This paper researches the strict dissipative control problem for uncertain fuzzy neutral Markov jump systems by Takagi-Sugeno fuzzy rules. The asynchronous phenomenon is considered between the uncertain fuzzy neutral Markov jump systems modes and asynchronous fuzzy P-D feedback controller modes, which is described by a hidden Markov model. Via using linear matrix inequalities, the desired asynchronous fuzzy P-D feedback controller is obtained, which can ensure that the closed-loop uncertain fuzzy neutral Markov jump systems satisfies robustly exponential mean square stabilization with strict dissipativity. A numerical example and a single-link robot arm are utilized to demonstrate the effectiveness of the method.
针对自适应局部迭代滤波(Adaptive Local Iterative Filtering,ALIF)方法的模态混叠问题,提出了基于伪极值点的自适应局部迭代滤波(Pseudo-extrema-based Adaptive Local Iterative Filtering,PEALIF)方法.此方法采用增加伪极值点的方式使得信号极值点的分布更均匀,有效地抑制模态混叠问题的同时,亦保证了算法分解的顺序性.详细介绍了EPALIF方法的原理,同时构建仿真信号,将此方法与EMD、EEMD、CEEMD和ALIF方法进行分析和对比.结果表明PEALIF在分解能力、抑制模态混叠和抗噪声干扰等方面都具有一定的优越性.最后,将此方法应用在双半内圈轴承故障诊断中,实验结果表明PEALIF方法能获取更突出且易于辨识的故障特征信息,证实了该方法应用在轴承故障诊断分析上的实用性. 相似文献