Speed Sensorless Direct Torque Control Research Articles

Novel Speed Sensorless DTC Design for a Five-Phase Induction Motor with an Intelligent Fractional Order Controller Based-MRAS Estimator

Abstract This paper presents a fractional-order adaptive mechanism-based model reference adaptive system (MRAS) configuration for speed estimation of sensorless direct torque control (DTC) of a five-phase induction motor. In effect, the fractional-order proportional-integral (FOPI) controller parameters are obtained by the particle swarm optimisation (PSO) algorithm to enhance the MRAS observer response. Thus, the developed algorithm in the speed loop control of the DTC strategy to increase its robustness against disturbances. Moreover, a comparative study has been done of the proposed MRAS-PSO/FOPI speed estimator with the conventional MRAS-proportional-integral (PI) and the PSO-based MRAS-PI. Simulation results have carried out of the different controllers used in the adaptation mechanism of the MRAS estimator, to show the performance and robustness of the proposed MRAS-PSO/FOPI algorithm in use.

Estimation performance of the novel hybrid estimator based on machine learning and extended Kalman filter proposed for speed-sensorless direct torque control of brushless direct current motor

In this study, machine learning (ML) based methods are used to estimate rotor mechanical speed of brushless direct current (BLDC) motors. Training performances of approaches such as Artificial Neural Network, k-Nearest Neighbor, and Random Forest in the ML-based speed estimator are tested using the datas obtained from the direct torque control (DTC) drive system of BLDC motor in simulation and it is seen that the ANN approach has the highest accuracy. In addition, a novel extended Kalman filter (EKF)-based estimator is proposed for the estimation of back-EMFs of BLDC motor. A hybrid estimation method is proposed by using the developed ML-based speed estimator with the proposed EKF-based estimator and its estimation performance is tested in simulation on DTC drive system.

A new intelligent adaptation mechanism of MRAS based on a genetic algorithm applied to speed sensorless direct torque control for induction motor

A new intelligent adaptation mechanism of MRAS based on a genetic algorithm applied to speed sensorless direct torque control for induction motor

Reduced-Sensor-Based PV Array-Fed Direct Torque Control Induction Motor Drive for Water Pumping

This paper aims at the design, control, and implementation of a solar photovoltaic (PV) array-fed speed sensorless direct torque control of an induction motor drive (IMD) for water pumping in a standalone as well as battery-connected hybrid mode. This stator flux estimated by the proposed flux observer is used for speed estimation. A dc-link current sensor is used to reconstruct the motor phase currents by modified active voltage vector. One voltage sensor for dc-link voltage sensing and only one current sensor for dc-link current sensing are used in this system for standalone operation of the system. All other required quantities are estimated through these two sensed signals. The IMD is energized by a PV array, which is operated at maximum power point (MPP). A perturb and observe control algorithm with additional flow rate controller is proposed for MPP, which tracks MPP throughout the operating range and provides the facility to control the flow rate. The suitability of the system is judged through simulated results in MATLAB/Simulink as well as test results obtained on a prototype developed in the laboratory.

Modified DTC of a Six-Phase Induction Motor With a Second-Order Sliding-Mode MRAS-Based Speed Estimator

This paper deals with a model reference adaptive system (MRAS) estimator based on the second-order sliding-mode (SOSM) strategy for speed-sensorless direct torque control (DTC) of a six-phase induction motor. A compensated flux observer is proposed using the well-known supertwisting algorithm, which is inherently an SOSM technique. This observer is adopted as the reference model in the MRAS-based speed estimator to overcome the chattering problem of the classical sliding-mode techniques. The estimator is robust against parameter uncertainties and dc offsets. In addition, a supertwisting-algorithm-based second-order sliding-mode (ST-SOSM) controller is designed for the speed loop in the DTC strategy to increase its robustness under applying external load disturbances. The speed control loop needs the load torque signal. For this purpose, an ST-SOSM load torque observer is proposed, where it provides a robust performance without the penalty of high chattering. Simulation and experimental results confirm the validity and the effectiveness of the proposed approaches.

Dynamic Hysteresis Torque Band for Improving the Performance of Lookup-Table-Based DTC of Induction Machines

The magnitude of hysteresis torque band has a considerable effect on the performance of two-level direct torque control (DTC) of induction machines. The conventional DTC fails at low speed due to the poor flux regulation. In this paper, two dynamic hysteresis torque band (DHTB) strategies for the conventional DTC are proposed to solve this problem by dynamically altering the amplitude of hysteresis torque band based on a flux error range. In this way, the simplicity of DTC algorithm is retained since it only requires a minor modification on its structure. The paper also presents further analysis on flux degradation, particularly the droop in between the flux sectors. In addition, the switching frequency effect of reverse voltage vectors for both DHTB schemes is investigated on the performance of the speed-sensorless DTC drive. The effectiveness of the proposed schemes is confirmed by simulation and experimental validation. Results show a significant enhancement in the flux regulation and dynamic torque response from zero motor speed.

