Robust Autonomous Guidance von Alberto Isidori | An Internal Model Approach | ISBN 9781447100119

Robust Autonomous Guidance

An Internal Model Approach

von Alberto Isidori, Lorenzo Marconi und Andrea Serrani
Mitwirkende
Autor / AutorinAlberto Isidori
Autor / AutorinLorenzo Marconi
Autor / AutorinAndrea Serrani
Buchcover Robust Autonomous Guidance | Alberto Isidori | EAN 9781447100119 | ISBN 1-4471-0011-5 | ISBN 978-1-4471-0011-9

The book is well organized and well written. Each chapter starts with an introductory section and each case study concludes with simulation results. The book is an excellent combination of theory and real-world applications. Each application not only demonstrates the power of the theoretical results but also is important on its own behalf.

This book is a valuable addition to references for academic researchers and industrial engineers working in the field of nonlinear control systems design, in particular, for aerospace guidance systems. The book can also serve as a useful reference for graduate courses in nonlinear control systems.

 

IEEE Control Systems Magazine (October 2004) (Reviewer: Qian Wang)

Robust Autonomous Guidance

An Internal Model Approach

von Alberto Isidori, Lorenzo Marconi und Andrea Serrani
Mitwirkende
Autor / AutorinAlberto Isidori
Autor / AutorinLorenzo Marconi
Autor / AutorinAndrea Serrani

Plant control systems are subject to the undesirable influence of exogenous commands and disturbances. To track and reject these the authors have designed a feedback control system based on embedding a model of them within the controller itself - the „internal model“.

From a review of the principles of internal-model-based feedback control design, this book moves on to expound recent enhancements to such designs and then to their implementation in systems operating under conditions of great uncertainty.

The case studies presented involve control systems coping with a high degree of nonlinear behaviour. The key issues addressed in each are the design of an adaptive internal model for the specific tracking task and of stabilizing control capable of steering the tracking error to zero while keeping all internal states bounded for any arbitrarily large but bounded envelope of initial data and uncertain parameters. Nested saturated controls form the basis of novel tools for asymptotic analysis and design.