UBC Theses and Dissertations
Algorithm for nonlinear process monitoring and controller performance recovery with an application to semi-autogenous grinding McClure, Kenneth Scott
Chemical and mineral processing industries commonly commission linear feedback controllers to control unit processes over a narrow and linear operating region where the economy of the process is maximized. However, most of these processes are nonlinear outside of this narrow operating region. In the event of a large unmeasured disturbance, a process can shift away from nominal and into an abnormal operating region. Owing to the nonlinearity of these processes, a linear controller tuned for the nominal operating region will perform poorly and possibly lead to an unstable closed-loop system in an abnormal operating region. Moreover, it is often difficult to determine whether a process has shifted to an abnormal operating region if none of the constraints on the measured process outputs are violated. In these events, it is the operator who must detect and recover the process, and this manual response results in a sub-optimal recovery. This thesis develops and demonstrates a control strategy that monitors several process variables simultaneously and provides an estimate of the process shift to a nonlinear abnormal operating region where a linear recovery controller is implemented to recover the process back to nominal. To monitor the process, principal component analysis is proposed for process shifts that can be detected by linear variable transformations. Alternatively, for nonlinear or high-dimensional processes, locally linear embedding is proposed. Once a process shift to an abnormal operating region is detected, the control strategy uses the estimate of the process shift in a recovery controller to recover the process. In the event the linear recovery controller is unable to recover the process, an expert system overrides the recovery controller to return the process to a recoverable region. A case study on a semi-autogenous grinding mill at a processing facility in British Columbia presents the successful application of the control strategy to detect and recover the mill from overloading. Portions of this control strategy have been implemented at this facility, and it provides the operators with a real-time estimate on the magnitude of the mill overload.
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