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Saturday, November 7, 2020 | History

3 edition of Model-Based Control of Particulate Processes (Particle Technology Series) found in the catalog.

Model-Based Control of Particulate Processes (Particle Technology Series)

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  • 33 Currently reading

Published by Springer .
Written in English

    Subjects:
  • Powder technology,
  • Science/Mathematics,
  • Chemical Engineering Operations,
  • Technology,
  • Technology & Industrial Arts,
  • Chemistry - Industrial & Technical,
  • Engineering - Chemical & Biochemical,
  • Science / Chemistry / Technical & Industrial,
  • Technology / Engineering / Chemical & Biochemical,
  • Applied,
  • Crystallization,
  • Mathematical Models

  • The Physical Object
    FormatHardcover
    Number of Pages229
    ID Numbers
    Open LibraryOL8370318M
    ISBN 101402009364
    ISBN 109781402009365


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Model-Based Control of Particulate Processes (Particle Technology Series) by P.D. Christofides Download PDF EPUB FB2

Particulate processes are characterized by the co-presence of a contin­ uous phase and a dispersed (particulate) phase, and are widely used in industry for the manufacturing of many high-value : Panagiotis D. Christofides. This book - the first of its kind - presents general methods for the synthesis of nonlinear, robust and constrained feedback controllers for broad classes of particulate process models and illustrates their applica­ tions Model-Based Control of Particulate Processes book industrially-important crystallization, aerosol and thermal spray processes.

Introduction. Particulate processes are characterized by the co-presence of a contin­ uous phase and a dispersed (particulate) phase, and are widely used in industry for the manufacturing of many high-value products. Examples include the crystallization of proteins for pharmaceutical applications, the emulsion polymerization reactors for the production of latex, the aerosol synthesis of titania powder used in the production of white pig­ ments, and the thermal spray processing.

Model-Based Control of Particulate Processes by Panagiotis D. Christofides,available at Book Depository with free delivery worldwide.

Model-Based Control of Particulate Processes: Panagiotis D. Christofides: The book is unique in the broad coverage of different model based control strategies and in the variety of applications presented. A special merit of the book is in the included library of dynamic models of several industrially relevant processes, which can be used by both the industrial and academic community to study and implement advanced.

While most of the researches on model-based control of particulate processes has focused on processes described by population balance models, there are many processes that involve coupling of a continuous phase and a particulate phase which are Cited by: Since the book was published, another more useful model was published which relates the crystallization results to control parameters like reactant addition rate, temperature and solubility of the crystals without arbitrary adjustable parameters.

Considering the caveats, I recommend the book Cited by: Christofides, () demonstrated one of the earliest applications of model-based control on a spray pyrolysis process using a population balance model of the droplets as the model.

The final. Buy Model-Based Control of Particulate Processes (Particle Technology Series) by Panagiotis D. Christofides (ISBN: ) from Amazon's Book Store. Everyday low prices and free delivery on eligible orders. Control of particulate processes: Recent results and future challenges we present an overview of recently developed methods for model-based control of particulate processes.

We primarily. Model-Based Control of Particulate Processes. Model-Based Control of is used for the construction of finite-dimensional ODE systems that accurately reproduce the dominant dynamics of the particulate process.

These ODE systems are then used to analyze the limitations imposed by input constraints on the ability to modify the dynamics of the Author: Panagiotis D. Christofides.

In this work, we present an overview of recently developed methods for model-based control of particulate processes. We primarily discuss methods developed in the context of our previous research work and use examples of crystallization, aerosol and thermal spray processes to motivate the development of these methods and illustrate their by: One common Model-Based Control of Particulate Processes book to all model-based control design approaches of particulate processes reviewed above is that they start by reducing the order of the PB model before designing the controller.

Otherwise, the controller design and implementation would become infeasible (such as in output feedback linearization involving Lie algebra) or the resulting controller would be limited by Cited by:   Buy Model-Based Control of Particulate Processes by Panagiotis D.

