Liu Furong

Disturbance attenuation in test turntable dynamic unbalance of iterative learning control

The turntable exist multi-period disturbance torque be obtained by setting up the dynamic unbalance model of three-axis test turntable. The multi-period disturbance torque relate to three-axis rotate speed of test turntable. Where presents the system model with position dependent periodic disturbance with only continuous Lipschitz condition imposed, deduces the condition of position dependent multi-period disturbance translating into time dependent periodic steady-state error. A novel iterative learning control method is proposed for attenuation multi-period error of three-axis test turntable, constructed learning operator by error convergence analytic, proposes the condition of compensate multi-period steady-state error, Simulation results verify which can compensate successfully period steady-stat error caused by dynamic unbalance of test turntable system, and proves this method can improve the control precision of test turntable system.

A Novel Model of IDS Based on Fuzzy Cluster and Immune Principle

This paper presents a novel intrusion detection model based on fuzzy cluster and immune principle. The original rival penalized competitive learning (RPCL) algorithm is modified in order to address the problem of different variability of variables and correlation between variables, the sensitivity to initial number of clusters is also solved. Especially, we use the extended RPCL algorithm to determine the initial number of clusters in the fuzzy cluster algorithm. The genetic algorithm is used to optimize the radius deviation for the determination of characteristic function of abnormal subspace.