تجزیه و تحلیل حساسیت جهانی از از مدل فرایند تصادفی بازخورد کنترل شده

The purpose of the study was to investigate whether global sensitivity analysis can be utilised in concurrent process and control design to gain insight into the process and its control. This paper addresses the issue of sensitivity of a control law performance to its parameters in a dynamic, hybrid deterministic–stochastic process model. The control law under investigation is a collection of single-input, single-output type tower level controllers in a papermaking process. Global sensitivity analysis is shown to attribute higher importance to certain key parameters, thus providing valuable insight for the designer.

This paper examines global sensitivity analysis (GSA) of a mill-wide control system. The purpose of this work was to investigate the potential of GSA in guiding design work in concurrent process and automation design. The current work relates to a simulation and optimisation based design framework under development, see [10], [18], [8] and [14]. Although concurrent design has been widely studied (see, e.g., [2] and [11] and the literature therein), in practice process design typically begins with flowsheet and equipment design, with the control of the process left as a later consideration. In contrast, the framework under development strives to start the control design as early as possible. This means that dynamic simulation models are needed early on in the design, even though not all relevant information is yet available. Consequently, the models contain a significant amount of uncertainty, especially with regard to their control system parts. This also means, therefore, that any further understanding of the model’s behaviour is useful in the later phases of design, such as in process and control optimisation. The purpose of this paper is thus to investigate what insight can be gained by applying global sensitivity analysis during the early phases of process and automation design. In this study we restrict the analysis to the control system of the model. This restriction is made since, as mentioned above, this part of the model is likely to contain the largest uncertainty. The aim of this paper is not to analyse one control loop at a time, as many methods and tools are available for that purpose (see, e.g., [15]). Rather, we take a systemic view, analysing several control loops and the process simultaneously. The studied case originates from the papermaking industry. The case control system provides system-wide control of several large storage towers. As such a control structure has an effect on several areas of the system, it follows that it should be designed together with the process structure as early on as possible. The work presented here relies heavily on simulation models, some of which are stochastic, arising from parts of the studied process for which first principles models are nearly impossible to construct. These models are presented in Section 2. The decision to use partly stochastic models is also justified by the fact that early on in the design of processes and controls, the amount of available information is limited. Thus, the secondary research interest of this paper was to investigate how well global sensitivity could be applied to such models. In addition to simulation models, the present work utilises global sensitivity analysis (GSA), which is outlined in Section 3. Section 4 presents the results of the study, and the final chapter discusses the results.