Frontiers of Model Predictive Control

Tao Zheng

• Publisher: IntechOpen
• Year: 2012
• Print ISBN: 9789535101192
• eBook ISBN: 9789535161233
• Topic: Technik & Maschinenbau
• Subtopic: Automatisierung im Maschinenbau

Model Predictive Control (MPC) usually refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance, but it is can also be seen as a term denoting a natural control strategy that matches the human thought form most closely. Half a century after its birth, it has been widely accepted in many engineering fields and has brought much benefit to us. The purpose of the book is to show the recent advancements of MPC to the readers, both in theory and in engineering. The idea was to offer guidance to researchers and engineers who are interested in the frontiers of MPC. The examples provided in the first part of this exciting collection will help you comprehend some typical boundaries in theoretical research of MPC. In the second part of the book, some excellent applications of MPC in modern engineering field are presented. With the rapid development of modeling and computational technology, we believe that MPC will remain as energetic in the future.

Table of contents

• Frontiers of Model Predictive Control
• Contents
• Preface
• Introductory Chapter - Model Predictive Control: Basic Characters
• Part 1 - New Theoretical Frontier
• 1. A Real-Time Gradient Method for Nonlinear Model Predictive Control
• 2. Feedback Linearization and LQ Based Constrained Predictive Control
• 3. Infeasibility Handling in Constrained MPC
• Part 2 - Recent Applications of MPC
• 4. Predictive Control Applied to Networked Control Systems
• 5. Predictive Control for the Grape Juice Concentration Process
• 6. Nonlinear Model Predictive Control for Induction Motor Drive
• 7. Development of Real-Time Hardware in the Loop Based MPC for Small-Scale Helicopter
• 8. Adaptable PID Versus Smith Predictive Control Applied to an Electric Water Heater System