Multi-parametric Optimization and Control

Recent developments in Multi-Parametric Optimization and Control Multi-Parametric Optimization and Control provides comprehensive coverage of recent theoretical, algorithmic and computational developments in multi-parametric optimization and control for different types of optimization problems, and their application to different classes of optimal model-based control problems. This book presents an overview of the state-of-the-art multi-parametric optimization theory and algorithms in multi-parametric programming and it examines the connection between multi-parametric programming and model-predictive control. Ideal for academics, researchers, and control and optimization practitioners, this excellent resource: Uses case studies to illustrate real-world applications for a better understanding of the concepts presented Covers the fundamentals of optimization and model predictive control by multi-parametric programming Provides information on key topics, such as the basic sensitivity theorem, linear programming, quadratic programming, mixed-integer linear programming, optimal control of continuous systems, and multi-parametric optimal control An appendix summarizes the history of multi-parametric optimization algorithms. It also covers the use of the parametric optimization toolbox (POP), which is comprehensive state-of-the-art software for efficiently solving multi-parametric programming problems.