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Fast Numerical Methods for Mixed-Integer Nonlinear Model-Predictive Control

Christian Kirches develops a fast numerical algorithm of wide applicability that efficiently solves mixed-integer nonlinear optimal control;

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Stabilization of Nonlinear Systems Using Receding-horizon Control Schemes

While conceptually elegant, the generic formulations of nonlinear model predictive control are not ready to use for the stabilization;

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Nonlinear and Mixed-Integer Optimization

elementary concepts of mixed-integer linear nonlinear optimization. Topics that are unique include the theory and methods for mixed-integer non;

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Economic Model Predictive Control

This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear;

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Modelling Optimization and Control of Biomedical Systems

systems Teaches the theory for multi-parametric mixed-integer programming and explicit optimal control of volatile anaesthesia Provides an;

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Process Operational Safety and Cybersecurity

: machine-learning-based modeling of nonlinear dynamical systems for model predictive control; a framework for detection and resilient control;

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Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming

integer programming models and to develop new results in the more general framework of mixed-integer nonlinear programs (MINLPs) with the goal;

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Explicit Nonlinear Model Predictive Control

Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process;

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Mixed Integer Nonlinear Programming

relationships involving the decision variables that have a pronounced effect on the set of feasible and optimal solutions. Mixed-integer nonlinear;

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Model Predictive Control

Although industrial processes are inherently nonlinear, many contributions for controller design for those plants are based on the;

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Optimal Trajectory Planning and Train Scheduling for Urban Rail Transit Systems

nonlinear model for the operation of trains and present several approaches for calculating optimal and energy-efficient trajectories within a given;

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Nonlinear Model Predictive Control

Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to;

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Predictive Filtering for Microsatellite Control System

Predictive Filtering for Microsatellite Control Systems introduces technological design, modeling, stability analysis, predictive;

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Active Disturbance Rejection Control for Nonlinear Systems

A concise, in-depth introduction to active disturbance rejection control theory for nonlinear systems, with numerical simulations and;

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Model Predictive Control

state space approaches. It systematically describes model predictive control design for chemical processes, including the basic control;

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Computer Methods for Analysis of Mixed-Mode Switching Circuits

of computer methods and numerical algorithms for analysis of mixed-mode switching circuits. Major topics include: -Computer-oriented formulation;

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Modern Predictive Control

of models for use with one- and two-step control. The author clearly explains the variations between predictive control methods-and the root;

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Modern Predictive Control

without a finite switching horizon This book gives researchers a variety of models for use with one- and two-step control. The author clearly;

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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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Nonlinear Model Predictive Control of Combustion Engines

This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines;

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Nonlinear Model Predictive Control of Combustion Engines

This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines;

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Business Optimization Using Mathematical Programming

, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed;

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Introduction To Population Pharmacokinet

for pharmacokinetic / pharmacodynamic analysis. Introduces requisite background to using Nonlinear Mixed Effects Modeling (NONMEM), covering;

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Predictive Control of Power Converters and Electrical Drives

Describes the general principles and current research into Model Predictive Control (MPC); the most up-to-date control method for power;

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Model-Based Tracking Control of Nonlinear Systems

Model-Based Control of Nonlinear Systems presents model-based control techniques for nonlinear, constrained systems. It covers constructive;

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Model-Based Tracking Control of Nonlinear Systems

Model-Based Control of Nonlinear Systems presents model-based control techniques for nonlinear, constrained systems. It covers constructive;

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Control Oriented Modelling & Identificat

to develop advanced mathematical models suitable for control system design, including: object-oriented modelling and simulation; projection;

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