Multivariable Computer-controlled Systems: A Transfer Function Approach (Communications and Control Engineering) - Tapa dura

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E.N. Rosenwasser holds the chair for automated ship complexes at the State University of Ocean Technology of Saint Petersburg, Russia. Prof. Rosenwasser is one of the leading Russian control scientists. His research results are published in more than 200 publications including 15 monographs.

Bernhard P. Lampe is Professor for automatic control at the Institute of Automation, Department Electrical Engineering and Computer Sciences at the University of Rostock, Germany. Prof. Lampe is initiator and leader of numerous research projects in theory and application of advanced control methods, as well as author and co-author of more than 250 publications including 5 monographs.

In cooperation both authors wrote the Communications and Control Engineering monograph Computer Controlled Systems, (1-85233-307-3, 2000).

De la contraportada

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.

Having established the ability of the parametric transfer function to solve this problem for single-input, single-output systems in previous work, the authors extend these 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.

Multivariable Computer-controlled Systems is divided into three parts:

Preliminary algebraic material describing the established fundamentals of polynomial and rational matrices necessary for the understanding of later chapters.

Control problems, important in their own right but which also have a substantial bearing on what follows (eigenvalue assignment and the use of z- and zeta-transforms in discrete systems).

Frequency methods for the investigation of MIMO sampled-data systems (parametric discrete-time models; stability; stochastic methods; H₂ optimization and L₂ design).

Appendices covering basic mathematical formulae and the description of two MATLAB^® toolboxes round out this self-contained guide to multivariable control systems.

Of special interest to researchers in automatic control and to development engineers working with advanced control technology, Multivariable Computer-controlled Systems will also interest mathematical control theorists and graduate students studying advanced methods of computer-based control.