基于近似模型的电弧炉解耦控制器

针对电弧炉电极调节系统,提出了基于近似模型的解耦控制策略.首先,选取弧长为状态变量,推导电极调节系统的状态方程,由Taylor展开技术,得到系统的近似模型.由近似模型直接推导近似逆控制律,实现三相之间的解耦,并避免了在线辨识逆模型计算量过大的问题.由于状态不能直接测量,利用扩展卡尔曼状态估计方法得到系统状态.另外,在内模结构中引入非线性补偿,保证了系统的鲁棒性.系统的稳定性通过Lyapunov方法进行了分析,最后的仿真结果验证了控制器的有效性.

Approximate-model-based decoupling controller for electric arc furnace

A decoupling strategy based on the approximated model is proposed for regulating electrodes in an arc furnace. The mathematical model of the system in state-space form is built, in which the length of electrical arc is considered the state variable. An approximate model is derived via the Taylor expansion. From the approximate model, the approximate inverse control strategy is derived for eliminating the coupling in the three-phase arc furnace. Thus, the learning of the inverse process dynamics is not required. Because not all states are accessible, a neural network model-based extended Kalman observer is used to estimate the states. In addition, uncertainty compensation in the internal-model structure is introduced to improve the robustness of the system. The stability is proved by using the Lyapunov method. The proposed nonlinear controller is verified by computer simulations.