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以金氰化浸出过程为背景,基于物料守恒方程建立动态机理模型,用Tikhonov正则化方法估计动力学反应速度,进而辨识模型未知参数,有效降低了测量噪声对估计及辨识结果的影响;采用实时优化约束自适应方法减小模型参数失配对优化结果的影响.仿真结果表明,在模型参数失配时,所提出的方法仍能收敛到实际过程的最优设定点,不必求实际数据梯度,且受噪声影响小,便于实际应用,为湿法冶金全流程优化控制的顺利实施奠定了基础.
Taking the gold cyanide leaching process as the background, a dynamic mechanism model was established based on the material conservation equation, and the kinetic reaction rate was estimated by Tikhonov regularization method. Then the unknown parameters of the model were identified and the influence of measurement noise on the estimation and identification results was effectively reduced. The results show that the proposed method can still converge to the optimal set point of the actual process when the model parameters are mismatched, without the need of the actual data gradient, Which is less affected by noise and is convenient for practical application. It has laid a foundation for the smooth implementation of optimization control of the whole hydrometallurgical process.