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Turnpike Theory for the Robinson-Solow-Srinivasan Model

-Srinivasan (RSS) model. It will be useful for researches interested in the turnpike theory, infinite horizon optimal control and their applications;

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Nonlinear Pinning Control of Complex Dynamical Networks

inverse optimal control approach is employed. For both cases, model-based is considered in Chapter 3 and Chapter 5; then, Chapter 4 and Chapter 6;

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Optimal Control And Forecasting Of Complex Dynamical Systems

This important book reviews applications of optimization and optimal control theory to modern problems in physics, nano-science and finance;

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Intelligent Algorithms for Analysis and Control of Dynamical Systems

control of dynamical systems. Both single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems are explored for analysis and;

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Continuous Time Dynamical Systems

, Continuous Time Dynamical Systems: State Estimation and Optimal Control with Orthogonal Functions, considers different classes of systems with;

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Optimal Design of Control Systems: Stochastic and Deterministic Problems (Pure and Applied Mathematics

"Covers design methods for optimal (or quasioptimal) control algorithms in the form of synthesis for deterministic and stochastic dynamical;

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Optimal Trajectory Tracking of Nonlinear Dynamical Systems

, of interest to a broad range of scientists and engineers. While common control strategies for dynamical systems center on the system state as the;

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Optimal Reference Shaping for Dynamical Systems

feedback control alone. Focusing on feedforward control techniques, Optimal Reference Shaping for Dynamical Systems: Theory and Applications;

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Optimal Reference Shaping for Dynamical Systems

feedback control alone. Focusing on feedforward control techniques, Optimal Reference Shaping for Dynamical Systems: Theory and Applications;

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Nonlinear Dynamical Systems and Control

of feedback systems, optimal control, disturbance rejection control, and robust control for nonlinear dynamical systems is also given. This book is an;

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Dynamical Systems in Theoretical Perspective

; value distribution and growth of solutions for certain Painleve equations; optimal control of hybrid systems with sliding modes; a mathematical;

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Deterministic Learning Theory for Identification, Recognition, and Control

-based closed-loop control via the so-called internal and dynamical matching of system dynamics. This actually represents a new model;

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Deterministic Learning Theory for Identification, Recognition, and Control

dynamical pattern recognition and pattern-based control processes. The results are applicable to areas such as detection and isolation;

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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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Impulsive and Hybrid Dynamical Systems

control, and robust control for nonlinear impulsive and hybrid dynamical systems. A major contribution to mathematical system theory and control;

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Differential Equations and Control Theory

, China. It provides an overview of current developments in a range of topics including dynamical systems, optimal control theory, stochastic;

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Model-Based Control

Model-Based Control will be a collection of state-of-the-art contributions in the field of modelling, identification, robust control and;

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Nonnegative and Compartmental Dynamical Systems

systems and advance the state of the art in their analysis and active control design. Nonnegative and Compartmental Dynamical Systems presents the;

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Dynamical Model and Optimal Control

from Economics and Social Sciences. The first part develops the fundamental aspects of mathematical modeling, dealing with both continuous time;

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Optimal Auxiliary Functions Method for Nonlinear Dynamical Systems

adjust the convergence of the solutions of nonlinear dynamical systems. The optimal auxiliary functions are depending on some convergence-control;

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Optimal Control of Switched Systems Arising in Fermentation Processes

and comprehensive systematic treatment of optimal control problems arising in fermentation processes. It not only develops nonlinear dynamical;

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Modelling, Analysis, and Control of Networked Dynamical Systems

This monograph provides a comprehensive exploration of new tools for modelling, analysis, and control of networked dynamical systems;

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Model Reduction of Complex Dynamical Systems

kernel-based methods; surrogate modeling for design and optimization, with special emphasis on control and data assimilation; model reduction;

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Elements Of Control Theory

and optimal control for dynamical systems represented by ordinary differential equations in a finite dimensional Euclidean space. The problems;

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Distributed Cooperative Control and Communication for Multi agent Systems

rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The;

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Distributed Cooperative Control and Communication for Multi agent Systems

rigid body systems. The model-based and data-driven control method are employed to design the (optimal) cooperative control protocol. The;

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Interpolatory Methods for Model Reduction

Dynamical systems are a principal tool in the modeling, prediction, and control of a wide range of complex phenomena. As the need for;

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