Model-Based Control of Particulate Processes

The interest in control of particulate processes has been triggered by the need to achieve tight distributed control of size distributions that greatly influence particulate product properties and quality. Drawing from recent advances in dynamics of infinite-dimensional systems and nonlinear control theory, control of particulate processes using population balances has evolved into a very active research area within the field of process control. 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 applications 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 handling of actuator saturation. Beginning with an introduction to control of particulate processes, the book discusses nonlinear order reduction and nonlinear, robust and constrained control of particulate spatially-homogeneous processes, and nonlinear control of spatially-homogeneous particulate processes. The synthesis of the controllers is performed by using geometric and Lyapunov-based control techniques. The book includes comparisons of the methods followed for controller synthesis with other approaches and discussions of practical implementation issues that can help researchers and engineers understand the development and application of the methods in greater depth. The methods are applied to continuous and batch crystallization processes, a titania aerosol reactor and a thermal spray process to regulate product size distribution. The resulting benefits in closed-loop performance, robustness and actuator saturation handling compared to other techniques for control of particulate processes are demonstrated through computer simulations. The book assumes a basic knowledge about population balances and nonlinear control. Researchers and graduate students in process control, particle technology and control systems theory, applied mathematicians and process control engineers will find this book a useful resource.