Research On Using GA To Optimize The Adaptive Fuzzy Controller On The Control Of The Engineer Ship

In order to fit the needs for the project of renovating the middle reaches channel of the Changjiang River, the Changjiang River channel office determines to develop a kind of engineer ship which can be used to lay software sand packets to protect the bottom of the river, so as to ensure the quality of the renovating project in the channel. At present,it is mostly controlled in the manual way, depended on working experience to coordinate and control the length of every six anchor chain to move and make a reservation of the ship. The thesis mainly researches automatic control of moving and mooring the engineer ship, which enables the controlling organization to respond the change of ship's position in time and adjust the courses and flight paths of the ship, and does not need artificial intervention.Since the engineer ship's mathematics model of kinetic control system is the foundation of system design and simulation experiment, the research on the control system of the course of shipping mathematics model has been carried on at first.In the theis,the author derives the mathematical model of the kinetic control system, which offer the essential foundation for the emulation of control system of ship handling in follow-up.Secondly, according to the characteristics of ship steering, a kind of adaptive fuzzy controller is designed. In the various adapitive schemes, A sort of adapive the self-adaptive proportion is selected. So the membership function of input and output lingual variables and control rules are formed in this thesis. When it is used in course control system, the quality of the system is satisfactory.Lastly, from the realization of engineer ship, the genetic algorithm is firstly introduced to the adaptive fuzzy controller which optimizes the membership function of the fuzzy controller. By establishing the simulation research, the result is most stisfactory.At present, Because the project still lacks the matured experience as reference in this project at present, it has some difficulty in applying the technique, so it needs more exploration and study to apply. In addition, the intellectual control technologywhich is adopted in the thesis is the advanced stage for the development of control theory, there to say research of applying genetic algorithm in fuzzy control has made some achievements, but there still exist a lot of problems for further research.