The Application Of Intelligent Control Theory In Automatic Monitoring System For The Geotextiles-laying Vessel's Operation

In order to meet the requirement of management in Changjiang River sea-route and the needs of soft riverbed basis of the requirements of the Building Construction, the geotextiles-laying vessel is produced, which is a new type of engineering ship. Because of its unique mode of motion control and difficult to build a precise model, therefore,this dependence of traditional control theory has greatly limited its application.At present, it is mostly controlled in manual way, depended on working experience to coordinate and control the length of every anchor chain to move and make a reservation of the ship. So to achieve high efficiency and high-quality geotextiles-laying operations the geotextiles-laying vessel automatic control is essential.The emergence of the intelligent control theory is the right remedy for what the traditional control theory lacks. Instead of building accurate mathematics model, it controls a system utilizing the ratiocinating methods of humankind. That is, by organizing mankind's valuable experience into systematical knowledge base and reasoning framework, intelligent control theory achieves its ideal control aim.The main research of this thesis is Fuzzy Neural control and its application in engineering ship's motion control. The self-steering and the self-rectifying of the course and the track in the engineering ship have been carried out in the thesis.First, the article works on ship modeling, research by BP neural network of geotextiles-laying vessel movement model to study the genetic algorithm BP neural network optimization parameters, based on the completion of a GA-BP's campaign geotextiles-laying vessel model. This paper is based on genetic algorithm for neural network modeling BP, BP neural network solution own shortcomings, the establishment of BP neural network structure has played a good role in the global optimization. The model is the use of genetic algorithm optimization of the overall ability to optimize BP neural network weights and threshold, a very good solution works hard to build ships ideal mathematical model of practical problems. Secondly, against established by the GA-BP ship model works simply fuzzy controller design through simulation received more satisfactory control effect; Finally, this paper will be based on neural network integration into the design of a fuzzy controller and its simulation .Experiments show that optimized the ship fuzzy neural controller works from the previous fuzzy controller has better dynamic performance and steady-state performance.