Study On TS-PID Fuzzy Control Method For The Smelting Process Of Electroslag Furnace

Electroslag re-melting is a special melting method for mental and mental alloy, and the steel produced by this method has many marked advantages, such as high purity, uniform components, dense organization, good mechanical property and so on, also, it is widely used in aviation, spaceflight, war industry, energy industry and some special requirement occasions. In order to get high quality re-melting ingot, some control parameters, such as melting current, melting voltage, melting rate and the depth that the electrode dipped into the slag pool etc, must be controlled accurately. Meanwhile, we must make sure that the re-melting process is stable and reliable. All those require a reasonable control method and parameters optimization algorithm.Based on the rich practical control experiences of classic PID control, in consideration of some actual problems existing in production practice, and combined with the unique characteristics of process control model of electroslag re-melting, this paper designs a TS-PID fuzzy controller which can optimize parameters based on genetic algorithm. This design is different from others in following aspects:Firstly, compared with PID control method, fuzzy intelligent control method is more suitable to control the complex object modals like electroslag melting that have multivariable, time-varying parameters, nonlinear factors, and strong random disturbances for its flexible and strong adaptable characteristics. Secondly, the fuzzed design method for fuzzying input variables just suitably applied to solve problems how to deal with the transition between different stages during re-melting procedures. Thirdly, this paper choose combed PID form output method to design T-S fuzzy rules, on the one hand, the control parameters’determination of the rules can absorb the rich practical knowledge of the PID parameter’setting, on the other hand, this new fuzzy controller also keep the good character of PID controller, simple and effective, for example. Fourthly, on the problem of how to choose the accurate parameters of the rules, this paper uses genetic intelligent optimization algorithm to find the optimal value. According to the given optimization performance index, the genetic algorithm perform its optimization study on the controlled object. Searching in a certain value range of parameters, which is determined by the practical experiences of the knowledge, not only ensure that we can get the optimal solution, but also can speed up convergence of the searching. With the optimized parameters of the rules, we can get the more satisfactory control performance.Under the simulation environment of the matlab, the paper builds the simulation modals of the system, and conducts an experiment to analysis the results. The results show that the control system has good tracking performance and high steady precision. At every stage of melting process, the fluctuation of current is reduced obviously. In short, the systerm controls smoothly and reliably. With this new control method, we can get qualified re-melting ingot and reduce the specific energy consumption. It is of great significace for the electricity slag enterprises to improve their economic benefit, meanwhile, it also provides a worth industrial method for the complex optimization control of the industrial process.