Constrained Optimal Control of Linear and Hybrid Systems

Many practical control problems are dominated by characteristics such as state, input and operational constraints, alternations between different operating regimes, and the interaction of continuous-time and discrete event systems. At present no methodology is available to design controllers in a systematic manner for such systems. This book introduces a new design theory for controllers for such constrained and switching dynamical systems and leads to algorithms that systematically solve control synthesis problems. The first part is a self-contained introduction to multiparametric programming, which is the main technique used to study and compute state feedback optimal control laws. The book's main objective is to derive properties of the state feedback solution, as well as to obtain algorithms to compute it efficiently. The focus is on constrained linear systems and constrained linear hybrid systems. The applicability of the theory is demonstrated through two experimental case studies: a mechanical laboratory process and a traction control system developed jointly with the Ford Motor Company in Michigan.

Introduces a new design theory for controllers for constrained and switching dynamical systems Includes a self-contained introduction to multiparametric programming Demonstration of applications through case studies developed jointly with Ford Motor Company Michigan Includes supplementary material: sn.pub/extras

Klappentext

Many practical control problems are dominated by characteristics such as state, input and operational constraints, alternations between different operating regimes, and the interaction of continuous-time and discrete event systems. At present no methodology is available to design controllers in a systematic manner for such systems. This book introduces a new design theory for controllers for such constrained and switching dynamical systems and leads to algorithms that systematically solve control synthesis problems. The first part is a self-contained introduction to multiparametric programming, which is the main technique used to study and compute state feedback optimal control laws. The book's main objective is to derive properties of the state feedback solution, as well as to obtain algorithms to compute it efficiently. The focus is on constrained linear systems and constrained linear hybrid systems. The applicability of the theory is demonstrated through two experimental case studies: a mechanical laboratory process and a traction control system developed jointly with the Ford Motor Company in Michigan.

Inhalt
Multiparametric Programming.- Multiparametric Programming: a Geometric Approach.- Optimal Control of Linear Systems.- Constrained Finite Time Optimal Control.- Constrained Infinite Time Optimal Control.- Receding Horizon Control.- Constrained Robust Optimal Control.- Reducing On-line Complexity.- Optimal Control of Hybrid Systems.- Hybrid Systems.- Constrained Optimal Control for Hybrid Systems.- Applications.- Ball and Plate.- Traction Control.