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.
The problem of guaranteeing rotor speed and flux modulus tracking on the basis of rotor speed and stator currents measurements is addressed and solved for induction motors with uncertain constant load torque and stator and rotor resistances. A new nonlinear adaptive control algorithm is designed, which relies on a closed loop adaptive observer providing estimates for the unmeasured state variables...
We address the state feedback position tracking control problem for uncertain current-fed permanent magnet step motors with non-sinusoidal flux distribution. Under the assumption that the reference profile for the rotor angle is periodic with known period, a robust adaptive learning control algorithm is designed, which "learns" the non-structured unknown periodic disturbance signal due to...
We propose a novel nonlinear dynamic tracking control algorithm for induction motors with uncertain load torque in which only stator currents are used for feedback: under suitable assumptions, closed loop boundedness and local exponential rotor speed and flux modulus tracking are guaranteed
The problem of designing a global output feedback tracking control for current-fed induction motor servo drives with mechanical uncertainties is addressed. Under the assumption that the reference profile for the rotor angle is periodic with known period, an adaptive learning control is designed which "learns" the non-structured unknown periodic disturbance signal due to mechanical uncertainties,...
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.