Christofides from Waterstones today. Click and Collect from your local Waterstones Book Edition: Softcover Reprint of The Original 1st Ed. of particulate processes, up to about 10 years ago, research on model-based control of particulate processes had been very limited.

Specifically, early research efforts had mainly focused on the understanding of fundamental control-theoretic prop-erties (controllability and observability) of.

Nonlinear Model Reduction and Control of Particulate Processes Nonlinear Control of Crystallization Robust Control of Particulate Processes Contrained Control of Particulate Processes Nonlinear Control of Spatially-Distributed Aerosol Processes Control of a Titania Aerosol Reactor Control of an HVOF Thermal Spray Process.

Model-Based Control of Particulate Processes. [Panagiotis D Christofides] -- This book - the first of its kind - presents general methods for the synthesis of nonlinear, robust and constrained feedback controllers for broad classes of particulate process models and.

Theory of Particulate Processes: Analysis and Techniques of Continuous Crystallization, Second Edition covers the numerous population balance-based particulate studies.

This edition emerged from the notes for an industrial short course on Edition: 2. [13] A. Bück & S. Palis & E. Tsotsas, Model-based control of particle properties in fluidised bed spray granulation, Powder Technology,pp. – [14] S. Palis & A. Kienle, Discrepancy based control of particulate processes, Journal of Process Contpp.

This paper addresses the problem of subspace-based model identification and predictive control of particulate process subject to uncertainty and time-varying parameters. To this end, subspace identification techniques are first adapted to handle the batch nature of the data.

A linear model predictive controller (MPC) is next formulated to enable achieving a particle size distribution with Cited by: book by Randolph and Larson for results and refer.

ences. The highly nonlinear and oscillatory behavior of manyx particulate processes implies the need to implement nonlin-ear model-based feedback controllers in order to ensure a stable and efficient operation.

In spite of. Robust Control of Particulate Processes Using Uncertain Population Balances Timothy Y. Chiu and Panagiotis D. Christofides Dept. of Chemical Engineering, University of California, Los Angeles, CA A general method is proposed for the synthesis of robust, nonlinear controllers for spatially homogeneous particulate processes described by.

The objective of this work is to present a review of computational tools and models for pharmaceutical processes, specifically those for the continuous manufacture of solid dosage forms.

Relevant mathematical methods and simulation techniques are discussed, as is the development of process models for solids-handling unit operations. Continuous processing is of particular interest in the Cited by:   Theory of Particulate Processes: Analysis and Techniques of Continuous Crystallization describes the complexity of crystal size distribution (CSD), secondary nucleation, and growth mechanisms.

This book is divided into 10 chapters that present a generalization from CSD studies as a unified predictive theory of particulate Edition: 1. At publication, The Control Handbook immediately became the definitive resource that engineers working with modern control systems its many accolades, that first edition was cited by the AAP as the Best Engineering Handbook of Now, 15 years later, William Levine has once again compiled the most comprehensive and authoritative resource on control by: 7.

controllers. This limitation had been the bottleneck for model-based synthesis and real-time implementation of nonlinear feedback controllers on particulate processes. Recent developments Control theory for particulate processes Motivated by the lack of population balance-based control methods for particulate processes and the need to.

model, model-based control, particulate processes. INTRODUCTION Valuable products from the agricultural, chemical, food, mineral, and pharmaceutical industries are derived from particulate processes whose qualities are determined by the characteristics of the particle size distribution.

Fault-tolerant control of particulate processes is an. Particulate control technologies rely on a range of physical phenomena, such as gravity, centrifugal, electrostatic and impaction forces, to capture and remove particulates from a flow stream.

The chapter includes numerous worked examples related to control of particulates. Wisdom is the principal thing; therefore get wisdom; and with all thy getting, get understanding.

