Multivariable Matlab

The transfer function approach is widely used in classical control theory for its easy handling and physical meaning. Although the use of transfer functions is well-established for linear time-invariant systems, it is not suitable for non-stationary systems among which are sampled-data systems and processes with periodically varying coefficients. Computer-controlled continuous-time processes are a very important subset of periodic sampled-data systems which are not treatable using ordinary transfer functions.

Das Buch richtet sich an in der Industrie tätige Ingenieure, die MPC-Regelungen planen, entwickeln und betreiben, aber auch an Studierende technischer Fachdisziplinen, die in das Arbeitsgebiet MPC einsteigen wollen. Das vorliegende Buch gibt eine Übersicht über die Grundideen und Anwendungsvorteile des MPC-Konzepts. Es zeigt, wie mit Hilfe der Toolbox MPC-Regelungen entworfen, eingestellt und simuliert werden können.
The book is aimed at engineers in industry interested in the development and application of MPC systems, as well as students of different technical disciplines seeking an introduction into this field. This book gives an overview of the basic ideas and advantages of the MPC concept. It shows how MPC systems can be designed, tuned, and simulated using the MPC Toolbox.

In this book, the authors extend the parametric transfer function methods, which incorporate time-dependence, to the idea of the parametric transfer matrix in a complete exposition of analysis and design methods for multiple-input, multiple-output (MIMO) sampled-data systems. Appendices covering basic mathematical formulae, two MATLAB® toolboxes round out this self-contained guide to multivariable control systems. The book will interest researchers in automatic control and to development engineers working with advanced control technology.

Variational Regularization of 3D Data provides an introduction to variational methods for data modelling and its application in computer vision. In this book, the authors identify interpolation as an inverse problem that can be solved by Tikhonov regularization.

Robust Modal Control covers most classical multivariable modal control design techniques that were shown to be effective in practice, and in addition proposes several new tools. The proposed new tools include: minimum energy eigenvector selection, low order observer-based control design, conversion to observer-based controllers, a new multimodel design technique, and modal analysis. The text is accompanied by a CD-ROM containing MATLAB® software for the implementation of the proposed techniques. The software is in use in aeronautical industry and has proven to be effective and functional.