Intelligent Optimization Approach of Eigenstructure Assignment Based Flight Control for Advanced Fighter

Abstract

An intelligent optimization approach is proposed for eigenstructure assignment (EA) via neural network (NN) adjusting the components of output vector autonomously. The Basic idea is to minimize the L 2 norm of error between the desired vector and achievable vector using the designing freedom provided by EA technique. Besides adjusting the output vector parameters, the closed-loop eigenvalues are also optimized within desired regions on the left-half complex plane to ensure both closed-loop stability and dynamical performance. With the proposed approach, additional closed-loop specifications such as decoupling of different modes and robustness can also be easily achieved. As a demonstration, application of the proposed approach to the designing of flight control law for an advanced fighter is discussed. The results show good closed loop performance and validate the proposed intelligent optimization approach of EA technique.