Optimization Of One Intelligent Tracking Control Algorithm

Along with the shipping business is becoming more and more intelligent, the ship trackingcontrol is becoming more and more important in the field of ship motion control. The shipIntelligent Handle and Control (SIHC) simulation research platform with DMI’s six degrees offreedom ship models is developed by our university. It is a innovative research platform of thekey projects that colleges and universities in Fujian province serving Haixi. And it can provideapproximate sea trial simulation test platform for algorithms of ship collision avoidance andautomatic control. Intelligent sailing and automatic control module is one of the innovations ofthe platform, and ship intelligent tracking control algorithm is one of the most importantalgorithms.After studying and understanding the preliminary ship controlling performance evaluationmethod and ship intelligent tracking algorithm, based on the SIHC simulation and researchplatform, respectively testing existing heading control and intelligent tracking control algorithmson the environment and all kinds of ship’s adaptability. Aimed at the problems, the main researchcontents are as follows：（1）Considering the important role of initial parameters in PID heading control algorithm,referred to as the initial calculation model, the model to calculate initial parameters of PIDheading control algorithm is built in this paper, which is referred to initial parameter calculationmodel. Optimization of fuzzy self-tuning PID heading control algorithm has further improvedthe algorithm’s adaptability.（2）Optimization of the original intelligent tracking control algorithm. The intelligenttracking control algorithm integrated in SIHC simulation and research platform includes twoparts, one is tracking guidance algorithm, and the other is tracking automatic control algorithm.The tracking automatic control algorithm includes heading guidance algorithm and headingcontrol algorithm. And heading control algorithm is fuzzy self-tuning PID heading controlalgorithm that can automatically determine the initial parameters. And the use of alternativetracking guidance algorithm, focus on optimizing the intelligent tracking control algorithm whileship approaching to turning points has greatly improved the accuracy of intelligent trackingcontrol algorithm.（3）Optimization of the proposed evaluation method used to judge the performance of ship course tracking algorithm. Through the adjustment of individual evaluation index, reducing theeffect of ship maneuvering parameters on the evaluation result. The optimized course trackingperformance evaluation method uses the simple weighted average method. The weights inheritedthe questionnaire results of original performance evaluation of tracking algorithm. And itovercame the shortages of original method.（4）Based on SIHC simulation and research platform, performance testing and analysis ofoptimized algorithms were carried out. Firstly, realized the optimized algorithms with the use ofVisual C++6.0, and then integrated them into the SIHC simulation and research platform. Finally,setted different environment and selected different ship model, to test all the optimizedalgorithms comprehensive, at the same time, used the optimized course tracking performanceevaluation algorithm to assess the performance of course control algorithm quantitatively.