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Darby M.,CMiD Solutions | Nikolaou M.,University of Houston
17th Topical on Refinery Processing 2014 - Topical Conference at the 2014 AIChE Spring Meeting and 10th Global Congress on Process Safety | Year: 2014

Benefit of higher amplitude, correlated input signals - Parameter accuracy & IC stability. D-opt ≈ IC-opt→ implement D-optimal convex - Can use IC bound as check. Formulated a tractable optimization problem. Can replace today's uncorrelated designs. Source


Darby M.L.,CMiD Solutions | Nikolaou M.,University of Houston
Control Engineering Practice | Year: 2014

The design of plant tests to generate data for identification of dynamic models is critically important for development of model-based process control systems. Multivariable process identification tests in industry continue to rely on uncorrelated input signals, even though investigations have shown the benefits of other input designs which lead to correlated, higher-amplitude input signals. This is partly due to difficulties in formulating and solving computationally tractable problems for identification test design. In this work, related results are summarized and extended. Connections between different designs that target D-optimality or integral controllability are established. Related concepts are illustrated through simulation case studies. © 2013 Elsevier Ltd. Source


Darby M.L.,CMiD Solutions | Nikolaou M.,University of Houston | Jones J.,Chevron | Nicholson D.,IPCOS UK Ltd.
Journal of Process Control | Year: 2011

The practice of implementing real-time optimization (RTO) using a rigorous steady-state model, in conjunction with model predictive control (MPC), dates back to the late 1980s. Since then, numerous projects have been implemented in refinery and chemical plants, and RTO has received significant attention in the industrial and academic literature. This history affords us the opportunity to assess the impact and success of RTO technology in the process industries. We begin with a discussion of the role RTO serves in the hierarchy of control and optimization decision making in the plant, and outline the key steps of the RTO layer and the coordination with MPC. Where appropriate, we point out the different approaches that have been used in practice and discuss the success factors that directly relate to the success of RTO within an organization. We also discuss alternative approaches that have been used to alleviate some of the challenges associated with implementing RTO and which may be appropriate for those unwilling to commit to the traditional RTO approach. Lastly, we provide suggestions for improvement to motivate further research. © 2011 Elsevier Ltd. All rights reserved. Source


Conz V.,Braskem | Fuchs S.,Braskem | Moura P.M.,Braskem | Darby M.,CMiD Solutions | Nicholson D.,IPCOS UK Ltd.
AIChE Ethylene Producers Conference Proceedings | Year: 2012

Braskem is the 8th largest petrochemical company in the world and the biggest producer of polymers in the Americas. The Braskem Triunfo site includes 2 Naphtha Crackers with a combined capacity of 1250 KTA ethylene and 685 KTA propylene. AspenTech DMCplus® controllers had been built for both plants over the past 10 years, but were not fully operational. In 2010 a project was initiated to review the performance of the advanced control systems and improve their operability, service factor and economic impact. A further objective was to increase the knowledge of the site process control engineers. This paper gives an overview on the project, including the basis for deciding which areas to focus on, changes made at both the regulatory and advanced control level, and the results obtained. Changes in operational philosophies which improved process stability and efficiency are discussed. Techniques and tools used in the project are highlighted. Source


Dittmar R.,Applied Information Sciences | Gill S.,IPCOS BV | Singh H.,IPCOS BV | Darby M.,CMiD Solutions
Control Engineering Practice | Year: 2012

Modern process plants are highly integrated and as a result, decentralized PID control loops are often strongly interactive. The iterative SISO tuning approach currently used in industry is not only time consuming, but does also not achieve optimal performance of the inherently multivariable control system. This paper describes a method and a software tool that allows control engineers/technicians to calculate optimal PID controller settings for multi-loop process systems. It requires the identification of a full dynamic model of the multivariable system, and uses constrained nonlinear optimization techniques to find the controller parameters. The solution is tailored to the specific control system and PID algorithm to be used. The methodology has been successfully applied in many industrial advanced control projects. The tuning results that have been achieved for interacting PID control loops in the stabilizing section of an industrial Gasoline Treatment Unit as well as a Diesel Desulfurization plant are presented. © 2011 Elsevier Ltd. Source

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