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OPTIMAL STATE ESTIMATION AND ON-LINE OPTIMISATION OF A BIOCHEMICAL REACTOR

机译:生物化学反应器的最佳状态估计和在线优化

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An on-line optimising control strategy involving a two level extended Kalman filter (EKF) for dynamic model identification and a functional conjugate gradient method for determining optimal operating condition is proposed and applied to a biochemical reactor. The optimiser incorporates the identified model and determines the optimal operating condition while maximising the process performance. This strategy is computationally advantageous as it involves separate estimation of states and process parameters in reduced dimensions. In addition to assisting on-line dynamic optimisation, the estimated time varying uncertain process parameter information can also be useful for continuous monitoring of the process. This strategy ensures that the biochemical reactor is operated at the optimal operation while taking care of the disturbances that are encountered during operation. The simulation results demonstrate the usefulness of the two level EKF assisted dynamic optimizer for on-line optimising control of uncertain nonlinear biochemical systems.
机译:提出了一种在线优化控制策略,该策略包括用于动态模型识别的两级扩展卡尔曼滤波器(EKF)和用于确定最佳运行条件的功能共轭梯度方法,并将其应用于生化反应器。优化器结合了已识别的模型并确定了最佳操作条件,同时使过程性能最大化。该策略在计算上是有利的,因为它涉及在减小的尺寸中分别估计状态和过程参数。除了帮助在线动态优化之外,估计的时变不确定过程参数信息也可用于连续监视过程。该策略确保生化反应器以最佳运行方式运行,同时要注意运行期间遇到的干扰。仿真结果表明,二级EKF辅助动态优化器对于不确定的非线性生化系统的在线优化控制很有用。

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