Model-Based Control of Particulate Processes

1. Front Matter

   Pages i-xx

   PDF

2. Introduction

   • Panagiotis D. Christofides

   Pages 1-7

3. Nonlinear Model Reduction and Control of Particulate Processes

   • Panagiotis D. Christofides

   Pages 9-33

4. Nonlinear Control of Crystallization

   • Panagiotis D. Christofides

   Pages 35-57

5. Robust Control of Particulate Processes

   • Panagiotis D. Christofides

   Pages 59-86

6. Constrained Control of Particulate Processes

   • Panagiotis D. Christofides

   Pages 87-120

7. Nonlinear Control of Spatially-Distributed Aerosol Processes

   • Panagiotis D. Christofides

   Pages 121-139

8. Control of a Titania Aerosol Reactor

   • Panagiotis D. Christofides

   Pages 141-162

9. Control of an HVOF Thermal Spray Process

   • Panagiotis D. Christofides

   Pages 163-189

10. Back Matter

    Pages 191-211

    PDF

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 of nanostructured coatings. It is now well understood that the physico-chemical and mechanical properties of materials made with particulates depend heavily on the characteristics of the corresponding particle size distribution. This fact, together with recent advances in dynamics of infinite-dimensional sys­ tems and nonlinear control theory, has motivated extensive research on model-based control of particulate processes using population balances to achieve tight control of particle size distributions. 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 to industrially-important crystallization, aerosol and thermal spray processes. The controllers use a finite number of measurement sensors and control actuators to achieve stabilization of the closed-loop system, output tracking, attenuation of the effect of model uncertainty and han­ dling of actuator saturation.

• actuator
• computer
• computer simulation
• control
• crystal
• development
• dynamics
• process control
• research
• sensor
• sensors
• simulation
• stabilization
• systems theory
• thermal spray

• Department of Chemical Engineering, University of California, Los Angeles, USA

  Panagiotis D. Christofides

Policies and ethics