Model-Based Control will be a collection of state-of-the-art contributions in the field of modelling, identification, robust control and optimization of dynamical systems, with particular attention to the application domains of motion control systems (high-accuracy positioning systems) and large scale industrial process control systems.The book will be directed to academic and industrial people involved in research in systems and control, industrial process control and mechatronics.

Provides extensive coverage of both theory and practice ranging from behavioral to conservation laws and to industrial process control

Fundamentals.- Linear Systems in Discrete Time.- Robust Controller Synthesis is Convex for Systems without Control Channel Uncertainties.- Conservation Laws and Lumped System Dynamics.- Polynomial Optimization Problems are Eigenvalue Problems.- Bridging Theory and Applied Technology.- Designing Instrumentation for Control.- Uncertain Model Set Calculation from Frequency Domain Data.- Robust Estimation for Automatic Controller Tuning with Application to Active Noise Control.- Identification of Parameters in Large Scale Physical Model Structures, for the Purpose of Model-Based Operations.- Applications in Motion Control Systems and Industrial Process Control.- Recovering Data from Cracked Optical Discs using Hankel Iterative Learning Control.- Advances in Data-driven Optimization of Parametric and Non-parametric Feedforward Control Designs with Industrial Applications.- Incremental Identification of Hybrid Models of Dynamic Process Systems.- Front Controllability in Two-Phase Porous Media Flow.- PhD Supervision by Okko H. Bosgra.- Okko H. Bosgra, Bibliographic Record.