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Showing 2 results for Ehyaei
Optimal Integral Sliding Mode Controller of a UAV With Considering Actuator Fault
R. Babaie, A. F. Ehyaei,
Volume 15, Issue 2 (June 2019)
Abstract
In this paper, using the State Dependent Riccati Equation (SDRE) method, we propose a Robust Optimal Integral Sliding Mode Controller (ROISMC) to guarantee an optimal control law for a quadrotor which has become increasingly important by virtue of its high degrees of manoeuvres ability in presence of unknown time-varying external disturbances and actuator fault. The robustness of the controller is ensured by an Integral Sliding Mode Controller (ISMC). Subsequently, based on Luenberger linear state estimator, the control algorithm is reformed and the actuator’s faults are detected. Moreover, design of the controller is based on Lyapunov method which can provide the stability of all system states during the tracking of the desired trajectory. The stability of suggested algorithm is verified via the execution of sudden maneuvers subjected to forcible wind disturbance and actuator faults while performing accurate attitude and position tracking by running an extensive numerical simulation. It is comprehended that the proposed optimal robust method can achieve much better tracking capability compared with conventional sliding mode controller.

Load Profile Flattening Considering EV’s Initial and Final SoC and Arrival and Departure Times
Vahid Bagheri, Amir Farhad Ehyaei, Mohammad Haeri,
Volume 18, Issue 4 (December 2022)
Abstract
In distribution networks, failure to smooth the load curve leads to voltage drop and power quality loss. In this regard, electric vehicle batteries can be used to smooth the load curve. However, to persuade vehicle owners to share their vehicle batteries, we must also consider the owners' profits. A challenging problem is that existing methods do not take into account the vehicle owner demands including initial and final states of charge and arrival and departure times of vehicles. Another problem is that battery capacity of each vehicle varies depending on the type of vehicle; which leads to uncertainties in the charging and discharging dynamics of batteries. In this paper, we propose a modified mean-field method so that the load curve is smoothed, vehicle owner demands are met, and different capacities of electric vehicle batteries are considered. The simulation results show the effectiveness of the proposed method.

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.