Feedback control systems.
Overview
| Works: | 72 works in 32 publications in 32 languages | |
|---|---|---|
Titles
Schaum's outline of theory and problems of feedback and control systems
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Advances in Control, Communication Networks, and Transportation Systems = In Honor of Pravin Varaiya /
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Autonomous underwater vehicles = modeling, control design, and simulation /
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(Electronic resources)
Two-degree-of-freedom control systems = the Youla Parameterization approach /
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Feedback stabilization of controlled dynamical systems = in honor of Laurent Praly /
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Reinforcement learning for optimal feedback control = a Lyapunov-based approach /
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Modern control systems analysis and design using MATLAB and SIMULINK /
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Feedback control problems : = using MATLAB and the control system toolbox /
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Feedback systems : = an introduction for scientists and engineers /
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Elementary feedback stabilization of the linear reaction-convection-diffusion equation and the wave equation
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Control of indefinite nonlinear dynamic systems = induced internal feedback /
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Non-linear feedback neural networks = VLSI implementations and applications /
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Robust output feedback H-infinity control and filtering for uncertain linear systems
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Feedback control = linear, nonlinear and robust techniques and design with industrial applications /
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Block backstepping design of nonlinear state feedback control law for underactuated mechanical systems
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Towards integrating control and information theories = from information-theoretic measures to control performance limitations /
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Multi-stage and multi-time scale feedback control of linear systems with applications to fuel cells
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Robust control of DC-DC converters : = the Kharitonov's theorem approach with MATLAB codes /
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Reinforcement learning aided performance optimization of feedback control systems
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Adaptive backstepping control of uncertain systems with actuator failures, subsystem interactions, and nonsmooth nonlinearities
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Feedback control systems analysis and design = practice problems, methods, and solutions /
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Adaptive approximation based control : = unifying neural, fuzzy and traditional adaptive approximation approaches /
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Reinforcement learning = optimal feedback control with industrial applications /
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Advances in nonlinear observer design for state and parameter estimation in energy systems
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