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Optimal PIP Control of a pH Neutralization Process Based on State-Dependent Parameter Model

机译：基于状态相关参数模型的pH中和过程的最优PIP控制

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In this paper, an optimal Proportional-Integral-Plus (PIP) controller based on State-Dependent Parameter (SDP) model is developed to control a highly nonlinear and time-varying pH neutralization process. Since the reaction invariants of the pH process are unavailable for direct measurement, a state observer is required for their estimation. Unfortunately, a closed-loop state observer cannot be designed for the pH process due to the decoupled nature of the reaction invariant dynamics. However, this problem is circumvented by engaging the power of State Variable Feedback (SVF) in the context of a Non-Minimum State Space (NMSS) framework. Furthermore, to compensate for process nonlinearities and unmeasured disturbances, an SDP model is identified using data collected from open-loop experiment, and a straightforwardly tuned optimal PIP controller is subsequently designed based on the SDP model to obtain the SDP-PIP controller. For benchmark purposes, a digital PI controller is designed and results are compared with those from the SDP-PIP controller. Simulation results show that SDP-PIP outperforms PI both in set point and disturbance changes.
机译：本文研究了一种基于状态相关参数（SDP）模型的最优比例积分加法（PIP）控制器，以控制高度非线性且随时间变化的pH中和过程。由于无法直接测量pH过程的反应不变性，因此需要状态观察器进行估计。不幸的是，由于反应不变动力学的解耦性质，不能为pH过程设计闭环状态观察器。但是，通过在非最小状态空间（NMSS）框架中使用状态变量反馈（SVF）的功能可以避免此问题。此外，为了补偿过程的非线性和不可测的干扰，使用从开环实验收集的数据识别SDP模型，然后基于SDP模型设计直接调整的最佳PIP控制器，以获得SDP-PIP控制器。为了进行基准测试，设计了数字PI控制器，并将结果与​​SDP-PIP控制器的结果进行比较。仿真结果表明，SDP-PIP在设定点和干扰变化方面均优于PI。

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