Title Details

Led by a well-known expert in the field, this self-contained book features comprehensive coverage of multi-parametric optimization and control.  The authors provide state-of-the-art coverage of the most recent methodological developments for optimal model-based control via parametric optimization.  Each chapter consists of a theoretical treatment of the topic along with a relevant case study, allowing for the topical complexity to gradually increase throughout.  Each case study describes the needed methods and illustrates real-world applications, aiding readers in gaining a better understanding of the presented material.  Part I presents an overview of the state-of-the-art multi-parametric optimization theory and algorithms in multi-parametric programming.  Introducing the ‘San Francisco to Topeka’ transportation problem case study, this section highlights a conceptual approach and covers the main algorithms.  Part II focuses on multi-parametric model predictive control and emphasizes the connection between multi-parametric programming and model-predictive control, starting from the linear quadratic regulator over hybrid systems to periodic systems and robust control.  Illustrating the natural combination between multi-parametric programming and model predictive control, this part introduces and works through a case study on the continuously stirred tank reactor.  Part III features multi-parametric optimization in process systems engineering.  This section introduces the step-by-step procedure of embedding multi-parametric programming within process system engineering.  This naturally leads to the PAROC framework and software platform, which is an integrated framework and software platform for the optimization and advanced model-based control of process systems.  This section’s case study features a combined heat and power system.  Finally, the book ends with an appendix that includes the history of multi-parametric optimization algorithms as well as the use of the parametric optimization toolbox (POP), which is a comprehensive software tool capable of efficiently solving multi-parametric programming problems, while being easily embedded into other software architectures such as the ones used in the PAROC platform.