Moving on from earlier stochastic and robust control paradigms,
this book introduces the fundamentals of probabilistic methods in
the analysis and design of uncertain systems. The use of randomized
algorithms, guarantees a reduction in the computational complexity
of classical robust control algorithms and in the conservativeness
of methods like H-infinity control.
Features:
self-contained treatment explaining randomized algorithms from
their genesis in the principles of probability theory to their use
for robust analysis and controller synthesis;
comprehensive treatment of sample generation, including
consideration of the difficulties involved in obtaining independent
and identically distributed samples;
applications in congestion control of high-speed communications
networks and the stability of quantized sampled-data systems.
This monograph will be of interest to theorists concerned with
robust and optimal control techniques and to all control engineers
dealing with system uncertainties."
General
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