Using Harrison's model and anisotropic parabolic approximation,the band structure of In1- x- y Gay Alx As compressively strained quantum wells is calculated.To design lasers with1.55μm wavelength,it is necessary...Using Harrison's model and anisotropic parabolic approximation,the band structure of In1- x- y Gay Alx As compressively strained quantum wells is calculated.To design lasers with1.55μm wavelength,it is necessary to an- alyze the well width,differential gain,transparency carrier density and the characteristic gain for an arbitrary com- position.Some useful empirical formulas are also presented.展开更多
This article investigates gain self-scheduled H 1 robust control system design for a tailless fold- ing-wing morphing aircraft in the wing shape varying process. During the wing morphing phase, the aircraft's dynamic...This article investigates gain self-scheduled H 1 robust control system design for a tailless fold- ing-wing morphing aircraft in the wing shape varying process. During the wing morphing phase, the aircraft's dynamic response will be governed by time-varying aerodynamic forces and moments. Nonlinear dynamic equations of the morphing aircraft are linearized by using Jacobian linearization approach, and a linear parameter varying (LPV) model of the morphing aircraft in wing folding is obtained. A multi-loop controller for the morphing aircraft is formulated to guarantee stability for the wing shape transition process. The proposed controller uses a set of inner-loop gains to provide stability using classical techniques, whereas a gain self-scheduled H 1 outer-loop controller is devised to guarantee a specific level of robust stability and performance for the time-varying dynamics. The closed-loop simulations show that speed and altitude vary slightly during the whole wing folding process, and they converge rapidly after the process ends. This proves that the gain self-scheduled H 1 robust controller can guarantee a satisfactory dynamic performance for the morphing aircraft during the whole wing shape transition process. Finally, the flight control system's robustness for the wing folding process is verified according to uncertainties of the aerodynamic parameters in the nonlinear model.展开更多
文摘Using Harrison's model and anisotropic parabolic approximation,the band structure of In1- x- y Gay Alx As compressively strained quantum wells is calculated.To design lasers with1.55μm wavelength,it is necessary to an- alyze the well width,differential gain,transparency carrier density and the characteristic gain for an arbitrary com- position.Some useful empirical formulas are also presented.
基金co-supported by China Postdoctoral Science Foundation(Nos.20110490259,2012T50038)
文摘This article investigates gain self-scheduled H 1 robust control system design for a tailless fold- ing-wing morphing aircraft in the wing shape varying process. During the wing morphing phase, the aircraft's dynamic response will be governed by time-varying aerodynamic forces and moments. Nonlinear dynamic equations of the morphing aircraft are linearized by using Jacobian linearization approach, and a linear parameter varying (LPV) model of the morphing aircraft in wing folding is obtained. A multi-loop controller for the morphing aircraft is formulated to guarantee stability for the wing shape transition process. The proposed controller uses a set of inner-loop gains to provide stability using classical techniques, whereas a gain self-scheduled H 1 outer-loop controller is devised to guarantee a specific level of robust stability and performance for the time-varying dynamics. The closed-loop simulations show that speed and altitude vary slightly during the whole wing folding process, and they converge rapidly after the process ends. This proves that the gain self-scheduled H 1 robust controller can guarantee a satisfactory dynamic performance for the morphing aircraft during the whole wing shape transition process. Finally, the flight control system's robustness for the wing folding process is verified according to uncertainties of the aerodynamic parameters in the nonlinear model.