排序方式: 共有3条查询结果,搜索用时 15 毫秒
1
1.
Taous-Meriem Laleg-Kirati Emmanuelle Crépeau Michel Sorine 《Mathematics of Control, Signals, and Systems (MCSS)》2013,25(1):37-61
This study introduces a new signal analysis method, based on a semi-classical approach. The main idea in this method is to interpret a pulse-shaped signal as a potential of a Schrödinger operator and then to use the discrete spectrum of this operator for the analysis of the signal. We present some numerical examples and the first results obtained with this method on the analysis of arterial blood pressure waveforms. 相似文献
2.
S. Khelouat T. M. Laleg-Kirati A. Benalia D. Boukhetala M. Djemai 《International journal of systems science》2019,50(5):1069-1088
In this paper, the problem of fault detection and isolation in a three-cell converter is investigated using a nonlinear geometric approach. This powerful method based on the unobservability distribution is used to detect and isolate the faulty cell in the three-cell converter. First, a model describing the faults in the cells is presented. The geometric approach is then applied on this faulty model to generate residual signals based on a sliding-mode observer that allows the detection of faults in the three-cell converter. Numerical results show the effectiveness of the proposed sliding-mode residual generators for fault detection and isolation in the three-cell converter. 相似文献
3.
Robust Fractional-Order Proportional-Integral Observer for Synchronization of Chaotic Fractional-Order Systems 下载免费PDF全文
Ibrahima N Doye Khaled Nabil Salama Taous-Meriem Laleg-Kirati 《IEEE/CAA Journal of Automatica Sinica》2019,6(1):268-277
In this paper, we propose a robust fractional-order proportional-integral (FOPI) observer for the synchronization of nonlinear fractional-order chaotic systems. The convergence of the observer is proved, and sufficient conditions are derived in terms of linear matrix inequalities (LMIs) approach by using an indirect Lyapunov method. The proposed FOPI observer is robust against Lipschitz additive nonlinear uncertainty. It is also compared to the fractional-order proportional (FOP) observer and its performance is illustrated through simulations done on the fractional-order chaotic Lorenz system. 相似文献
1