Springer Tracts in Autonomous Systems – serie

This book introduces a comprehensive and mathematically rigorous controller design for families of nonlinear systems with time-varying parameters and unstructured uncertainties. Although the presented methodology is general, the specific family of systems considered is the latest, NextGen, unconventional fixed-wing unmanned aircraft with circulation control or morphing wings, or a combination of both.The approach considers various sources of model and parameter uncertainty, while the controller design depends not on a nominal plant model, but instead on a family of admissible plants. In contrast to existing controller designs that consider multiple models and multiple controllers, the proposed approach is based on the ‘one controller fits all models’ within the unstructured uncertainty interval.The book presents a modeling-based analysis and synthesis approach with additive uncertainty weighting functions for accurate realization of the candidate systems. This differs significantly from existing designs in that it is capable of handling time-varying characteristics.  This research monograph is suitable for scientists, engineers, researchers and graduate students with a background in control system theory who are interested in complex engineering nonlinear systems.

This book introduces a comprehensive and mathematically rigorous controller design for families of nonlinear systems with time-varying parameters and unstructured uncertainties. Although the presented methodology is general, the specific family of systems considered is the latest, NextGen, unconventional fixed-wing unmanned aircraft with circulation control or morphing wings, or a combination of both.The approach considers various sources of model and parameter uncertainty, while the controller design depends not on a nominal plant model, but instead on a family of admissible plants. In contrast to existing controller designs that consider multiple models and multiple controllers, the proposed approach is based on the ‘one controller fits all models’ within the unstructured uncertainty interval.The book presents a modeling-based analysis and synthesis approach with additive uncertainty weighting functions for accurate realization of the candidate systems. This differs significantly from existing designs in that it is capable of handling time-varying characteristics.  This research monograph is suitable for scientists, engineers, researchers and graduate students with a background in control system theory who are interested in complex engineering nonlinear systems.

This book presents the breakthrough and cutting-edge progress for collaborative perception and mapping by proposing a novel framework of multimodal perception-relative localization–collaborative mapping for collaborative robot systems. The organization of the book allows the readers to analyze, model and design collaborative perception technology for autonomous robots. It presents the basic foundation in the field of collaborative robot systems and the fundamental theory and technical guidelines for collaborative perception and mapping. The book significantly promotes the development of autonomous systems from individual intelligence to collaborative intelligence by providing extensive simulations and real experiments results in the different chapters. This book caters to engineers, graduate students and researchers in the fields of autonomous systems, robotics, computer vision and collaborative perception.