Abstract
A fuzzy logic based optimization approach is employed to solve the constrained control allocation problem via intelligent 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 L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> 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 close-loop system self-adaptation. With above approach, additional closed-loop specifications such as decoupling of different modes and reconfigurable control can also be achieved. Finally, an application example of flight control designing for an advanced fighter is discussed as a demonstration.
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