The Study Of Multi-Object Optimal Control On Application In Vehicle Control

As a basis, the definition of object and multi-object are firstly studied in this paper, as well as their relations. Then the definition of the supporting degree for a rule to one object put forward in some literatures is extended. It is announced that the supporting degree for a rule to one object should be the favoring degree of the system response function to certain object during a time period instead of a time instant. Then the definitions of Pareto rule and Pareto rule base put forward in some literatures are also quoted, following the conclusion that to solve the optimization control problem equals to build a Pareto rule base. A method to obtain the Pareto rule base is put forward. Supporting degree of different rules with same response region to each object should be firstly obtained. Then different weight should be endowed to each object manually according to different importance or priority objects. Then a compromise supporting degree can be reached. A Pareto rule base composed of such best Pareto rules can be set up.Automatic vehicle driving on the current research are generally based on the visual. It installs video cameras in the car, using computer vision technology, modeled on the visual mechanisms adopted to deal with the camera lens to capture images, and access to information. According to the information used in the strategy we can achieve the corresponding vehicle driving control. Allattempts under way to the precise mathematical models and the initial location of vehicles using more ambiguous optimize control strategy to achieve the objectives of the automatic vehicle driving. In order to solve the optimization control problem that a car drive on a closed path, we pick-up the mathematical model of path according to the practical condition and the need of this thesis firstly, and then we define and analyze the multiple objects of the model and find the Pareto rule base of the model. At last, this thesis designs a fuzzy controller of double-input and double-output. Some experiments have been done on some paths, and the ultimate results show the validity of the control and control algorithm.