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Optimal control: linear quadratic methods
This augmented edition of a respected text teaches the reader how to use linear quadratic Gaussian methods effectively for the design of control systems. It explores linear optimal control theory
Linear Optimal Control
Optimal Filtering
TLDR
This book helps to fill the void in the market and does that in a superb manner by covering the standard topics such as Kalman filtering, innovations processes, smoothing, and adaptive and nonlinear estimation.
Rigidity, computation, and randomization in network localization
We provide a theoretical foundation for the problem of network localization in which some nodes know their locations and other nodes determine their locations by measuring the distances to their
A Theory of Network Localization
TLDR
This paper constructs grounded graphs to model network localization and applies graph rigidity theory to test the conditions for unique localizability and to construct uniquely localizable networks, and further study the computational complexity of network localization.
Controller Reduction: Concepts and Approaches
  • B. Anderson, Yi Liu
  • Mathematics, Computer Science
    American Control Conference
  • 10 June 1987
This paper considers the problem of passing from a linear time-invariant high order controller designed for a linear time-invariant plant (of presumably high order) to a low order approximation of
Localization in sparse networks using sweeps
TLDR
A class of algorithms for fine-grained localization called Sweeps, which correctly finitely localizes all nodes in bilateration networks and handles angle measurements and noisy measurements.
Network Analysis and Synthesis: A Modern Systems Theory Approach
TLDR
Wheeler and Ganji introduce many topics that engineers need to master in order to plan, design and document a successful experiment or measurement system, including modern computerized data acquisition systems, electrical output measuring devices, and in-depth coverage of experimental uncertainty analysis.
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