劉洋 王蕾

為了提高海上艦艇編隊攻擊路徑自動規(guī)劃和自適應調度能力，從而實現(xiàn)海上艦艇編隊協(xié)同智慧調度，提出基于模糊PID的艦艇編隊攻擊路徑優(yōu)化規(guī)劃算法。采用衛(wèi)星通信組網信息調度技術進行海上艦艇編隊攻擊路徑規(guī)劃的控制指令信息提取，結合艦艇編隊攻擊路徑的信息特征檢測技術進行攻擊路徑規(guī)劃過程中的信息調度和特征提取，采用模糊神經網絡控制技術進行海上艦艇編隊攻擊路徑自動規(guī)劃的線路自動篩選和尋優(yōu)控制處理，構建物聯(lián)網信息管理平臺進行海上艦艇編隊攻擊路徑自動規(guī)劃和分布式協(xié)同調度，采用模糊PID神經網絡學習方法進行海上艦艇編隊攻擊路徑規(guī)劃的優(yōu)化學習。仿真結果表明，采用該方法進行艦艇編隊攻擊路徑規(guī)劃的協(xié)同控制能力較好，區(qū)域覆蓋能力較強，路徑自適應尋優(yōu)的收斂性較好。

關鍵詞：模糊PID;艦艇編隊;攻擊路徑;規(guī)劃

【Abstract】 In order to improve the automatic planning and adaptive scheduling ability of marine warship formation attack path， so as to realize the cooperative wisdom of offshore warship formation， a fuzzy PID based ship formation attack path optimization planning algorithm is proposed. The satellite communication network information scheduling technology is used to extract the control instruction information of the attack path planning of the marine warship formation. Combined with the information feature detection technology of the attack path of the warship formation， the information scheduling and feature extraction in the process of the attack path planning are carried out. The fuzzy neural network control technology is used to automatically screen and optimize the route of the attack path automatic planning of the marine warship formation. The information management platform of the Internet of things is constructed for automatic planning and distributed cooperative scheduling of attack paths for offshore warship formation， and fuzzy PID neural network learning method is used to optimize the attack path planning for offshore warship formation. The simulation results show that the cooperative control ability of ship formation attack path planning is better， the regional coverage ability is strong， and the convergence of path adaptive optimization is better.

【Key words】 fuzzy PID; ship formation; attack path; planning

0 引 言

隨著海上協(xié)同作戰(zhàn)信息化水平的不斷提升，需要進行海上艦艇編隊攻擊的信息化調度和攻擊路徑的智能規(guī)劃設計，構建海上艦艇編隊攻擊路徑規(guī)劃模型，在集成信息處理平臺下進行海上艦艇編隊攻擊路徑自動規(guī)劃系統(tǒng)的優(yōu)化設計，采用大數據信息融合處理技術，進行海上艦艇編隊攻擊路徑自動規(guī)劃，提高海上協(xié)同作戰(zhàn)背景下艦艇編隊的打擊和火力覆蓋能力，研究艦艇編隊攻擊路徑優(yōu)化規(guī)劃模型具有重要意義[1]。

對艦艇編隊攻擊路徑優(yōu)化規(guī)劃模型的研究是建立在對艦艇編隊攻擊路徑的信息特征分析和大數據挖掘基礎上，結合協(xié)同融合濾波模型進行艦艇編隊攻擊路徑的自適應調度和規(guī)劃，提高艦艇編隊攻擊路徑優(yōu)化規(guī)劃能力[2]。傳統(tǒng)方法中，對艦艇編隊攻擊路徑優(yōu)化規(guī)劃方法主要有遺傳算法、粒子群算法和Kalman濾波算法等，根據對海上艦艇編隊攻擊路徑統(tǒng)計信息流的測量和特征提取結果，進行海上艦艇編隊攻擊路徑規(guī)劃，構建海上艦艇編隊攻擊路徑規(guī)劃網絡模型，實現(xiàn)路徑規(guī)劃的自適應尋優(yōu)控制，但上述方法進行艦艇編隊攻擊路徑規(guī)劃的自適應性不好，融合度不高[3]。針對上述問題，本文提出基于模糊PID的艦艇編隊攻擊路徑優(yōu)化規(guī)劃算法。首先采用衛(wèi)星通信組網信息調度技術進行海上艦艇編隊攻擊路徑規(guī)劃的控制指令信息提取，結合艦艇編隊攻擊路徑的信息特征檢測技術進行攻擊路徑規(guī)劃過程中的信息調度和特征提取。然后采用模糊神經網絡控制技術進行海上艦艇編隊攻擊路徑自動規(guī)劃的線路自動篩選和尋優(yōu)控制處理，構建物聯(lián)網信息管理平臺進行海上艦艇編隊攻擊路徑自動規(guī)劃和分布式協(xié)同調度，采用模糊PID神經網絡學習方法進行海上艦艇編隊攻擊路徑規(guī)劃的優(yōu)化學習。最后進行仿真實驗分析，展示了本文方法在提高艦艇編隊攻擊路徑優(yōu)化規(guī)劃能力方面的優(yōu)越性能。