output part
2.When we apply fuzzy control to a unknow process,we can"t find good control rule because of we don"t know it"s characteristics.This paper based on an analytic structure of fuzzy controller put forward a method,which combines fuzzy controller and neural network.Use neural network to make identification of system and provide necessary message for LS.Regard control object as an output part of network.Based on message provided by neural network adopt BP algorithm to modify experience rule.Thus,improve dynamic process of fuzzy control system.Simulation results indicate：this controller has better adaptability for variety of model parameters and can modify original system control rule,makes a output follow system input tracks faster.
8.At first using the method of inverse kinematical analysis, the computing formulae of displacement, velocity and acceleration of each component in the seven-bar mechanism and variation law of motion for the two expanding and contracting bar were derived, and then combining with analytical living example and according to the motion law of output component the motion law of driving part was computed, finally the transmission error was analyzed.