Online Speed Estimation Using Artificial Neural Network for Speed Sensorless Direct Torque Control of Induction Motor based on Constant V/F Control Technique

This paper presents the speed estimator for speed sensorless direct torque control of a three-phase induction motor based on constant voltage per frequency (V/F) control technique, using artificial neural network (ANN). The estimated stator current equation is derived and rearranged consistent with the control algorithm and ANN structure. For the speed estimation, a weight in ANN, which relates to the speed, is adjusted by using Widrow–Hoff learning rule to minimize the sum of squared errors between the measured stator current and the estimated stator current from ANN output. The consequence of using this method leads to the ability of online speed estimation and simple ANN structure. The simulation and experimental results in high- and low-speed regions have confirmed the validity of the proposed speed estimation method.

Constant Switching Frequency DTC for Matrix Converter Fed Speed Sensorless Induction Motor Drive

The paper presents a constant switching frequency scheme for speed sensorless Direct Torque Control (DTC) of Matrix Converter fed Induction Motor Drive. The use of matrix converter facilitates improved power quality on input as well as motor side, along with Input Power Factor control, besides eliminating the need for heavy passive elements. Moreover, DTC through Space Vector Modulation helps in achieving a fast control over the torque and flux of the motor, with added benefit of constant switching frequency. A constant switching frequency aids in maintaining desired power quality of AC mains current even at low motor speeds, and simplifies input filter design of the matrix converter, as compared to conventional hysteresis based DTC. Further, stator voltage estimation from sensed input voltage, and subsequent stator (and rotor) flux estimation is done. For speed sensorless operation, a Model Reference Adaptive System is used, which emulates the speed dependent rotor flux equations of the induction motor. The error between conventionally estimated rotor flux (reference model) and the rotor flux estimated through the adaptive observer is processed through PI controller to generate the rotor speed estimate.

Speed‐sensorless direct torque control scheme for matrix converter driven induction motor

A speed-sensorless direct torque control (DTC) system and control means of AC motor based on matrix converter (MC) fed was proposed, for reducing harmonic pollution and advancing control accuracy. At the base of expounding MC and speed-sensorless DTC means, both the fusion technology and model reference of rotational speed are discussed with emphasis, and the latter has adaptive parameters. Experimental results show that accuracy of parameter identification is higher than the measurable accuracy of measure module, and dynamic response is also fast, the predominance of MC and DTC are exerted at the same time. The system not only can realise the control request of torque and flux linkage as speed accelerates or loaded torque of AC motor changes, but also can run steadily, furthermore actualise energy bi-directional flow and input unity power factor.

A simplified three-level SVM-DTC induction motor drive with speed and stator resistance estimation based on extended Kalman filter

In this paper, a speed-sensorless direct torque control (DTC) drive for induction motors (IMs) fed by three-level neutral-point clamped (NPC) inverter has been investigated. The main objective of the study is to solve two different problems in DTC drive with three-level NPC inverter. First, the conventional switching table fails to consider some limitations caused by the topology of NPC inverter. As a solution to this problem, a new switching method based on simplified three-level space-vector modulation (SVM) technique has been developed by fulfilling both neutral-point potential balance and soft commutation requirements needed for three-level NPC inverters. Other problem is to make accurate estimates, especially in very low and zero speed operation. To address this issue, an extended Kalman filter (EKF)-based observer has been utilized for the estimation of rotor speed, load torque, and flux. The estimated load torque is used to improve the response of speed estimation in both transient and steady states. The stator resistance has also been estimated simultaneously to make more robust and reliable flux estimation. The proposed drive system has been tested under some challenging conditions and verified by the simulation results.

Simple Flux Regulation for Improving State Estimation at Very Low and Zero Speed of a Speed Sensorless Direct Torque Control of an Induction Motor

This paper presents a simple flux regulation for a direct torque control (DTC) of an induction motor (IM) to improve speed and torque estimations at low- and zero-speed regions. To accomplish this, a constant switching frequency controller (CSFC) is used to replace the three-level hysteresis torque comparator of a DTC IM. The DTC of IM utilizing CSFC (DTC-CSFC) retains the simple structure of a lookup table-based DTC drive. With DTC-CSFC, constant switching frequency is maintained, and at the same, the flux droop problem that normally occurs in DTC with the hysteresis controller (DTC-HC) at low speed is solved; subsequently, the stator flux and torque estimations at low speed are also improved. In the proposed system, the speed feedback for the closed-loop speed control is estimated using an extended Kalman filter, which requires heavy real-time computation. However, due to the simple structure of DTC-CSFC, small sampling time, hence large control bandwidth is possible. The performances of the speed sensorless DTC-HC and DTC-CSFC are compared experimentally under different operating conditions. With the improved stator flux regulation, experimental results of the DTC-CSFC showed a significant improvement in speed and torque estimations at very low and zero-frequency operations.

