Based On The Embedded Temperature Control System And Algorithm

Surface mounting technology (SMT) is used to mount the electronic components onthe PCB. It treat of the components,mounting equipment,soldering measure andmaterials, and it also has been considered as a revolution in electronic mounting fields. With lead-free development of international IT industry and IC chip technical improvement, the new request to electronic information products lead-free technology that is availability in reflow jointing have brought forward: jointing lead-free solders Making use of more advanced control method under the condition of high temperature, high temperature difference, temperature equation, temperature flexibility and perpendicularity bakes, to realize the goal of enhancing the products' quality and saving the energy.This paper designed the temperature control system based on embedded , first introduced the hardware structure of the temperature control , and designed the main circuit, adopt the LPC2212 as the core processor of the temperature control system, running speed and handling complex data have many SCM unmatched performance, in reflow transplant the embedded real-time operating systemμC/OS-II, set up a task management platform, through real-time kernel to schedule and manage the tasks , to complete the control of the reflow soldering tasks, the design of industrial control systems useμC/OS- II as operating platform, can be overcome traditional Taiwan before and after the introduction of control and difficult to interrupt response by the good way to resolve the real-time response poor, low-efficiency control weaknesses. Actual operating results show that the system has good stability, high reliability, friendly Man-machine Interface, easy maintenance.The problem of parameters optimization is involved in many scientific, engineering and economic fields. founding on this temperature control system,evolutionary algorithm is proposed based on the PID tuning strategy, focused on genetic algorithms and particles swarm algorithm, the genetic algorithm PID turning strategy have been brought forward. It can optimize the system model structure through the self-learning ability, and turn up the optimized parameter of the model. The paper utilize the step response simulate curves of the Integral-Separated PID algorithm to comparing to the effect, finally, PSO is used to optimize the PID parameters, The simulation results show that the algorithm short response time, stability, convergence, high accuracy, easy to concurrentoperation. It is an ideal method for optimizing PID parameters.