An identification method of time-varying delay based on genetic algorithm

Author(s):  
Feng Pan ◽  
Ru-Cheng Han ◽  
Dong-Mei Feng
2012 ◽  
Vol 629 ◽  
pp. 853-858
Author(s):  
Jiu Ying Deng ◽  
Qin Ruo Wang ◽  
Wei Jen Lee ◽  
Jian Bin Xiong

This paper explores the robust stability and H∞ control performance index of uncertain system with time-varying delay. The output feedback H∞ controller is constituted at the finite uncertain limit. The condition of delay-independence for the system with asymptotic stable and perturbation sustaining is derived as LMI formulation. The optimum control problem of uncertain time-delay system with H-infinite output feedback is presented. The stability and exogenous disturbance constraint synthesis is performed by chaos and genetic algorithm. The genetic algorithm based optimization approach is developed for extracting the upper bound of the performance index. Experiment results suggest that the H∞ output feedback control law is less conservative and possesses much high stabilization and optimization performance.


Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 661
Author(s):  
Huansen Fu ◽  
Baotong Cui ◽  
Bo Zhuang ◽  
Jianzhong Zhang

This work proposes a state estimation strategy over mobile sensor–actuator networks with missing measurements for a class of distributed parameter systems (DPSs) with time-varying delay. Initially, taking advantage of the abstract development equation theory and operator semigroup method, this kind of delayed DPSs described by partial differential equations (PDEs) is derived for evolution equations. Subsequently, the distributed state estimators including consistency component and gain component are designed; the purpose is to estimate the original state distribution of the delayed DPSs with missing measurements. Then, a delay-dependent guidance approach is presented in the form of mobile control forces by constructing an appropriate Lyapunov function candidate. Furthermore, by applying Lyapunov stability theorem, operator semigroup theory, and a stochastic analysis approach, the estimation error systems have been proved asymptotically stable in the mean square sense, which indicates the estimators can approximate the original system states effectively when this kind of DPS has time-delay and the mobile sensors occur missing measurements. Finally, the correctness of control strategy is illustrated by numerical simulation results.


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