Design An Optimal Robust Integral Signum Of The Error Controller For Electrical Vehicle Based On Salp Swarm Optimization Algorithm - Info and Reading Options
"Design An Optimal Robust Integral Signum Of The Error Controller For Electrical Vehicle Based On Salp Swarm Optimization Algorithm" and the language of the book is English.
“Design An Optimal Robust Integral Signum Of The Error Controller For Electrical Vehicle Based On Salp Swarm Optimization Algorithm” Metadata:
- Title: ➤ Design An Optimal Robust Integral Signum Of The Error Controller For Electrical Vehicle Based On Salp Swarm Optimization Algorithm
- Language: English
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- Internet Archive ID: ➤ 10.11591ijpeds.v15.i3.pp1369-1378
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"Design An Optimal Robust Integral Signum Of The Error Controller For Electrical Vehicle Based On Salp Swarm Optimization Algorithm" Description:
The Internet Archive:
The electric vehicle (EV) has nowadays become a suitable alternative to clean and sustainable energy emissions in transportation, so researchers have become interested in modeling and controlling the electric vehicle.in this paper, an optimal robust integral signum of the error (ORISE) controller is designed to control the actuator speed of an electric vehicle. The actuator type of this vehicle is three-phase induction motor (IM). By reducing the discrepancy between the desired and actual output, the standard salp swarm algorithm (SSA) is utilized to find the optimal suggested ORISE parameter. The suggested controller tested by different desired velocity trajectory. Simulation results demonstrate that the ORISE have high performance, fast and accurate tracking for the EV speed, compare with PID controller that the output speed suffer from chattering and has higher oscillation. In particular, the SSA-based ORISE controller is superior to the proportional-integral-derivative (PID)-based SSA method in terms of no steady-state error and smallest overshoot (0.002% with ORISE while 0.05% with PID) prevention for electric vehicle (EV) speed despite the better results of settling time and rising time obtained in PID (1.532s and 0.785s) respectively while these values were (1.574s and 1.915s) respectively, in ORISE. The MATLAB (R2020a)/Simulink environment is used for all projects.
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