Helps readers learn state-of-the-art applications of control theory with numerous step-by-step tutorials

Provides a comprehensive survey of contemporary model-predictive control theory and methods

Illustrates solutions for a variety of optimization problems in computationally intensive control

Theory.- The Essentials of Model Predictive Control (MPC).- Dynamic Programming and MPC.- Set-valued and Lyapunov Methods for MPC.- Stochastic Model Predictive Control.- Moving Horizon Estimation.- Probing and Duality in Stochastic Model Predictive Control.- Economic Model Predictive Control: Some Design Tools and Analysis Techniques.- Nonlinear Predictive Control for Trajectory Tracking and Path Following: An Introduction and Perspective.- Hybrid Model Predictive Control.- Model Predictive Control of Polynomial Systems.- Distributed MPC for Large-Scale Systems.- Scalable MPC Design.- Computations.- Efficient Convex Optimization for Linear MPC.- Implicit Non-Convex Model Predictive Control.- Convexification and Real-Time Optimization for MPC with Aerospace Applications.- Explicit (Offline) Optimization for MPC.- Real-Time Implementation of Explicit Model Predictive Control.- Robust Optimization for MPC.- Scenario Optimization for MPC.- Nonlinear Programming Formulations for Nonlinear and Economic Model Predictive Control.- Applications.- Automotive Applications of Model Predictive Control.- Applications of MPC in the Area of Health Care.- Model Predictive Control for Power Electronics Applications.- Learning-based Fast Nonlinear Model Predictive Control for Custom-made 3D Printed Ground and Aerial Robots.- Applications of MPC to Building HVAC Systems.- Toward Multi-Layered MPC for Complex Electric Energy Systems.- Applications of MPC to Finance.