Proverbs In the early chapters of the book of Proverbs there is a strong emphasis on three words: knowledge, understanding, and wisdom. Perhaps we can apply these words to our philosophy behind the technology of Predictive Process Control.

Diesel particulate filter is one of the most effective after-treatment techniques to reduce Particulate Matters (PM) emissions from a diesel engine, but the blocking Diesel Particulate Filter (DPF) will seriously affect the engine performance, so it is necessary to study the fault diagnosis of blocking DPF.

In this paper, a simulation model of an RDOHC diesel engine with wall-flow ceramic Cited by: 1. Author: Bück, A. et al.; Genre: Conference Paper; Published in Print: ; Title: Model-based measurement and control of particulate processes: an application to Author: A.

Bück, M. Peglow, E. Tsotsas, M. Mangold, A. Kienle, A. Kienle. Predictive Process Control of Crowded Particulate Suspensions | Wisdom is the principal thing; therefore get wisdom; and with all thy getting, get understanding. Proverbs In the early chapters of the book of Proverbs there is a strong emphasis on three words: knowledge, understanding, and wisdom.

Book Description. The state-of-the-art publication in model-based process control—by leading experts in the field. In Techniques of Model-Based Control, two leading experts bring together powerful advances in model-based control for chemical-process n Brosilow and Babu Joseph focus on practical approaches designed to solve real-world problems, and they offer extensive.

There's no description for this book yet. Can you add one?. First Sentence. Predictive Process Control (PPC) is a method for predicting the performance of a crowded particulate suspension by separate measurements of selected fundamental properties of each raw material ingredient before their assembly into a by: Nonlinear control of particulate processes Nonlinear control of particulate processes Chiu, Timothy; Christofides, Panagiotis D.

A general methodology is proposed for the synthesis of practically-implementable nonlinear output feedback controllers for spatially-homogeneous particulate processes modeled by population balance equations. Panagiotis Christofides. DISTINGUISHED PROFESSOR “Control of Particulate Processes,” Special Issue of Particle & Particle Systems Characterization, 25(4), pages, Christofides, P.

D., “Model-Based Control of Particulate Processes,” pages, Kluwer Academic Publishers, The Netherlands, Occupation: DISTINGUISHED PROFESSOR.

PDA Europe. Am Borsigturm 60 - Berlin, Germany Tel: +49 30 55 or Fax: +49 30 55 In this work on particulate processes three main topics are addressed: the numerical solution of a one dimensional PBE, time optimal control of a particulate system in a semi-batch reactor, and the solution of inverse problems to extract the kernels of the PBE from available data.

Robust control of particulate processes using uncertain population balances Robust control of particulate processes using uncertain population balances Chiu, Timothy Y.; Christofides, Panagiotis D.

Dept. of Chemical Engineering, University of California, Los Angeles, CA A general method is proposed for the synthesis of robust, nonlinear controllers for spatially. In the exhaust after treatment system considered in this paper, a diesel oxidation catalyst (DOC) is installed upstream of the DPF to facilitate the regeneration process.

In order to combust the captured particulate in the DPF, a small amount of fuel can be injected into the exhaust, upstream of the DOC, when by: 1. Characterization of process nonlinearity for control-relevant design Large scale applications of MPC including plant-wide control and cross direction control of sheet/film processes Experimental studies of nonlinear model-based control of particle size distribution in a semi-batch emulsion polymerization reactor.The design of wet scrubbers or any air pollution control device depends on the industrial process conditions and the nature of the air pollutants involved.

Inlet gas characteristics and dust properties (if particles are present) are of primary importance. Scrubbers can be designed to collect particulate matter and/or gaseous pollutants.matter from PCC plant. Subsequently, this has led to the installation of particulate control.

Electrostatic precipitators (ESP) dominate the market for particulate control in a variety of combustion and industrial processes, including PCC plant, incineration plant, cement kilns, steel manufacture, oil refineries and paper industries.