Bayesian Computation with R

by Jim Albert, K. Glover

This monograph concerns the design of feedback controllers for multivariable linear dynamic systems. The particular approach is to consider a coprime factor description of the plant's transfer function and to represent a family of systems by perturbing the numerator and denominator. The design of controllers to robustly stabilize such a family is posed as an H? optimization problem and some explicit solutions are obtained. Similarly, procedures for reduced order modelling and controller design are derived. Finally, the results are exploited to give a systematic loop shaping control system design procedure that is assessed on several aerospace examples. The book will be appropriate for advanced undergraduate or graduate classes requiring only a first course in state-space methods. It also gives a good introduction to multivariable control and the use of H? methods.

280 pages, Paperback

First published January 1, 1990

About the author

Jim Albert is a Distinguished University Professor of Statistics at Bowling Green State University. His research interests include Bayesian modeling and applications of statistical thinking in sports. He has authored or coauthored several books including Ordinal Data Modeling, Bayesian Computation with R, and Workshop Statistics: Discovery with Data, A Bayesian Approach.