a new chapter on economic NMPC relaxing the assumption that the running cost penalizes the distance to a pre-defined equilibrium.The second edition has been substantially rewritten, edited and updated to reflect the significant advances that have been made since the publication of its predecessor, including:
.jpg "melanie van overloop")
#MELANIE VAN OVERLOOP SOFTWARE#
Accompanying software in MATLAB® and C++ (downloadable from /), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine-the core of any nonlinear model predictive controller-works. These results are complemented by discussions of feasibility and robustness. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants.
This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems.
0 kommentar(er)
