A Fractional Order Controller for Sensorless Speed Control of an Induction Motor

Nosheen, Tayyaba; Ali, Ahsan; Chaudhry, Muhammad Umar; Nazarenko, Dmitry; Shaikh, Inam Ul Hasan; Bolshev, Vadim; Iqbal, Muhammad Munwar; Khalid, Sohail; Панченко, Владимир

doi:10.3390/en16041901

Cited by 18 publications

(6 citation statements)

References 29 publications

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“…The excess power from PV source if any could be utilized to charge the battery bank and supply it to the drive under unavailability of PV source as a backup source for short duration of time. However, the sizing and viability of battery backup is determined upon economics of the system [28]. The battery backup was considered in the study to achieve reliable operation of the drive under unavailability of grid power and PV power.…”

Section: System Descriptionmentioning

confidence: 99%

“…where a, a 0 , a 1 , a 2 and b are constants [28,29] and W hp is the horsepower, and H represents the total dynamic head (in feet).The pump should run at a power which is greater than W hp to increase its efficiency. The brake horsepower (BHP) is the power essential at the pump shaft to pump an actual flow rate against a specified H, given by,…”

Section: Selection Of Componentsmentioning

confidence: 99%

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TS fuzzy control of PV assisted single phase three phase induction motor drive for rural pumping applications

Rami Reddy,

Mudundi,

Kumar

et al. 2024

TESEA

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The motor drives for aqua farms and large-scale irrigation system needs a reliable electric drive, which requires the continuous power supply and efficient control. However, the rural single phase power supply is frequently interrupted. Renewable assistance would improve the availability of supply and heuristic control approach improves robustness in control. This paper presents a three phase induction motor drive fed from single phase electric grid with assistance from PV and battery energy storage. TS- fuzzy based direct torque control is employed for robust control during load changes, and the topology, component modelling, front-end converter control, PV interface DC–DC converter control, and inverter control are presented. MATLAB/Simulink is used to simulate the proposed drive system. The performance of the proposed system is validated using simulation data for both steady-state and transient states.

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Section: System Descriptionmentioning

confidence: 99%

Section: Selection Of Componentsmentioning

confidence: 99%

TS fuzzy control of PV assisted single phase three phase induction motor drive for rural pumping applications

Rami Reddy,

Mudundi,

Kumar

et al. 2024

TESEA

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“…However, more degrees of freedom are provided with the advent of fractional order regulators PI𝜇Dμ, which are a generalization of integer integration and differentiation to a fractional (or non‐integer) order. Many researchers have implemented them or some of their variants, like FOPI and FOIP, due to their ability to exploit the non‐linearity nature and damping feature, ensuring the best system tuning [2, 3].…”

Section: Introductionmentioning

confidence: 99%

Driving an asynchronous motor powered by PV‐MPPT using equivalent RST controller of fractional order PI and IP, based on generalized predictive control

Nemouchi,

Rezgui,

Babqi

et al. 2024

IET Generation Trans & Dist

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The article introduces a new model of a Reference Signal Tracking (RST) controller for the fractional order quantities. The controller is applied to an indirect field‐oriented control (IFOC) system used for the speed control of an asynchronous motor powered by a photovoltaic (PV) generator with a maximum power point tracking (MPPT) algorithm. This model utilizes two fractional order controllers: the fractional order proportional‐integral (FOPI) regulator and the fractional‐order integral‐proportional (FOIP) regulator. These controllers are used with the generalized predictive control (GPC) technique. The first step in the approach is to derive the equivalent digital RST controller's model from the FOPI and FOIP controller's transfer functions. The GPC technique converts the continuous‐time FOPI (and FOIP) controller into a discrete‐time version. This conversion ensures a fast response and effective disturbance rejection. Simulation tests are conducted to analyze the rotor speed and stator current ripples to evaluate the performance of the proposed method. The results demonstrate the effectiveness of the introduced scheme in achieving improved control performance in terms of response speed and disturbance rejection. The article presents a modified RST controller model based on the fractional order approach applied to an IFOC system for motor speed control driven by a photovoltaic generator. Using FOPI, FOIP controllers, and GPC contributes to enhanced control performance, as evidenced by the simulation results.

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“…Compared with a proportional integral controller and conventional ADRC, simulations and experiments verified that the proposed control strategy has good input interference suppression and measurement noise suppression capabilities.Compared with the recently developed control method without anti-integral saturation compensation, the strategy applied to temperature control of jacket crystallizer is superior. In addition, some scholars have proposed other control methods about fractional order [12].…”

Section: Introductionmentioning

confidence: 99%

Reactor Temperature Control Based on Improved Fractional Order Self-Anti-Disturbance

Tang

2023

Processes

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In the chemical industry, a reactor is an absolutely necessary container. The fact that its dynamic qualities are nonlinear and unknown, however, is what causes the temperature to deviate from the value that was specified. As a result, the typical PID control cannot fulfill the prerequisites of the production process. A new nonlinear function is presented to replace the function that was previously used, and a temperature controller that is based on better fractional order active disturbance rejection is devised. On the basis of a new fractional order temperature detector (FOTD), a new fractional order equilibrium state observer (FOESO), and nonlinear function, an improved fractional order active disturbance rejection controller has been developed. A model of the reactor was created, and the dynamic properties of temperature control were investigated. By simulation and experimentation, it was demonstrated that the strategy has a number of benefits and is effective. In this approach, the information provided by the model is exploited to its maximum potential, and the temperature of the inlet cooling water is employed as the temperature control disturbance for feedforward compensation. Over the entirety of the process, this guarantees that the desired temperature will be preserved. When compared to FADRC, PID, and ADRC, the rising time is increased by 5 s, and the overshoot is raised by 25%. It has been established that the fraction-order active disturbance rejection controller has a quicker response speed, a higher capacity for anti-interference, and a quicker speed of stabilization.

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A Fractional Order Controller for Sensorless Speed Control of an Induction Motor

Cited by 18 publications

References 29 publications

TS fuzzy control of PV assisted single phase three phase induction motor drive for rural pumping applications

TS fuzzy control of PV assisted single phase three phase induction motor drive for rural pumping applications

Driving an asynchronous motor powered by PV‐MPPT using equivalent RST controller of fractional order PI and IP, based on generalized predictive control

Reactor Temperature Control Based on Improved Fractional Order Self-Anti-Disturbance

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