High Performance Control
by T.T. Tay, I.M.Y. Mareels, J.B. Moore
Publisher: Birkhauser 1997
Number of pages: 362
Using the tools of optimal control, robust control and adaptive control, the authors develop the theory and practice of high performance control in a real world environment. Topics include performance enhancement, stabilizing controllers, offline controller design, and dynamical systems.
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by Tao Zheng - InTech
Model Predictive Control refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request to complicated process plants, MPC has been accepted in many practical fields.
by Derek Atherton - BookBoon
The book covers the basic aspects of linear single loop feedback control theory. Explanations of the mathematical concepts used in classical control such as root loci, frequency response and stability methods are explained by making use of MATLAB.
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The book provides a self-contained treatment on practical aspects of stochastic modeling and calculus including applications in engineering, statistics and computer science. Readers should be familiar with probability theory and stochastic calculus.
by M.R. James - Australian National University
These notes are an overview of some aspects of optimal and robust control theory considered relevant to quantum control. The notes cover classical deterministic optimal control, classical stochastic and robust control, and quantum feedback control.