According to actual components,a dynamic mathematical model describing the electrode regulating system of an electric arc furnace was developed.Then,the fuzzy-integral compound controller based on variable universe was designed because of the various control performance requirements of the electrode regulation in different melting stages,the controlled object's own characteristics and the steady state error.Based on the electrode regulating system model,the fuzzy-integral compound control based on variable universe and the traditional proportional-integral-derivative(PID) control were simulated respectively in Simulink environment.The simulation results show that the proposed controller,compared with the effect of the traditional PID control,can achieve better performance.

For Hammerstein-Wiener nonlinear systems with input and output constraints,a nonlinear predictive control algorithm based on T-S fuzzy model was proposed.A Lyapunov function is used to analyze system stability.By establishing the T-S fuzzy model,the nonlinear optimization problem in predictive control design is transformed into a corresponding linear optimization problem.By designing offline the state feedback control law and online implementation of the appropriate feedback control law,online computational efficiency is greatly improved.Simulation trials indicate the effectiveness of the proposed algorithm.

For Hammerstein-Wiener nonlinear systems with the input and output constraints, the T-S fuzzy model is established, and then a nonlinear predictive control algorithm based on piecewise Lyapunov function is proposed. By constructing the piecewise Lyapunov function, the stability of nonlinear system is analyzed and the conversation of common quadratic Lyapunov function is reduced. By offline designing the piecewise feedback control law and online implementing the appropriate feedback control law, the online computational efficiency is improved greatly. The simulation results show the effectiveness of the proposed algorithm.

Many actual systems are often represented as the Hammerstein-Wiener nonlinear models, where a linear dynamic subsystem is surrounded by two static nonlinear subsystems at its input and output. For Hammerstein-Wiener nonlinear systems with the input and output constraints, a predictive control synthesis algorithm based on polytopic terminal region is proposed. At the offline stage, by constructing a series of the polytopic invariant sets, the terminal region is enlarged; in the polytopic invariant set, the nonlinear controller is designed, then the conservation of conventional linear control law design is reduced. At the online stage, by solving a finite number of linear matrix inequality optimization problems, not only the real-time demand can be satisfied, but also the control performance can be improved. Simulation results show the advantages of adopting polyhedron invariant set. Copyright © 2011 Acta Automatica Sinica.

Dead zone exists in electrode regulating system of electric arc furnace,which can bring the steady-state error to control system and even cause the instability of system.Therefore,for the dead zone nonlinearity with asymmetric breakpoint and unequal slope,an adaptive dead zone compensation method is proposed.By introducing the dead zone inverse nonlinearity and updating the unknown dead zone inverse parameters on-line,dead zone is compensated completely.The convergence of parameter estimation error is proved by using Lyapunov method.The simulation results show the effectiveness of the proposed algorithm.

Dead-zone nonlinearity exists in many practical systems,which deteriorates the performance of control system and even causes the instability of the system.In order to compensate the dead-zone nonlinearity in the dynamic system, a dead-zone compensation control algorithm based on adaptive dynamic radial basis function network(DRBF)is presented for eliminating the undesirable effects caused by the unknown dead-zone.A linear controller paralleled with the DRBF network is designed for the compensated dynamic system.The closed-loop system stability is proved by Lyapunov method. The simulation research was performed in a hydraulic system.The results show that this proposed algorithm effectively eliminates the steady-state error,reduces the computation complexity,and makes the control signal less oscillatory.