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Soft Sensors for Monitoring and Control of Industrial Processes

Soft Sensors for Monitoring and Control of Industrial Processes
Author: Luigi Fortuna
Publisher: Springer Science & Business Media
Total Pages: 284
Release: 2007-05-31
Genre: Technology & Engineering
ISBN: 1846284805
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This book reviews current design paths for soft sensors, and guides readers in evaluating different choices. The book presents case studies resulting from collaborations between the authors and industrial partners. The solutions presented, some of which are implemented on-line in industrial plants, are designed to cope with a wide range of applications from measuring system backup and what-if analysis through real-time prediction for plant control to sensor diagnosis and validation.

Soft Sensors for Monitoring and Control of Industrial Processes

Soft Sensors for Monitoring and Control of Industrial Processes
Author: Luigi Fortuna
Publisher: Springer
Total Pages: 271
Release: 2009-10-12
Genre: Technology & Engineering
ISBN: 9781848005419
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This book reviews current design paths for soft sensors, and guides readers in evaluating different choices. The book presents case studies resulting from collaborations between the authors and industrial partners. The solutions presented, some of which are implemented on-line in industrial plants, are designed to cope with a wide range of applications from measuring system backup and what-if analysis through real-time prediction for plant control to sensor diagnosis and validation.

Application of Soft Sensors in Process Monitoring and Control

Application of Soft Sensors in Process Monitoring and Control
Author: Ajaya K. Pani
Publisher:
Total Pages: 0
Release: 2010
Genre:
ISBN:
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A major problem in product quality control in process industries is the difficulty of continuous online measurement of certain output variables especially related to composition. Although analytical instruments are available in some cases, significant time delays associated with most of such instruments make timely control difficult and sometimes impossible. Soft sensor is a modeling approach to estimate hard-to-measure process variables (primary variables) from easy-to-measure online process variables (secondary variables). The important steps of soft sensor development are collection of historical plant data for different variables and their processing, development of a model based on the available data and validation of the model. This paper presents the need and advantages of soft sensor implementation in process industries and does a critical review of various techniques available for data handling and modeling.

Advanced Control and Supervision of Mineral Processing Plants

Advanced Control and Supervision of Mineral Processing Plants
Author: Daniel Sbárbaro
Publisher: Springer Science & Business Media
Total Pages: 327
Release: 2010-08-20
Genre: Technology & Engineering
ISBN: 1849961069
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Advanced Control and Supervision of Mineral Processing Plants describes the use of dynamic models of mineral processing equipment in the design of control, data reconciliation and soft-sensing schemes; through examples, it illustrates tools integrating simulation and control system design for comminuting circuits and flotation columns. Coverage is given to the design of soft sensors based on either single-point measurements or more complex measurements like images. Issues concerning data reconciliation and its employment in the creation of instrument architecture and fault diagnosis are surveyed. In consideration of the widespread use of distributed control and information management systems in mineral processing, the book describes the platforms and toolkits available for implementing such systems. Applications of the techniques described in real plants are used to highlight their benefits; information for all of the examples, together with supporting MATLAB® code can be found at www.springer.com/978-1-84996-105-9.

Soft Sensors for Process Monitoring of Complex Processes

Soft Sensors for Process Monitoring of Complex Processes
Author: Mitchell Roy Serpas
Publisher:
Total Pages:
Release: 2012
Genre:
ISBN:
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Soft sensors are an essential component of process systems engineering schemes. While soft sensor design research is important, investigation into the relationships between soft sensors and other areas of advanced monitoring and control is crucial as well. This dissertation presents two new techniques that enhance the performance of fault detection and sensor network design by integration with soft sensor technology. In addition, a chapter is devoted to the investigation of the proper implementation of one of the most often used soft sensors. The performance advantages of these techniques are illustrated with several cases studies. First, a new approach for fault detection which involves soft sensors for process monitoring is developed. The methodology presented here deals directly with the state estimates that need to be monitored. The advantage of such an approach is that the nonlinear effect of abnormal process conditions on the state variables can be directly observed. The presented technique involves a general framework for using soft sensor design and computation of the statistics that represent normal operating conditions. Second, a method for determining the optimal placement of multiple sensors for processes described by a class of nonlinear dynamic systems is described. This approach is based upon maximizing a criterion, i.e., the determinant, applied to the empirical observability gramian in order to optimize certain properties of the process state estimates. The determinant directly accounts for redundancy of information, however, the resulting optimization problem is nontrivial to solve as it is a mixed integer nonlinear programming problem. This paper also presents a decomposition of the optimization problem such that the formulated sensor placement problem can be solved quickly and accurately on a desktop PC. Many comparative studies, often based upon simulation results, between Extended Kalman filters (EKF) and other estimation methodologies such as Moving Horizon Estimation or Unscented Kalman Filter have been published over the last few years. However, the results returned by the EKF are affected by the algorithm used for its implementation and some implementations may lead to inaccurate results. In order to address this point, this work provides a comparison of several different algorithms for implementation.

