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Robust Control Design: An Optimal Control Approach

Comprehensive and accessible guide to the three main approaches to robust control design and its applications Optimal control is a;

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Linear Systems

Balancing rigorous theory with practical applications, Linear Systems: Optimal and Robust Control explains the concepts behind linear;

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Robust Industrial Control Systems

of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for;

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Robust Control Systems with Genetic Algorithms

developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure;

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Robust Control Systems with Genetic Algorithms

developing optimal robust controllers for linear control systems, optimal disturbance rejection controllers, and predictive and variable structure;

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Robust Output LQ Optimal Control via Integral Sliding Modes

useful and practical optimal control with very few impractical assumptions. The results presented allow optimal control theory to grow in its;

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Linear Control Theory

areas of control engineering (PID control, robust control, and optimal control). It provides balanced coverage of elegant mathematical theory;

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Modern Control Engineering

recent methods in system identification and optimal, digital, adaptive, robust, and fuzzy control, as well as stability, controllability;

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Robust Systems Theory and Applications

used in linear robust control analysis/synthesis and in robust (control-oriented) identification. The main analysis and design methods are;

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Linear Robust Control

for students and control engineers, the authors examine all of these advances, providing an in-depth examination of modern optimal and robust;

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Optimal Reference Shaping for Dynamical Systems

limited time-optimal control. The author explains how the minimax optimization problem can help in the design of robust time-delay filters and;

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Optimal Reference Shaping for Dynamical Systems

limited time-optimal control. The author explains how the minimax optimization problem can help in the design of robust time-delay filters and;

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Positive 1d and 2D Systems

theorists concerned with robust and optimal control techniques and to all control engineers dealing with system uncertainties.;

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Modern Trends in Controlled Stochastic Processes:

, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems;

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Cooperative Control of Multi-Agent Systems

Cooperative Control of Multi-Agent Systems: An Optimal and Robust Perspective reports and encourages technology transfer in the field;

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Optimal and Robust Scheduling for Networked Control Systems

Optimal and Robust Scheduling for Networked Control Systems tackles the problem of integrating system components-controllers, sensors, and;

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Optimal and Robust Scheduling for Networked Control Systems

Optimal and Robust Scheduling for Networked Control Systems tackles the problem of integrating system components-controllers, sensors, and;

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Optimal Adaptive Control and Differential Games by Reinforcement Learning Principles

is connected from a theoretical point of view with both adaptive control and optimal control methods. The book shows how ADP can be used to design a;

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Cooperative Optimal Control of Hybrid Energy Systems

consists of the hierarchical optimal control strategy for the security issue, multi-objective optimization for both economic and emission issue;

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Cooperative Optimal Control of Hybrid Energy Systems

consists of the hierarchical optimal control strategy for the security issue, multi-objective optimization for both economic and emission issue;

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Optimal and Robust Estimation

today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second;

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Nonlinear Control Systems

like Feedback Linearization, Lyapunov Based Control, Adaptive Control, Optimal Control and Robust Control and discusses various applications;

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Optimal and Robust Control

knowledge of automatic control and signals and systems, this second edition of Optimal and Robust Control offers a straightforward, self-contained;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

. The discrete-time optimal and robust control techniques proposed can be used in a range of industrial applications, from aerospace and energy;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

. The discrete-time optimal and robust control techniques proposed can be used in a range of industrial applications, from aerospace and energy;

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Periodic Systems

optimal and robust control. The text focuses on discrete-time signals and systems; however, an overview of the entire field, including the;

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Uncertain Models and Robust Control

Uncertain Models and Robust Control .;

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