed.The guiding strategy of the economic model designed in the subject,the model prediction framework of the search model,and the optimized search decision are encapsulated,and the simulation of the UUV collaborative online optimization decision search scenario is completed through the interface design.The validity of the research content of this paper is proved by different search cases.