In the context of systems and control, incomplete information refers to
a dynamical system in which knowledge about the system states is limited
due to the difficulties in modelling complexity in a quantitative way.
The well-known types of incomplete information include parameter
uncertainties and norm-bounded nonlinearities. Recently, in response to
the development of network technologies, the phenomenon of randomly
occurring incomplete information has become more and more prevalent.
Filtering, Control and Fault Detection with Randomly Occurring
Incomplete Information reflects the state-of-the-art of the research
area for handling randomly occurring incomplete information from three
interrelated aspects of control, filtering and fault detection. Recent
advances in networked control systems and distributed filtering over
sensor networks are covered, and application potential in mobile
robotics is also considered. The reader will benefit from the
introduction of new concepts, new models and new methodologies with
practical significance in control engineering and signal processing.
Key Features:
- Establishes a unified framework for filtering, control and fault
detection problem for various discrete-time nonlinear stochastic
systems with randomly occurring incomplete information
- Investigates several new concepts for randomly occurring phenomena and
proposes a new system model to better describe network-induced
problems
- Demonstrates how newly developed techniques can handle emerging
mathematical and computational challenges
- Contains the latest research results
Filtering, Control and Fault Detection with Randomly Occurring
Incomplete Information provides a unified yet neat framework for
control/filtering/fault-detection with randomly occurring incomplete
information. It is a comprehensive textbook for graduate students and is
also a useful practical research reference for engineers dealing with
control, filtering and fault detection problems for networked systems.
