Sirocco-circumfluence Soldering System Temperature Control Based On Fuzzy Neural Networks

Sirocco-circumfluence soldering system is the important equipment ofSurface Mount Technology (SMT). The temperature dynamic-characteristic of thesystem has influenced the quality of production directly. In production, theprocedure of the system has many characters such as time variable, nonlinear andindefinite. In the paper, a Fuzzy Neural Networks Controller (FNNC) connectedparallel with general PID controller has been used to improve the adaptive andanti-jamming ability, avoid the general PID control disfigurement, e.g. slowlyresponse, bad control stability and overrun, and get good effects.Fuzzy logic has virtue of expressing knowledge easily, neural networks hasgood self-learning ability. A kind of new controller——Fuzzy Neural NetworksController (FNNC) has been designed by combining the virtue of these twotechniques. In traditional fuzzy control, unsuitable selected membership function andfuzzy rules will induce the control disfigurement, but the Fuzzy Neural NetworksController has avoided it. It has clear structure, good self-learning and nonlinear mapability. Considered the characteristic of Sirocco-circumfluence soldering system, aNeural Networks Predictor(NNP) has been designed to predict the output ofcontrolled system,then the controller will forecast the change trend of controlledsystem ,and adjust the system in advance. At last, establish the model of Sirocco-circumfluence soldering system forsimulation with Matlab, simulation is done for general PID control system, FuzzyNeural Network Control system compound contro(lPID+FNNC) and Fuzzy NeuralNetwork Control system compound control equipped Neural Networks Predictor(PID+FNNC+NNP)with Matlab. The result approved the Fuzzy Neural NetworkControl system compound control equipped Neural Networks Predictor(PID+FNNC+NNP)has the best control effect.