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Self-Learning Optimal Control of Nonlinear Systems

This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which;

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Robust Adaptive Dynamic Programming

theoretical framework for integrating techniques from adaptive dynamic programming (ADP) and modern nonlinear control to address data-driven optimal;

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Distributed Cooperative Control and Communication for Multi agent Systems

stability theory, event-triggered sampling mechanism, adaptive dynamic programming and optimal control.;

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Distributed Cooperative Control and Communication for Multi agent Systems

stability theory, event-triggered sampling mechanism, adaptive dynamic programming and optimal control.;

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Electric Power System Applications of Optimization

fundamental theories and theorems from functional optimization, optimal control, and dynamic programming to explain new Adaptive Dynamic Programming;

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Electric Power System Applications of Optimization

fundamental theories and theorems from functional optimization, optimal control, and dynamic programming to explain new Adaptive Dynamic Programming;

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Adaptive Stochastic Optimization Techniques with Applications

optimization techniques used to solve problems with adaptive, dynamic, and stochastic features. Presenting modern advances in static and dynamic;

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Optimal Control

, the fundamentals of optimal control theory. It covers the major topics involving measurement, principles of optimality, dynamic programming;

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Adaptive Dynamic Programming with Applications in Optimal Control

This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review;

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Uncertain Optimal Control

, make use of dynamic programming. The uncertain optimal control theory relates to equations of optimality, uncertain bang-bang optimal control;

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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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Optimal Control of Hybrid Vehicles

, including dynamic programming and a novel solution for state-constrained optimal control problems based on the maximum principle. Real-time;

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Controlled Markov Processes and Viscosity Solutions

This book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity;

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Optimal Networked Control Systems with MATLAB

Optimal Networked Control Systems with MATLAB (R) discusses optimal controller design in discrete time for networked control systems (NCS;

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Optimal Networked Control Systems With MATLAB

Optimal Networked Control Systems with MATLAB (R) discusses optimal controller design in discrete time for networked control systems (NCS;

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Model Free Adaptive Control

novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the;

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Model Free Adaptive Control

novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the;

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Partially Observed Markov Decision Proce

processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers in engineering;

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Applied Stochastic Control of Jump Diffusions

complete solutions. The 2nd edition adds a chapter on optimal control of stochastic partial differential equations driven by Levy processes, and a;

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Optimal Control Theory

and with certain constraints etc. It gives the necessary and sufficient condition for the (continuous-time) optimal control solution via the;

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Optimal Control Theory

and with certain constraints etc. It gives the necessary and sufficient condition for the (continuous-time) optimal control solution via the;

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Deep Reinforcement Learning with Guaranteed Performance

industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.;

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Optimal Control Theory and Static Optimization in Economics

integrated, beginning with the simple formulations and progressing to advanced topics. Optimal control theory is introduced directly, without;

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Adex Optimized Adaptive Controllers and Systems

provides practicing process control engineers with a multivariable optimal control solution which is adaptive and resistant to perturbation and the;

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Variational Calculus, Optimal Control and Applications

Variational Calculus, Optimal Control and Applications was the topic of the 12th Baltic Sea conference, traditionally an important meeting;

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Optimal Control Theory

economic processes. Geared toward upper-level undergraduates, this text introduces three aspects of optimal control theory: dynamic programming;

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Hamilton-Jacobi-Bellman Equations

Optimal feedback control arises in different areas such as aerospace engineering, chemical processing, resource economics, etc. In this;

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