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LFT Modeling and Robust Stability Analysis of Missiles with Uncertain Parameters
HOU Zhen-qian,LIANG Xiao-geng,WANG Wen-zheng,LI Rui 한국항공우주학회 2014 International Journal of Aeronautical and Space Sc Vol.15 No.2
The structured singular value (μ) analysis based method has many advantages for the robust stability analysis of missiles with uncertain parameters. Nevertheless, the present linear fractional transformation (LFT) modeling process, which is the basis of μ analysis, is complex, and not suitable for automatic implementation; on the other hand, μ analysis requires a large amount of computation, which is a burden for large-scale application. A constructive procedure, which is computationally more efficient, and which may lead to a lower order realization than existing algorithms, is proposed for LFT modeling. To reduce the calculation burden, an analysis method is developed, based on skew μ. On this basis, calculation of the supremum of μ over a fixed frequency range converts into a single skew μ value calculation. Two algorithms are given, to calculate the upper and lower bounds of skew μ, respectively. The validity of the proposed method is verified through robust stability analysis of a missile with real uncertain parameters.
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Optimal Controller for Near-Space Interceptor with Actuator Saturation
FAN Guo-long,LIANG Xiao-geng,HOU Zhen-qian,YANG Jun 한국항공우주학회 2013 International Journal of Aeronautical and Space Sc Vol.14 No.3
The saturation of the actuator impairs the response performance of the near space interceptor control system. A control system based on the properties of linear tracking system is designed for this problem. The properties are that the maximum value of the pseudo-Lyapunov function of the linear tracking control system do not present at the initial state but at the steady state, based on which the bounded stability problem is converted into linear tracking problem. The pseudo-Lyapunov function of the linear tracking system contain the input variables; the amplitude and frequency of the input variables affect the stability of the nonlinear control system. Designate expected closed-loop poles area for different input commands and obtain a controller which is function of input variables. The coupling between variables and linear matrices make the control system design problem non-convex. The non-convex problem is converted into a convex LMI according to the Shur complement lemma and iterative algorithm. Finally the simulation shows that the designed optimal control system is quick and accurate; the rationality of the presented design techniques is validated.
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