The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this Letter, we discuss delayed Hopfield neural networks of variable coefficients and distribution, based on globally Lipchitz continuous activation functions, the equilibrium point and the Lyapunov functional method. Sufficient conditions ensuring Globally Asymptotical Stability of neural networks are given.
In order to improve tracking accuracy of the servo system, an adaptive inverse controller with PID feedforward is designed. It is based on the time-delay characteristic of the adaptive inverse control when training. The controller can realize accurately tracking of the servo, so as to meet the working need of the system. Finally, the tracking simulation is carried out on the digital servo experimental...
An approach based on chaos theory and fuzzy neural network (FNN) is proposed for chaotic time series prediction. Firstly, C-C algorithm is applied to estimate the delay time of chaotic signal. Grassberger-Procaccia (G-P) algorithm and least squares regression are employed to calculate the correlation dimension of chaotic signal simultaneously. Considering the difficulty in determining the number of...
In this paper, the sliding-mode lag synchronization control scheme is proposed based on the neural network to synchronize two different delayed chaotic systems. An integral delayed sliding surface is presented to design the sliding mode control. The lag synchronization controller is achieved by combining the RBF (radial basis function) neural network with sliding-mode control. Numerical simulations...
This paper is concerned with the state feed-back guaranteed cost fault tolerant control of networked control systems with both network-induces delay and data dropout. Using LMI approach, The sufficient condition for the existence of the networked guaranteed quadratic cost controller is obtained in terms of matrix inequalities, and the controller design method is deduced in terms of linear matrix inequalities...
In this paper we consider the approximate controllability for a class of semilinear delayed control systems described by a semigroup formulation with boundary control and nonlinear perturbations appearing in boundary conditions. Sufficient conditions for approximate controllability are established provided the approximate controllability of corresponding linear systems.
She gave the new sufficient conditions for the exponential stability of BAM neural networks with distribute delays. The analysis of the stability of the equilibrium point had focused on establishing a relationship between the networks parameters of neural networks model independent of the delay parameters.
In this paper, the global exponential stability for a class of impulsive cellular neural networks with discrete and distributed time-varying delays is considered. The results are based on the Lyapunov-Krasovskii functional stability analysis for differential equations and the linear matrix inequality (LMI) optimization approach. Some numerical examples are given to show the effectiveness of our results.
In this paper, asymptotic stability for a new type of neutral delay neural networks systems is investigated. Stability criteria are presented by using Lyapunov method and linear matrix inequalities (LMIs) which can be easily solved by LMI Toolbox in Matlab.
PID neural network controller design for Sharif University of Technology (SUT) building energy management system (BEMS) is addressed in this paper. The most important characteristics of process systems are time delay with model uncertainties. Artificial neural networks can perform adaptive controller properties through learning processes. PID neural network has the advantage of both conventional PID...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.