Mutual Impact of Computing Power and Control Theory

1. Front Matter

   Pages i-xi

   PDF

2. Upcoming Numerical Linear Algebra Issues in Systems and Control Theory

   • Paul Van Dooren

   Pages 1-11

3. On Design of Approximate Finite-Dimensional Estimators: The Bayesian View

   • Rudolf Kulhavý

   Pages 13-39

4. Sidestepping the Certainty Equivalence in 2-DOF Adaptive Control Via Multiple Implicit Identifiers

   • E. Mosca, L. Chisci, L. Giarré

   Pages 41-64

5. Simulation and Control of Gas Transport and Distribution by Large-Scale Pipeline Networks

   • Zdenĕk Vostrý, Jiří Záworka

   Pages 65-75

6. Complexity of Dynamic Models for Intelligent Control

   • K. M. Hangos

   Pages 77-95

7. The Most Simple Systolic Architectures for Parallel Probabilistic Searching Algorithms

   • Ivan Kramosil

   Pages 97-109

8. On the Riemannian Interpretation of the Gauss-Newton Algorithm

   • Bernard Hanzon, Ralf L. M. Peeters

   Pages 111-121

9. Recursive Least Squares Approximation of Bayesian Non-Gaussian/Non-Linear Estimation

   • Miroslav Kárný, Ivan Nagy

   Pages 123-134

10. Fundamental Properties of Real Computers

    • Jan Šindelář

    Pages 135-150

11. A Numerical Method for Computing the Approximate Solution of the Infinite-Dimensional Discrete-Time Optimal Linear Filtering Problem

    • L. Jetto

    Pages 151-158

12. Smart Matrices

    • Pavel Kovanic

    Pages 159-167

13. Branch and Bound Algorithm for Global Optimization in Control Theory

    • S. Balemi, V. Balakrishnan

    Pages 169-179

14. Mapping LQ Control Design on Fixed-Size Array Processors

    • L. Chisci, G. Zappa

    Pages 181-193

15. Identification of Data-Compatible Models for Control Applications

    • R. P. Guidorzi, A. Stoian

    Pages 195-211

16. MIMO — A Set of SISO ?

    • Miroslav Kárný, Alena Halousková, Josef Böhm

    Pages 213-224

17. Extensions of Standard CADCS Environment for Parallel Computation and Real Time Control

    • Petr Nedoma

    Pages 225-232

18. On the Ordering of Characteristic Input-Output Modes in MIMO Discrete-Time Systems

    • V. P. Deskov, G. M. Dimirovski, N. E. Gough

    Pages 233-243

19. Regularised Lattice-Ladder Adaptive Filter

    • J. Kadlec, F. M. F. Gaston, G. W. Irwin

    Pages 245-257

20. Neural Network Applications — Case Studies

    • Kevin Warwick

    Pages 259-271

Recent rapid developments in computing power, such as parallel processing and neural networks, have stimulated new trends in control. However a discrepancy exists between available computing power and exploitable algorithms obtained classically from control theory. The aim of this book is to address the discrepancy from both the com­ putational power and control theory viewpoints. Areas such as identification, adaptive control, signal processing and neural networks therefore hold a prominent position in the text presented. The form of the book is such that it should be useful for readers at various levels, particularly those at the research and/or application stage. The book has resulted from the IFAC Workshop on the Mutual Impact of Computing Power and Control Theory, which was held at the Institute of Information Theory and Automation (UTIA), Prague, in September 1992. Organisation of the event was provided jointly by the Department of Adaptive Systems, UTIA, Prague and the School of Engineering and Information Sciences, University of Reading, UK. Selected papers from the Workshop have been chosen to give a good balance across the field, whilst at the same time highlighting important areas for future research. In this way the book represents edited Proceedings from the Workshop. One point, quickly apparent, is the international nature of the presentations themselves, which provide not only a technical appraisal of the field but also inject cultural aspects which are vitally important on the path ahead.

• Algebra
• Processing
• Signal
• algorithm
• algorithms
• automation
• complexity
• control
• information
• information theory
• linear algebra
• networks
• neural network
• optimization
• organization
• algorithmic complexity

• Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, Prague, Czech Republic

  M. Kárný

• School of Engineering and Information Sciences, University of Reading, Reading, UK

  K. Warwick

Policies and ethics