Optimization Of Multi-Objective Fuzzy Control And Application In Vehicle Control

Optimization of Multi- Objective Control for nonlinear systems, charged with object model unknown circumstances, a feasible objective function and system response was built to describe the relationship between the process, and was applyed to design multi-objective fuzzy controller. According to the control system quirements, a control function or an object state with control input function was established, so that each control objectives can be achieved in terms of a compromise "satisfied" optimal.Relevant literature about the degree support of single goal to rules was first cited in this paper, then the definition of the supporting degree for a rule to one object put forward in some literatures was extended. It was 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. MIMO Mamdani fuzzy controller as a universal approximation, was used to approximate the optimal control solution. According satisfactory solution principle in the literature cited the relevant definition of Pareto rules. Because the establishment of fuzzy control rules-based is the key of control algorithm, put the multi-objective optimization control problem into the Pareto rules-basis access issues, the control approximation solution of the control objectives or control function can be get from the fuzzy control algorithm based on the rules-basis. A Pareto rules-basis search method was present in this paper, the concept of satisfied function was defined.First, for controller input language variables membership function of the basic composition,and the corresponding output language variables basis points in the membership function of each group constitutes a basis rules, at basis point active rules,separately calculated the support degree of rules to every single objective after a sampling period, and then each target standardized, in accordance with the objectives of the importance or priority, separately gave different weights, according to a compromise get the integrated support of all the pareto rules. Search the maximum integrated support as the outcome result, the optimal response correspond results of the rules shall be Pareto optimal rules, all of this search to Pareto optimal rules constitute a Pareto rules-basis. Based on the rules of the Pareto optimal control algorithm is a nearly optimal Pareto control algorithm.Based on the above algorithm,a control and simulation based on Michael's dynamics simulation model vehicles was given in this paper.The methods selected for vehicles popular fuzzy Control. Firstly,defined and analysised vehicle Model multiple targets, and assuming that the vehicles around installed the visual based on machine vision systems, Then, imitate excellent driving experience, the speed of vehicles was quantified for a number of grades,search the control rules weighted linear optimization based on controller membership function for a certain parameters on the different objectives,gave search algorithm and search procedures.Based on this,obtained the optimal pareto rule basis of vehicle.The rule basis is of the application,suitable for certain road's safty and high-speed driving.Finally,based on the rule basis used Mamdani-fuzzy control algorithm to approximate the optimal solution,and tried a simulation test in Matlab,obtained the track curves and output curves of vehicle driving.Through different traffic conditions' test showed that the multi-objective optimization of fuzzy Control Strategy's effectiveness. Finally, the validation analysis of multi-objective optimization method based on linear weighted control systems was given in this paper , further validated the effectiveness of this method.