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Titlebook: Optimization Based Clearance of Flight Control Laws; A Civil Aircraft App Andreas Varga,Anders Hansson,Guilhem Puyou Book 2012 Springer Ber

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Book 2012ation.. This project successfully contributed to the achievement of a top-level objective to meet society’s needs for a more efficient, safer and environmentally friendly air transport by providing new techniques and tools for the clearance of flight control laws. This is an important part of the ce
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Worst-Case Parameter Search Based Clearance Using Parallel Nonlinear Programming Methodsation methods in conjunction with established simulation and analysis tools; and (2) increasing the efficiency of clearance by applying parallel computation techniques. These enhancements are illustrated in Chapter 13 by the application of the selected optimization methods and parallelization techniques to several challenging clearance criteria.
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Generation of LFRs for a Flexible Aircraft Modelze and satisfactorily approximates the aircraft behaviour, by providing almost exact match of the system eigenvalues and frequency responses. This model serves as basis of the clearance techniques relying on .-analysis, Lyapunov-based analysis and IQC-based analysis.
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Generation of LFRs for a Nonlinear Controller and Closed-Loop Aircraft Models controller LFR is interconnected with the LFRs of the actuators, sensors and of the nonlinear rigid aircraft or linear flexible aircraft generated in Chapters 3 or 4 to obtain the LFRs of the corresponding closed-loop systems. These closed-loop LFRs are used for stability and performance analysis in Chapters 12-16.
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Identification of LPV State-Space Models Using ,-Minimisationtimisation-based generation method to convert these linear models into an LPV-model, by minimising a suitable . error norm. Although computationally more demanding than the alternative element-wise approximation approach, the new method often produces LPV-models with lower complexity.
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