Earch On Control Approaches Of Electrode Regulator System For Electric Arc Furnace

The electrode regulator system is the key link of electric arc furnace steelmaking. By regulating the electrode position, the electric power which is inputed into electric furnace arc can be changed. The rapid and accurate electrode position control is one of the key factors of saving electric energy, shortening smelting period, reducing energy consumption and prolonging lining life. However, electrode regulator system is a complex system with high nonlinearity, parameter time-varying, variable coupling and strong random disturbance. Therefore, the research on modeling and control of electrode regulator system for electric arc furnace has the important theoretical significance and the application value. The main work of this paper is given as follow:(1) For the characteristics of input dead zone nonlinearity, output arc nonlinearity and strong random disturbance, Hammerstein-Wiener models of electrode regulator system are established in chapter2. A parameter identification algorithm based on bias compensation recursive least squares is proposed to identify the unbiased estimation of the original system parameters product vector on line; the tensor product approximation parameter separation method is adopted to compute the parameter values of linear part and nonlinear parts. The proposed method can compensate estimation bias caused by the process noise and get the unbiased estimation of the parameters of electrode regulator system for electric arc furnace, which lay the foundation for the controller design of electrode regulator system.(2) In order to avoid the adverse effect of arc nonlinearity on control performance, the change of arc length is replaced by the change of piston stroke of hydraulic cylinder in chaper3. An electrode lifting controller based on dynamic radial basis function network dead zone compensation is presented. Then system stability is proved by Lyapunov method. The proposed algorithm can not only compensate the harmful effects caused by the dead zone, but also avoid the oscillation of control signal which is good for prolonging actuator service life.(3) The control algorithm given in above chaper is simple, but when material collapse disturbance appears, piston displacement of hydraulic cylinder is inequal to arc length, that is to say the above control method is not fit for the initial stage of smelting. Therefore, a fuzzy PID control method based on adaptive inverse dead zone compensation is presented in chapter 4. The proposed algorithm can not only remove the steady-state error cause by dead zone, but also improve response speed and tracking performance.(4) In the above control algorithms, the dead zone nonlinearity is compensated firstly and the controller is designed secondly, which will have an effect on the control performance of electrode regulator system. In order to improve the control performance, input dead zone nonlinearity, hydraulic linear part and output arc nonlinearity are considered comprehensively in chapter5. Off-Line design on-line synthesis integral predictive control algorithm is presented. Then Lyapunov method is used to prove system stability. In the whole optimization process, not only the time-varying terminal constraint sets are adopted, but also at least one free control variable is introduced. Consequently, the control performance of electrode regulator system can be improved.(5) The actual input and output constraints are both linear inequality constraints, and the ellipsoid set designed in above chapter has the large conservation in processing linear inequality constraints. Therefore, the polytopic set which is suitable to process actual linear inequality constraints is designed in chapter6. The improved off-line design on-line synthesis integral predictive control algorithm based on polytopic set is presented. And then Lyapunov method is utilized to prove system stability. In the polytopic set, the parameter-correlation nonlinear control law is designed, which is not only correlated with the vertices of polytopic invariant set, but also depended on polytopic description predictive model. So the conservation of the common nonlinear control law can be reduced, and the bound of the polytopic stability region can be enlarged. Moreover, under the situation that the real-time is met, the better control performance can be obtained.