An intelligent fuzzy sliding mode controller for a BLDC motor

BLDC motors are generally implemented in copious industrial processes because of its high proficiency, large torque and minimum volume. The variation in load torque, causes the variation of speed in BLDC motor, which leads the complete system in unstable condition. In this paper a robust first-order SM controller scheme depends on twofold controlling algorithm for angular velocity and also current control in Brushless DC motor to attenuate the chattering problems. Two cascaded sliding mode controllers of first-order are used and first sliding mode controller generates stator currents based on speed error then the second SM controller generates voltage based on current-error in stator which runs the universal bridge by this controlled voltage source. In addition to the method suggested by Slotine, two feed forward loops are added to both speed and current errors to improve the response. The existing sliding-mode control is unresponsive to uncertainties and will cause undesirable chattering problems. To overcome this snag, a manual control law in conjunction with Sliding mode control is utilized that provides smooth and chattering free actual control signal. The overall system stability performance is implemented in MATLAB/SIMULINK and simulation results shows that proposed scheme is robust with respect to uncertainty in the system

Section: Proposed Controlling Schemementioning

confidence: 99%

Speed Characteristics of Two-Fold Sliding Mode Control of BLDC Motor

Murali¹,

Rao²

2019

“…BLDCMs exhibit several advantages over brushed DC motors. In particular, they require lower maintenance due to the disposal of the commutator, have longer operating life due to the lack of friction and electrical losses and achieve higher power density; these characteristics make them ideal candidates for applications that require high electromagnetic torque-to-weight ratio [1]. Compared with brushed DC motors and induction machines, BLDCMs have lower inertia, enabling faster dynamic response to reference commands.…”

Section: Introductionmentioning

confidence: 99%

Experimental Design and Implementation of IT2FL-controlled BLDCM Based on LabVIEW™

Abed*,

Humaidi,

humod

et al. 2019

This article presents design and implementation of Interval Type-2 Fuzzy Logic Controller (IT2FLC) for speed control of brushless DC motor (BLDCM) based on LabVIEW package. For the purpose of comparison, the performance of IT2FLC is compared to Type-1 FL controller (T1FLC). For fair comparison, both schemes of FL controllers are set with the same number of membership functions and input-output gain values. The robustness characteristics of both FL controllers are assessed in terms of dynamic performance and load rejection capaility. The design of IT2FLC and T1FLC are made and implemented within LabVIEW environment and the effectiveness of controllers are verified experimentally. The experimental results showed that IT2FL controller gives better robustness under load variation than conventional T1FL controller.

“…BLDC motors have some advantages over its brushed DC counterpart. BLDC motors require minimal maintenance due to the disposal of the commutator, have a long operating life because of the lack of friction and electrical loss and have high power density which translates to possible applications that require a high electromagnetic torque-to-weight ratio [1]. Compared with brushed DC motors and induction machines, BLDC motors have lower inertia, thus permitting faster dynamic response to reference commands.…”

Section: Introductionmentioning

confidence: 99%

“…Compared with brushed DC motors and induction machines, BLDC motors have lower inertia, thus permitting faster dynamic response to reference commands. They also have high efficiency given their permanent magnets which perform in virtually zero rotor losses [1].…”

Section: Introductionmentioning

confidence: 99%

Robust IT2FL Controller Design for the Speed Control of a BLDC Motor

Abed*,

humod,

Humaidi

et al. 2019

This work presents the design of intelligent controller for the speed control of a brushless DC motor under uncertainty in motor parameters. The Interval Type 2 Fuzzy Logic (IT2FL) controller has been proposed and designed to achieve the speed control specifications. A comparative study is conducted between IT2FL and PID controllers in terms of tracking performance and robustness characteristics. The effectiveness of both controller structures is verified through simulation within a MATLAB/Simulink environment. The simulated results showed that the IT2FL controller is more efficient than the PID counterpart in terms of tracking and robustness.