Chen Gang, Chen Yun, Zeng Hong-Bing
School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
School of Electrical and Information Engineering, Hunan University of Technology, Zhuzhou 412007, China.
ISA Trans. 2020 Jun;101:170-176. doi: 10.1016/j.isatra.2020.02.007. Epub 2020 Feb 10.
This study verifies the H filter design for sampled-data systems with quantization and event-triggered schemes. Firstly, an event-triggered mechanism is presented to detect the release of the necessary sampled-data packet, which significantly reduces the limited network resources compared with the conventional time-triggered mechanism. Secondly, by considering the impact of quantization on the sampled-data system and using the time interval analysis approach, a new sampled-data filtering error model is presented. Then, the Lyapunov-Krasovskii functional (LKF) approach is utilized to derive the required conditions to ensure the asymptotical stability and attain the prescribed H performance for the mentioned system by solving a group of linear matrix inequality (LMIs). Consequently, the corresponding event-triggered and H parameters are co-designed. Finally, the efficiency and the advantage of the presented approach are demonstrated via a mass-spring system example.
本研究验证了具有量化和事件触发机制的采样数据系统的H滤波器设计。首先，提出了一种事件触发机制来检测必要采样数据包的释放，与传统的时间触发机制相比，这显著减少了有限的网络资源。其次，通过考虑量化对采样数据系统的影响并使用时间间隔分析方法，提出了一种新的采样数据滤波误差模型。然后，利用李雅普诺夫-克拉索夫斯基泛函（LKF）方法，通过求解一组线性矩阵不等式（LMI）来推导确保上述系统渐近稳定性并达到规定H性能所需的条件。因此，相应的事件触发参数和H参数是共同设计的。最后，通过一个质量-弹簧系统示例展示了所提方法的有效性和优势。
