This work analyzes the advantages of Artificial Neural Networks applied to sensorless control for Switched Reluctance Motors. Due to the non-linear electrical characteristics of Switched Reluctance Motors, Artificial Neural Networks perform a good tool and for torque ripple minimization in Switched Reluctance Motors. The simulation results to prove the efficiency of a multilayer perceptron in o...

prompt detection and diagnosis of faults in industrial systems areessential to minimize the production losses, increase the safety of the operatorand the equipment. several techniques are available in the literature to achievethese objectives. this paper presents fuzzy based control and fault detection for a6/4 switched reluctance motor. the fuzzy logic control performs like a classicalproporti...

this paper presents a new control structure to reduce torque ripple in switched reluctance motor. although srm possesses many advantages in motor structure, it suers from large torque ripple that causes some problems such as vibration and acoustic noise. in this paper another control loop is added and torque ripple is de ned as an objective function. by using fuzzy sliding mode strategy, the dc...

electric and hybrid electric vehicles are attractive candidates for sustainable transportation due to its higher efficiency and low emission. the critical choice on the electric motors is its capability of motoring and regenerative braking characteristics. switched reluctance machines are viable candidate as with proper control and extended constant power range operation replacing the multi-gea...

Shaft position sensing is an essential part of switched reluctance (SR) motor drive In order to synchronize the pulses of phase current with the period of rising inductance of the proper motor phase. Direct sensors such as, Hall effect and optical encoder are commonly used in SR motors. The purpose of this paper is to present an indirect shaft positioning sensing known as "sensorless " control ...