Explicit Nonlinear Model Predictive Control

Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an expli

Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorith

Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehic

The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful

Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB® and Simulink®. This reference is one of the most detaile

Networked and Distributed Predictive Control presents rigorous, yet practical, methods for the design of networked and distributed predictive control systems – the first book to do so. The design of m

For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques.Predictive Control describes the development of tractable

A comprehensive development of interpolating control, this monograph demonstrates the reduced computational complexity of a ground-breaking technique compared with the established model predictive con

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive

The description for this book, Stability in Nonlinear Control Systems, will be forthcoming.

Constructive Nonlinear Control presents a broad repertoire of constructive nonlinear designs not available in other works by widening the class of systems and design tools. Several streams of nonlinea

Spacecraft Dynamics and Control: The Embedded Model Control Approach provides a uniform way of approaching space engineering control problems from the standpoint of model-based control, using state eq

This brief provides an overview on the most relevant nonlinear phenomena in internal combustion engines with a particular emphasis on the use of nonlinear circuits in their modelling and control. The

This treatment of modern topics related to mathematical systems theory forms the proceedings of a workshop, Mathematical Systems Theory: From Behaviors to Nonlinear Control, held at the University of

In this work we derive asymptotically stabilizing control laws for electrical power systems using two nonlinear control synthesis techniques. For this transient stabilization problem the actuator cons

The work in this book entails the development of non-linear model-based multivariable control algorithms and strategies and their use in an integrated approach to control strategy, which incorporates

This monograph provides insight and fundamental understanding into the feedback control of nonlinear and hybrid process systems. It presents state-of-the-art methods for the synthesis of nonlinear fee

Nonlinear transport phenomena are an increasingly important aspect of modern semiconductor research. Nonlinear Spatio-Temporal Dynamics and Chaos in Semiconductors deals with complex nonlinear dynamics, pattern formation, and chaotic behaviour in such systems. In doing so it bridges the gap between two well-established fields: the theory of dynamic systems, and nonlinear charge transport in semiconductors. This unified approach is used to consider important electronic transport instabilities. The initial chapters lay a general framework for the theoretical description of nonlinear self-organized spatio-temporal patterns, like current filaments, field domains, fronts, and analysis of their stability. Later chapters consider important model systems in detail: impact ionization induced impurity breakdown, Hall instabilities, superlattices, and low-dimensional structures. State-of-the-art results include chaos control, spatio-temporal chaos, multistability, pattern selection, activator-inh

Memristive Nonlinear Electronic Circuits deals with nonlinear systems in the design and implementation of circuits for generating complex dynamics. The brief proposes a new memristor model using an in

This treatment of modern topics relatedto the control of nonlinear systems is a collection of contributionscelebrating the work of Professor Henk Nijmeijer and honoring his 60thbirthday. It addresses

Explicit Learning in the L2 Classroom offers a unique five-prong (theoretical, empirical, methodological, pedagogical, and model building) approach to the issue of explicit learning in the L2 classroo

?In order to precisely model real-life systems or man-made devices, both nonlinear and dynamic properties need to be taken into account. The generic, black-box model based on Volterra and Wiener serie

Analysis and Synthesis of Networked Control Systems focuses on essential aspects of this field, including quantization over networks, data fusion over networks, predictive control over networks and fa

This research monograph summarizes solutions to reconfigurable fault-tolerant control problems for nonlinear dynamical systems that are based on the fault-hiding principle. It emphasizes but is not li

The authors present a study of the H-infinity control problem and related topics for descriptor systems, described by a set of nonlinear differential-algebraic equations. They derive necessary and suf

Dynamics and Optimal Control of Road Vehicles uniquely offers a unified treatment of tyre, car and motorcycle dynamics, and the application of nonlinear optimal control to vehicle-related problems wit

In the traditional curriculum, students rarely study nonlinear differential equations and nonlinear systems due to the difficulty or impossibility of computing explicit solutions manually. Although th

This treatment of modern topics related to mathematical systems theory forms the proceedings of a workshop, Mathematical Systems Theory: From Behaviors to Nonlinear Control, held at the University of

This brief presents a description of a new modelling framework for nonlinear/geometric control theory. The framework is intended to be—and shown to be—feedback-invariant. As such, Tautological Control

This up-to-date book details the basic concepts of many recent developments of nonlinear identification and nonlinear control, and their application to hydraulic servo-systems. It is very application-

This book is on existence and necessary conditions, such as Potryagin's maximum principle, for optimal control problems described by ordinary and partial differential equations. These necessary conditions are obtained from Kuhn–Tucker theorems for nonlinear programming problems in infinite dimensional spaces. The optimal control problems include control constraints, state constraints and target conditions. Evolution partial differential equations are studied using semigroup theory, abstract differential equations in linear spaces, integral equations and interpolation theory. Existence of optimal controls is established for arbitrary control sets by means of a general theory of relaxed controls. Applications include nonlinear systems described by partial differential equations of hyperbolic and parabolic type and results on convergence of suboptimal controls.

Chaos control refers to purposefully manipulating chaotic dynamical behaviors of some complex nonlinear systems. There exists no similar control theory-oriented book available in the market that is de

The chapters of this book have been presented at the 1st Workshop of the Nonlinear Control Network*, which was held in Ghent, March 15,16, 1999. These contributions give an overview of some of the cur

Model-Based Control of a Robot Manipulator presents the first integrated treatment of many of the most important recent developments in using detailed dynamic models of robots to improve their control

Predictive Sentencing addresses the role of risk assessment in contemporary sentencing practices. Predictive sentencing has become so deeply ingrained in Western criminal justice decision-making that

Partial least squares is a new approach in structural equation modeling that can pay dividends when theory is scarce, correct model specifications are uncertain, and predictive accuracy is paramount.

This book examines the role of model validation of power system planning and operation to optimize its performance in terms of frequency control. It presents the detailed model validation for the Iran

Fault Diagnosis and Sustainable Control of Wind Turbines: Robust Data-Driven and Model-Based Strategies discusses the development of reliable and robust fault diagnosis and fault-tolerant (‘sustainabl

Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from si

Excel predictive analytics for serious data crunchers! The movie Moneyball made predictive analytics famous: Now you can apply the same techniques to help your business win. You don’t need multimi