Stability Analysis for Stochastic Markovian JumpReaction‐Diffusion Neural Networks with Partially Known TransitionProbabilities and Mixed Time Delays

Zhang, Weiyuan; Li, Junmin; Naizheng, Shi

doi:10.1155/2012/524187

Cited by 2 publications

(1 citation statement)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Obviously, the error dynamics in (14) is nonlinear. For the stability of nonlinear dynamical systems, various results have been derived in [21][22][23][24][25][26][27]. For convenience, the stability of (14) can be analyzed by using Lyapunov indirect method.…”

Section: Stability Of Open-loop Operationmentioning

confidence: 99%

On Stability of Open-Loop Operation without Rotor Information for Brushless DC Motors

Lyu

Shi³

et al. 2014

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Open-loop operation mode is often used to control the Brushless DC Motors (BLDCMs) without rotor position sensors when the back electromotive force (EMF) is too weak due to the very low rotor velocity. The rotor position information is not necessary in this mode and the stator windings are supplied with voltages under a certain ratio of the amplitude to the frequency. However, the rotor synchronization will be destroyed once if the commutation instant is inappropriate. In order to improve the reliability of the open-loop operation mode, a dynamic equation is established to represent the synchronization error between the rotor and the stator. Thereafter, the stability of the open-loop control mode is analyzed by using Lyapunov indirect method. Theoretical analysis indicates that the open-loop control mode is asymptotically stable only when the commutation instant of the stator current lags behind the ideal one suitably. Finally, theoretical analysis is verified through the experimental results of a certain BLDCM.

show abstract

Section: Stability Of Open-loop Operationmentioning

confidence: 99%

On Stability of Open-Loop Operation without Rotor Information for Brushless DC Motors

Lyu

Shi³

et al. 2014

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

Dynamical Behaviors of Impulsive Stochastic Reaction‐Diffusion Neural Networks with Mixed Time Delays

Zhang

Chen

2012

Abstract and Applied Analysis

View full text Add to dashboard Cite

We discuss the dynamical behaviors of impulsive stochastic reaction-diffusion neural networks (ISRDNNs) with mixed time delays. By using a well-knownL-operator differential inequality with mixed time delays and combining with the Lyapunov-Krasovkii functional approach, as well as linear matrix inequality (LMI) technique, some novel sufficient conditions are derived to ensure the existence, uniqueness, and global exponential stability of the periodic solutions for ISRDNNs with mixed time delays in the mean square sense. The obtained sufficient conditions depend on the reaction-diffusion terms. The results of this paper are new and improve some of the previously known results. The proposed model is quite general since many factors such as noise perturbations, impulsive phenomena, and mixed time delays are considered. Finally, two numerical examples are provided to verify the usefulness of the obtained results.

show abstract

Stability Analysis for Stochastic Markovian JumpReaction‐Diffusion Neural Networks with Partially Known TransitionProbabilities and Mixed Time Delays

Cited by 2 publications

References 34 publications

On Stability of Open-Loop Operation without Rotor Information for Brushless DC Motors

On Stability of Open-Loop Operation without Rotor Information for Brushless DC Motors

Dynamical Behaviors of Impulsive Stochastic Reaction‐Diffusion Neural Networks with Mixed Time Delays

Contact Info

Product

Resources

About