Robust Intelligent Guidance Law for Missile Interception Based on Prescribed Performance
Aiming at the missile interception problem with model uncertainty,a composite learning method combined with prescribed performance control is studied.Firstly,an integrated guidance and control model for missile interception is constructed.To ensure the constraint on the miss distance between the two sides,the prescribed performance function is utilized to guarantee the tracking performance.To improve the system accuracy against the model uncertainty,a composite learning law is constructed to estimate the unknown nonlinear functions of the system online.Finally,through Lyapunov analysis,the system stability is proved.Simulation results show that the proposed algorithm can successfully intercept the target and keep the tracking error within the specified performance curve,which demonstrates the effectiveness of the algorithm.
Prescribed performance controlComposite learningMissile interceptionIntegrated guidance and controlModel uncertainty
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