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PID Passivity-Based Control of Nonlinear Systems with Applications

field In PID Passivity-Based Control of Nonlinear Systems with Applications, expert researchers and authors Drs. Romeo Ortega, Jose;

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PID Control System Design and Automatic Tuning using MATLAB/Simulink

analysis, PID control design, implementation with constraints, disturbance observer-based PID control, gain scheduled PID control systems, cascade;

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Control of Nonlinear Systems via PI, PD and PID

The purpose of this book is to give an exposition of recently adaptive PI/PDPID control design for nonlinear systems. Since PI/PDPID;

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Nonlinear Industrial Control Systems

Nonlinear Industrial Control Systems presents a range of mostly optimisation-based methods for severely nonlinear systems; it discusses;

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Robust Adaptive Control for Fractional-Order Systems with Disturbance and Saturation

A treatise on investigating tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties;

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Control Systems

analyzed with applications such as auto-landing aircraft, industrial process control, active suspension system, fuzzy gain scheduling, PID control;

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PID Control in the Third Millennium

to PID including fractional-order, event-based, nonlinear, data-driven and predictive control; the nearly twenty chapters provide a state;

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PID Control in the Third Millennium

to PID including fractional-order, event-based, nonlinear, data-driven and predictive control; the nearly twenty chapters provide a state;

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Operator-Based Nonlinear Control Systems Design And Applicat

* Operator-based nonlinear control systems with smart actuators * Nonlinear feedback control for large-scale systems using a distributed control;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

of Discrete-Time Nonlinear Systems The book presents two approaches for controller synthesis: the first based on passivity theory and the second on;

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Discrete-Time Inverse Optimal Control for Nonlinear Systems

of Discrete-Time Nonlinear Systems The book presents two approaches for controller synthesis: the first based on passivity theory and the second on;

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Passivity-Based Control and Estimation in Networked Robotics

. The text begins with an introduction to passivity and passivity-based control together with the other foundations needed in this book. The;

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Nonlinear Control Systems

This book presents an overview on the various aspects of Nonlinear Control Systems. A trend of examining Nonlinear Control Systems has been;

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Linear Multivariable Control Systems

generalization of Thevenin's Theorem, a new single-input single-output approach to multivariable control, and analytical design of PID controllers;

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Lyapunov-Based Control of Robotic Systems

Lyapunov-Based Control of Robotic Systems describes nonlinear control design solutions for problems that arise from robots required to;

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Lyapunov-Based Control of Robotic Systems

Lyapunov-Based Control of Robotic Systems describes nonlinear control design solutions for problems that arise from robots required to;

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Image-Based and Fractional-Order Control for Mechatronic Systems

first discusses practical issues with the implementation of fractional-order control, comparing them with more traditional integer-order PID;

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Introduction to Fuzzy Systems

fuzzy control theory, based mainly on the well-known classical Proportional-Integral-Derivative (PID) controllers theory and design methods;

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Modeling and Control of Uncertain Nonlinear Systems with Fuzzy Equations and Z-Number

Systems with Fuzzy Equations and Z-Number presents a structured approach to the control and modeling of uncertain nonlinear systems in industry;

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Nonlinear Control Systems using MATLAB (R)

and appropriate controller (P-PI-PID) for feedback linearization control strategy. A Symbolic MATLAB Based function for;

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Nonlinear Control Systems using MATLAB (R)

appropriate controller (P-PI-PID) for feedback linearization control strategy. A Symbolic MATLAB Based function for finding the feedback;

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Network Optimization Methods in Passivity-Based Cooperative Control

data-based, model-free approach for the synthesis of network controllers for multi-agent systems with passivity-short agents. Further, the;

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Explicit Nonlinear Model Predictive Control

black-box models; - Nonlinear systems with continuous control inputs and nonlinear systems with quantized control inputs; - Nonlinear;

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Control of Large Wind Energy Systems

. Examples and a case study are included to illustrate the parametrization of models, the control systems design with problems and possible solutions;

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Advances in Systems, Control and Automation

nonlinear systems, intelligent systems, stochastic control, knowledge-based systems applications, fault diagnosis and tolerant control, real-time;

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Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

architecture of control science and engineering. Introduces nonlinear systems' basic knowledge, analysis and control methods, along with;

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Neural Networks Modeling and Control

control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order;

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