Unmanned systems are one of the fastest-growing and widely developing technologies in the world, offering many possibilities for a variety of research fields. This book comprises the proceedings of the 2022 International Symposium on Unmanned Systems and the Defense Industry (ISUDEF), a multi-disciplinary conference on a broad range of current research and issues in areas such as autonomous technology, unmanned aircraft technologies, avionics, radar systems, air defense, aerospace robotics and mechatronics, and aircraft technology design. ISUDEF allows researchers, scientists, engineers, practitioners, policymakers, and students to exchange information, present new technologies and developments, and discuss future direction, strategies, and priorities in the field of autonomous vehicles and unmanned aircraft technologies.

Higher Order Dynamic Mode Decomposition and Its Applications provides detailed background theory, as well as several fully explained applications from a range of industrial contexts to help readers understand and use this innovative algorithm. Data-driven modelling of complex systems is a rapidly evolving field, which has applications in domains including engineering, medical, biological, and physical sciences, where it is providing ground-breaking insights into complex systems that exhibit rich multi-scale phenomena in both time and space. Starting with an introductory summary of established order reduction techniques like POD, DEIM, Koopman, and DMD, this book proceeds to provide a detailed explanation of higher order DMD, and to explain its advantages over other methods. Technical details of how the HODMD can be applied to a range of industrial problems will help the reader decide how to use the method in the most appropriate way, along with example MATLAB codes and advice on how to analyse and present results.