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.
This article presents a Lyapunov function based neural network tracking (LNT) strategy for single-input, single-output (SISO) discrete-time nonlinear dynamic systems. The proposed LNT architecture is composed of two feedforward neural networks operating as controller and estimator. A Lyapunov function based back propagation learning algorithm is used for online adjustment of the controller and estimator...
Dynamic variations in real power directly affects the system frequency. Consequently, large frequency deviations in interconnected systems might cause costly power outages. In order to maintain continuous and stable power production, the load frequency control (LFC) becomes utmost important. This paper presents a neuro-adaptive controller that minimizes the effects of load variations on system frequency...
This paper presents a Lyapunov function based neural network tracking control strategy for single-input-single-output nonlinear dynamic systems. The proposed architecture is composed of two feed-forward neural networks operating as controller and estimator in a unified framework. The network parameters are tuned online with a Lyapunov function based backpropagation learning algorithm. The closed-loop...
Temperature is an important control variable in industrial processes. In this paper, an adaptive PID control algorithm has been discussed to track the process temperature. The presented control algorithm employs Lyapunov function based artificial neural networks for online tuning of proportional, integral and derivative actions. This algorithm has been successfully tested on the laboratory temperature...
This paper presents the design of fuzzy logic controllers (FLC) for a highly nonlinear dynamic system of Surge Tank. The controllers are designed from two approaches: model free (Mamdani) and model based (Takagi-Sugeno). For model free approach, Mamdani inference engine is formed from the expert knowledge of the system using which a fuzzy PD controller is synthesized. For model based approach, first...
This paper presents Takagi-Sugeno (TS) fuzzy modeling of a dynamic system. TS fuzzy model of a highly nonlinear system of Surge Tank has been proposed which has fixed structure that is linear in parameters. The rule base for the fuzzy model is obtained from the input-output data set, extracted from the measurements performed on the actual system. Number of rules has been determined utilizing the fuzzy...
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.