Speed sensorless control of a converter-fed DC motor

Jahmeerbacus, M. I.; Oolun, M.K.; Bhurtun, C.; Soyjaudah, K. M. S.

doi:10.1109/afrcon.1999.820906

Cited by 9 publications

(2 citation statements)

References 4 publications

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“…Jahmeerbacus et al [2] in 1999 proposed a speed control for a sensor-less DC motor application. The DC motor was powered by DC to DC converter with a Buck topology.…”

Section: Introductionmentioning

confidence: 99%

Flatness Based Control of a Buck-Converter/DC-Motor Combination

Silva‐Ortigoza

Alba-Martínez

Marciano-Melchor

et al. 2012

2012 IEEE Ninth Electronics, Robotics and Automotive Mechanics Conference

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This paper shows a control law designed for a DC/DC Buck-Power-Converter and DC-motor system by using the differential flatness property of the plant model. This approach is meant to perform angular speed control for tracking trajectory applications. The flatness property of the DC motor model is exploited in order to propose a highhierarchal control system, which allows the angular speed to track a desired trajectory. This controller provides the voltage profiles that must be tracked by the Buck converter and a low-hierarchical control is designed in order to ensure the aforementioned. This is accomplished using another flatness based control. The findings are verified through numerical simulations with Matlab-Simulink software.

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“…Jahmeerbacus et al [2] in 1999 proposed a speed control for a sensor-less DC motor application. The DC motor was powered by DC to DC converter with a Buck topology.…”

Section: Introductionmentioning

confidence: 99%

Flatness Based Control of a Buck-Converter/DC-Motor Combination

Silva‐Ortigoza

Alba-Martínez

Marciano-Melchor

et al. 2012

2012 IEEE Ninth Electronics, Robotics and Automotive Mechanics Conference

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“…Due to their effectiveness and robustness, DC motors are widely employed in various industrial applications, partic-ularly those that require accurate speed control including servo control and traction activities. [1][2][3][4][5][6][7] These motors are powered by a DC source, which is where the majority of renewable energy sources are produced. These sources are PV systems, 8 Fuel cell systems, 9 and some electrical generators in wind applications like permanent magnet synchronous machines 10 and switched reluctance machines.…”

Section: Introductionmentioning

confidence: 99%

DC motor control using model reference adaptive control

Mosaad¹

2023

Yanbu Journal of Engineering and Science

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Despite having higher maintenance costs than AC motors, DC motors had been widely employed in the industry due to their outstanding speed control capabilities. This employment increased due to the DC output of some renewable sources recently. This article introduces the speed control of DC motors using model reference adaptive control (MRAC). This control is achieved through regulating the armature voltage at different load changes. A comparison between the proposed adaptive controller and optimized PI controller using the elephant herding optimization (EHO) is presented. The PI controller parameters were optimality adjusted to minimize the integral absolute error, minimum overshoot, and minimum settling time. Computer simulations show that the suggested MRAC is preferable to a traditional optimized PI controller. In addition, the proposed controller is effective in regulating the DC motor over a broad range of operating speeds.

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Nonlinear Adaptive Neural Control of Power Converter‐Driven DC Motor System: Design and Experimental Validation

Nizami,

Gangula,

Udumula

et al. 2024

Engineering Reports

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This article presents an intelligent adaptive neural control scheme to track the output speed trajectory in power converter‐driven DC motor system. The proposed technique integrates an adaptive polynomial‐neural network with a backstepping strategy to yield a robust control system for output tracking in DC motor. Such a unification of online neural network‐based estimation and adaptive control, results in effective regulation of the output across a wide load torque uncertainties, besides yielding a promising transient and steady‐state performance. The stability of the entire closed‐loop system is ensured through Lyapunov stability criterion. The efficacy of the proposed strategy is revealed through an extensive experimental investigation under various operating points during start‐up, step‐reference tracking, and external step‐load torque disturbances. The real‐time experimentation is conducted on a laboratory prototype of power converter‐driven DC motor of 200 W, using dspace DS1104 control board with MPC8240 processor. The results obtained confirm an improvement in the transient response of the output speed by significantly reducing the settling time to and yielding a steady state behavior with no peak over/undershoots during load disturbances, in contrast to other similar works presented in the literature intended for same the application.

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Speed sensorless control of a converter-fed DC motor

Cited by 9 publications

References 4 publications

Flatness Based Control of a Buck-Converter/DC-Motor Combination

Flatness Based Control of a Buck-Converter/DC-Motor Combination

DC motor control using model reference adaptive control

Nonlinear Adaptive Neural Control of Power Converter‐Driven DC Motor System: Design and Experimental Validation

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