Control in Bioprocessing

Control in Bioprocessing
Author: Pablo A. López Pérez
Publisher: John Wiley & Sons
Total Pages: 296
Release: 2020-03-03
Genre: Technology & Engineering
ISBN: 1119296080
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Closes the gap between bioscience and mathematics-based process engineering This book presents the most commonly employed approaches in the control of bioprocesses. It discusses the role that control theory plays in understanding the mechanisms of cellular and metabolic processes, and presents key results in various fields such as dynamic modeling, dynamic properties of bioprocess models, software sensors designed for the online estimation of parameters and state variables, and control and supervision of bioprocesses Control in Bioengineering and Bioprocessing: Modeling, Estimation and the Use of Sensors is divided into three sections. Part I, Mathematical preliminaries and overview of the control and monitoring of bioprocess, provides a general overview of the control and monitoring of bioprocesses, and introduces the mathematical framework necessary for the analysis and characterization of bioprocess dynamics. Part II, Observability and control concepts, presents the observability concepts which form the basis of design online estimation algorithms (software sensor) for bioprocesses, and reviews controllability of these concepts, including automatic feedback control systems. Part III, Software sensors and observer-based control schemes for bioprocesses, features six application cases including dynamic behavior of 3-dimensional continuous bioreactors; observability analysis applied to 2D and 3D bioreactors with inhibitory and non-inhibitory models; and regulation of a continuously stirred bioreactor via modeling error compensation. Applicable across all areas of bioprocess engineering, including food and beverages, biofuels and renewable energy, pharmaceuticals and nutraceuticals, fermentation systems, product separation technologies, wastewater and solid-waste treatment technology, and bioremediation Provides a clear explanation of the mass-balance–based mathematical modelling of bioprocesses and the main tools for its dynamic analysis Offers industry-based applications on: myco-diesel for implementing "quality" of observability; developing a virtual sensor based on the Just-In-Time Model to monitor biological control systems; and virtual sensor design for state estimation in a photocatalytic bioreactor for hydrogen production Control in Bioengineering and Bioprocessing is intended as a foundational text for graduate level students in bioengineering, as well as a reference text for researchers, engineers, and other practitioners interested in the field of estimation and control of bioprocesses.

PID Control for Industrial Processes

PID Control for Industrial Processes
Author: Mohammad Shamsuzzoha
Publisher: BoD – Books on Demand
Total Pages: 220
Release: 2018-09-12
Genre: Technology & Engineering
ISBN: 1789237009
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PID Control for Industrial Processes presents a clear, multidimensional representation of proportional - integral - derivative (PID) control for both students and specialists working in the area of PID control. It mainly focuses on the theory and application of PID control in industrial processes. It incorporates recent developments in PID control technology in industrial practice. Emphasis has been given to finding the best possible approach to develop a simple and optimal solution for industrial users. This book includes several chapters that cover a broad range of topics and priority has been given to subjects that cover real-world examples and case studies. The book is focused on approaches for controller tuning, i.e., method bases on open-loop plant tests and closed-loop experiments.

Development of soft sensors for monitoring and control of bioprocesses

Development of soft sensors for monitoring and control of bioprocesses
Author: Robert Gustavsson
Publisher: Linköping University Electronic Press
Total Pages: 55
Release: 2018-10-31
Genre:
ISBN: 9176852075
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In the manufacture of bio-therapeutics the importance of a well-known process is key for a high product titer and low batch to batch variations. Soft sensors are based on the concept that online sensor signals can be used as inputs to mathematical models to derive new valuable process information. This information could then be used for better monitoring and control of the bioprocess. The aim of the present thesis has been to develop soft sensor solutions for upstream bioprocessing and demonstrate their usefulness in improving robustness and increase the batch-to-batch reproducibility in bioprocesses. The thesis reviews the potential and possibilities with soft sensors for use in production of bio-therapeutics to realize FDA´s process analytical technology (PAT) initiative. Modelling and hardware sensor alternatives which could be used in a soft sensor setup are described and critically analyzed. Different soft sensor approaches to control glucose feeding in fed-batch cultures of Escherichia coli are described. Measurements of metabolic fluxes and specific carbon dioxide production was used as control parameters to increase product yield and decrease the variability of produced recombinant proteins. Metabolic heat signals were used in uninduced cultures to estimate and control the specific growth rate at a desired level and thereby also estimate the biomass concentration online. The introduction of sequential filtering of the signal enabled this method to be used in a down-scaled system. The risk and high impact of contaminations in cell cultures are also described. An in situ microscope (ISM) was used as an online tool to estimate cell concentration and also to determine cell diameter size which enabled the detection of contaminant cells at an early stage. The work presented in this thesis supports the idea that soft sensors can be a useful tool in the strive towards robust and reliable bioprocesses, to ensure high product quality and increased economic profit.

Fault Detection and Diagnosis in Industrial Systems

Fault Detection and Diagnosis in Industrial Systems
Author: L.H. Chiang
Publisher: Springer Science & Business Media
Total Pages: 281
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 1447103475
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Early and accurate fault detection and diagnosis for modern chemical plants can minimize downtime, increase the safety of plant operations, and reduce manufacturing costs. This book presents the theoretical background and practical techniques for data-driven process monitoring. It demonstrates the application of all the data-driven process monitoring techniques to the Tennessee Eastman plant simulator, and looks at the strengths and weaknesses of each approach in detail. A plant simulator and problems allow readers to apply process monitoring techniques.