A modeling and control approach for an advanced configured large civil aircraft with aeroservoelasticity via the LQG method and control allocation is presented.Mathematical models and implementation issues for the multi-input/multi-output(MIMO) aeroservoelastic system simulation developed for a flexible wing with multi control surfaces are described.A fuzzy logic based optimization approach is employed to solve the constrained control allocation problem via intelligently adjusting the components of output vector and find a proper vector in the attainable moment set(AMS) autonomously.The basic idea is to minimize the L2 norm of error between the desired moment and achievable moment using the designing freedom provided by redundantly allocated actuators and control surfaces.Considering the constraints of control surfaces,in order to obtain acceptable performance of aircraft such as stability and maneuverability,the fuzzy weights are updated by the learning algorithm,which makes the closed-loop system self-adaptation.Finally,an application example of flight control designing for the advanced civil aircraft is discussed as a demonstration.The studies we have performed showed that the advanced configured large civil aircraft has good performance with the proper designed control law designed via the proposed approach.The gust alleviation and flutter suppression are applied with the synergetic effects of elevator,ailerons,equivalent rudders and flaps.The results show good closed loop performance and meet the requirement of constraint of control surfaces. A modeling and control approach for an advanced configured large civil aircraft with aeroservoelasticity via the LQG method and control allocation is presented. Mathematical models and implementation issues for the multi-input / multi-output (MIMO) aeroservoelastic system simulation developed for a flexible wing with A control strategy is to solve the constrained control allocation problem via intelligently adjusting the components of output vector and find a proper vector in the attainable moment set (AMS) autonomously. The basic idea is to minimize the L2 norm of error between the desired moment and achievable moment using the programmed freedom provided by redundantly allocated actuators and control surfaces. Considring the constraint of control surfaces, in order to obtain acceptable performance of aircraft such as stability and maneuverability, the fuzzy weights are updated by the learning algorithm, which makes the close d-loop system self-adaptation. Finaally, an application example of flight control designing for the advanced civil aircraft is discussed as a demonstration. the studies we have performed showed that the advanced configured large civil aircraft has good performance with the proper designed control law designed via the proposed approach. The gust alleviation and flutter suppression are applied with the synergetic effects of elevator, ailerons, equivalent rudders and flaps. The results show good closed loop performance and meet the requirement of constraint of control surfaces.