金氰化浸出过程建模及实时优化自适应策略

Modeling and real-time optimization adaptations for gold cyanidation leaching process

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.

Based on the gold cyanidation leaching process, a dynamic mechanism model is established according to material balance equations. The kinetic reaction rates are estimated by the Tikhonov regularization method, which reduces the propagation of measurement noise effectively. And then the estimated results are used to identify the unknown parameters. To reduce the influence of model uncertainty on real-time optimization （RTO） results, the constraint adaptation method is applied to RTO of leaching process. The simulation results show that this method can track the optimal set point of the actual process under model uncertainty. Moreover, the measurement gradients are unnecessary, which is less influenced by measurement noise and more available for practical applications and has laid an important foundation for the successful implementation of the optimization and control for hydrometallurgy process.