Springer Nonlinear Control of Fixed-Wing UAVs with Time-Varying and Unstructured Uncertainties: 1 (Springer Tracts in Autonomous Systems, 1)

Product Description 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. From the Back Cover 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.