An on-line process dead-time estimation algorithm

Abstract: An algorithm has been developed estimating the process dead-time within a closed-loop time invariant system. This paradigm allows for the estimation of the process dead-time without the need for open-loop tests or disabling the controller. The algorithm can estimate the process dead-time in the presence of noise within the control loop increasing the applicability to industrial applications. The process dead-time estimate can replace the constant dead-time assumptions in the control performance assessments, such as the dead-time constant in the Harris Index calculation.

Published in: Control Conference (ASCC), 2017 11th Asian

A methodology to determine the dynamic relationship between process and manipulated variables

Abstract: A methodology has been developed that identifies how pairing the process and manipulated variables will improve process performance. Within an industrial processing plant there are many challenges to determining the strategy of the controller. Some of the challenges include the identification of the existence of a control loop, the operating mode of the control loop (manual versus automatic) and the desired coupling of the process variables within the industrial plant to maximize production performance. A demonstration of this methodology illustrates the potential improvement to be realised within an industrial plant.

Extending the Harris Index performance assessment technique: A plant-wide focus

Abstract: Industrial plant-wide control performance assessment challenges are discussed, illustrating the need to extend the Harris Index control performance technique. This paper proposes two paradigms, the first being designed to increase the accuracy of the Harris Index by extracting the process dead time from closed loop operating data and eliminating the need for generalized prediction horizon constants. The second paradigm is aimed at extending the Harris Index assessment technique to a plant-wide system, without the requirement for process or control system knowledge.

Conference: 2016 Australian Control Conference (AuCC)

On the industrial plant performance & operating point drifting phenomenon

Abstract: The effective performance of various processing plants is reliant on many contributing factors. Such factors include equipment availability and operating performance, operating practices, technical influence and the ability to control the process in a consistent and high performing manner. Operating objectives need to be established to allow for product quality and throughput targets to be achieved throughout. This paper elaborates on an assessment of various categories of plants to demonstrate the wide dominance of the theme and aims to assess the performance of specific industrial plants, namely, Coal Handling Preparation Plants and Bauxite Beneficiation Plants against these parameters. The assessment will focus on the process as well as the control schemes supporting these process objectives.

Published in: Control Conference (ASCC), 2015 10th Asian