Results 101 to 110 of about 1,825 (125)
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Input-to-state stability (ISS) analysis for dynamic neural networks

IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 1999
Summary: A novel approach to assess the stability of dynamic neural networks is presented. Using a Lyapunov function, we determine conditions to guarantee input-to-state stability which also ensures global asymptotic stability. The applicability of these conditions is illustrated by two examples.
Edgar N. Sánchez, José P. Pérez
openaire   +4 more sources

The Input-to-State Stable (ISS) Approach for Stabilizing Haptic Interaction With Virtual Environments

IEEE Transactions on Robotics, 2017
Passivity has been a major criterion for designing a stable haptic interface due to its numerous advantages. However, passivity-based controllers have suffered from the design conservatism of the passivity criterion, particularly when users want to increase the maximum apparent impedance.
Aghil Jafari   +2 more
openaire   +3 more sources

On the input-to-state stability (ISS) of a double integrator with saturated linear control laws

Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 2003
We show that the closed loop system consisting of a double integrator with any stabilizing saturated linear control law is not input-to-state stable (ISS) even for external disturbances with arbitrarily small magnitude.
Guoyong Shi, Ali Saberi
openaire   +1 more source

Robust global stabilization with ignored input dynamics: an input-to-state stability (ISS) small-gain approach

IEEE Transactions on Automatic Control, 2001
The authors consider the system \[ \dot x= f(x)+ g(x)v,\quad\dot\xi= A(\xi)+ bu,\quad v= c(\xi)+ du \] for which it is known that \(\dot x= f(x)+ g(x)\alpha(x)\) has the equilibrium at \(\{0\}\) globally asymptotically stable. Redesign of the control, i.e.
Zhong-Ping Jiang, Murat Arcak
openaire   +2 more sources

Exponential Input-to-State Stability (e-ISS) Analysis of Delayed Impulsive Stochastic Reaction-Diffusion Cohen-Grossberg Neural Networks (RDCGNNS) with Varying Coefficients

2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), 2018
In this article, the e-ISS of delayed impulsive stochastic RDCGNNs with varying coefficients has been studied. In light of Halanay inequalities and using Razumikhin technique, we obtain some new sufficient criteria judging e-ISS of the derived RDCGNNs. A numerical simulation is also discussed to check the efficiency of our mian results.
Weisong Zhou, Zhichun Yang
openaire   +1 more source

Interval exponential input-to-state stability for switching impulsive systems and hybrid control to ISS for micro-grids

2016
MSC 2015 includes two international conferences sponsored and promoted by the IEEE Control Systems Society: The IEEE Conference on Control Applications (CCA) and The IEEE International Symposium on Intelligent Control (ISIC)
Liu, B, Hill, DJ
openaire   +1 more source

Input-to-State Stability of Impulsive Delay Systems With Multiple Impulses

IEEE Transactions on Automatic Control, 2021
Xiaodi Li, Jianquan Lu, Peng Li
exaly  

Input‐to‐state exponents and related ISS for delayed discrete‐time systems with application to impulsive effects

International Journal of Robust and Nonlinear Control, 2018
Bin Liu, Zhijie Sun, David Hill
exaly  

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