Author:
Yue Yuanda,Mi Ling,Chen Chuan,Yang Yanqing
Abstract
AbstractLyapunov equation is extensively applied in engineering areas, and zeroing neural networks (ZNN) are very effective in solving this kind of equation. In this paper, two predefined-time stability theorems are used to devise new activation functions. Then, we obtain two new ZNN models, which are applied in solving the Lyapunov equation. This type of model is called the predefined-time stability-based zeroing neural network model. Compared with the ZNN models which have existed, the proposed model retains the noise-tolerant virtue and gains a new advantage: predefined-time convergence. Lastly, we verify that the model developed in this paper is superior to the known models in solving the time-variant Lyapunov equation via numerical simulations.
Funder
the National Natural Science Foundation of China
the Shandong Province Natural Science Foundation of China
the Taishan Scholars Program
the Innovation Ability Pormotion Project for Small and Medium-sized Technology-based Enterprise of Shandong Province
the Young Innovation Team of Colleges and Universities in Shandong Province
the Pilot Project for Integrated Innovation of Science, Education and Industry of Qilu University of Technology
the Natural Science Project of Xinjiang University Scientific Research Program
Publisher
Springer Science and Business Media LLC