共查询到4条相似文献，搜索用时 140 毫秒
1.
Yanyi Cao Yuting Cao Shiping Wen Tingwen Huang Zhigang Zeng 《Journal of The Franklin Institute》2018,355(17):8915-8933
In this paper, we intend to discuss the passivity of coupled neural networks (NNs) with reaction–diffusion terms and mixed delays. By constructing appropriate Lyapunov functional, and with the help of liner matrix inequalities, some inequality techniques, several sufficient conditions are derived to guarantee the output strictly passive, input strictly passive, passive of the proposed neural network model. Then, a stability criterion is presented according to the obtained passivity results. Moreover, the proposed neural network model herein is more general than some recent studies, which can improve and enrich the previous research results. Finally, a numerical example is presented to show the effectiveness of the theoretical criteria. 相似文献
2.
This paper analyzes synchronization in finite time for two types of coupled delayed Cohen–Grossberg neural networks (CDCGNNs). In the first type, linearly coupled Cohen–Grossberg neural networks with and without coupling delays are considered, respectively. In the second type, nonlinearly coupled Cohen–Grossberg neural networks both with and without coupling delays are discussed. By designing suitable controllers and using some inequality techniques, several criteria ensuring finite-time synchronization of the CDCGNNs with linear coupling and nonlinear coupling are derived, respectively. Moreover, the settling times of synchronization in finite time for the considered networks are also predicted. In the end, the availability for the acquired finite-time synchronization conditions is confirmed by two selected numerical examples. 相似文献
3.
To perform repetitive tasks, this paper proposes an adaptive boundary iterative learning control (ILC) scheme for a two-link rigid–flexible manipulator with parametric uncertainties. Using Hamilton?s principle, the coupled ordinary differential equation and partial differential equation (ODE–PDE) dynamic model of the system is established. In order to drive the joints to follow desired trajectory and eliminate deformation of flexible beam simultaneously, boundary control strategy is added based on the conventional joints torque control. The adaptive iterative learning algorithm for boundary control scheme includes a proportional-derivative (PD) feedback structure and an iterative term. This novel controller is designed to deal with the unmodeled dynamics and other unknown external disturbances. Numerical simulations are provided to verify the performance of proposed controller in MATLAB. 相似文献