MRAS Speed Estimator Based on Type-1 and Type-2 Fuzzy Logic Controller for the Speed Sensorless DTFC-SVPWM of an Induction Motor Drive

This paper presents model reference adaptive system speed estimators based on Type-1 and Type-2 fuzzy logic controllers for the speed sensorless direct torque and flux control of an induction motor drive (IMD) using space vector pulse width modulation. A Type-1 fuzzy logic controller (T1FLC) based adaptation mechanism scheme is initially presented to achieve high performance sensorless drive in both transient as well as in steady-state conditions. However, the Type-1 fuzzy sets are certain and cannot work effectively when a higher degree of uncertainties occurs in the system, which can be caused by sudden changes in speed or different load disturbances and, process noise. Therefore, a new Type-2 FLC (T2FLC) - based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties, improve the performance, and is also robust to different load torque and sudden changes in speed conditions. The detailed performance of different adaptation mechanism schemes are performed in a MATLAB/Simulink environment with a speed sensor and sensorless modes of operation when an IMD is operates under different operating conditions, such as no-load, load, and sudden changes in speed. To validate the different control approaches, the system is also implemented on a real-time system, and adequate results are reported for its validation.

Type-2 fuzzy logic control based MRAS speed estimator for speed sensorless direct torque and flux control of an induction motor drive

In this research study, a model reference adaptive system (MRAS) speed estimator for speed sensorless direct torque and flux control (DTFC) of an induction motor drive (IMD) using two adaptation mechanism schemes are proposed to replace the conventional proportional integral controller (PIC). The first adaptation mechanism scheme is based on Type-1 fuzzy logic controller (T1FLC), which is used to achieve high performance sensorless drive in both transient as well as steady state conditions. However, the Type-1 fuzzy sets are certain and unable to work effectively when higher degree of uncertainties presents in the system which can be caused by sudden change in speed or different load disturbances, process noise etc. Therefore, a new Type-2 fuzzy logic controller (T2FLC) based adaptation mechanism scheme is proposed to better handle the higher degree of uncertainties and improves the performance and also robust to various load torque and sudden change in speed conditions, respectively. The detailed performances of various adaptation mechanism schemes are carried out in a MATLAB/Simulink environment with a speed sensor and speed sensorless modes of operation when an IMD is operating under different operating conditions, such as, no-load, load and sudden change in speed, respectively. To validate the different control approaches, the system also implemented on real-time system and adequate results are reported for its validation.

Simulation Reach of Permanent Magnet Synchronous Motor System Based on Speed Sensor-Less Direct Torque Control

The simulation model of permanent magnet synchronous motor system based on speed sensor-less direct torque control is built by analysing the mathematic model of permanent magnet synchronous motor and the theory of direct torque control in this dissertation, and the system’s speed and position is estimated by calculating the angle of stator flux linkage. MATLAB/Simulink is utilized to simulate the system, and the simulation results are analyzed, with which the simulation result prove the correctness and feasibility of the estimation using in this dissertation and good dynamic response performance of the system.

Rotor Speed and Stator Resistance Identification of Direct Torque Control for Induction Motor Based on Mutual MRAS

Based on the dynamic mathematical model of induction motor, the mutual model reference adaptive system method (MRAS) for rotor speed identification is proposed to implement a speed sensorless direct torque control of induction motor. The model reference adaptive theory is flexibly used in the rotor speed and the stator resistance online identification. The reference model and adjustable model used in the mutual MRAS scheme are interchangeable. Therefore, The induction motor speed sensorless direct torque control system can obtain high-precision speed identification. Computer simulations and experimental results show that the method can solve the problems of speed control accuracy and system stability under the influence of motor parameter variation. The low speed performance of DTC is also improved.

High-Performance Speed Sensorless Direct Torque Control of PMSM

A high-performance speed sensorless direct torque control (DTC) system of permanent magnet synchronous motor (PMSM) is presented in this paper. The stator flux linkage, speed, rotor position and load torque of PMSM are observed using a fourth-order Extended Kalman Filter (EKF) and a second-order Kalman Filter (KF) and the observed load torque is used for feed-forward compensation of reference torque. Simulation results clearly demonstrate the performance of speed can be improved when load torque is changed and the validity of the proposed control strategy.

Rotor Speed Adaptive Identification of Direct Torque Control for Induction Motor

Based on the dynamic mathematical model of induction motor, the mutual model reference adaptive system method (MRAS) for rotor speed identification is proposed to implement a speed sensorless direct torque control. The model reference adaptive theory is flexibly used in the rotor speed and the stator resistance online identification. The reference model and adjustable model used in the mutual MRAS scheme are interchangeable. Therefore, the control system can obtain high-precision speed identification. Simulation results show the method can solve the problems of speed control accuracy and system stability under the influence of motor parameter variation. The low speed performance of DTC is also improved.

Speed sensorless DTC control of the induction motor using FPGA implementation

PurposeThe purpose of this paper is to present a fixed‐point implementation of a complete direct torque control (DTC) algorithm connected with a rotor speed estimation algorithm for the induction motor drive, using field‐programmable gate array (FPGA).Design/methodology/approachThe parallel processing approach is described, which requires a decomposition of the control and estimation algorithms for the converter‐fed induction motor to several tasks, realised in parallel. The advanced data processing techniques are described, like PIPELINE technique for data streams design, coordinate rotation digital computer algorithm for transformation of stator flux vector components from Cartesian to polar coordinates. Moreover, the method for the qualitative analysis of the full‐order state observer's sensitivity to the variations of the induction motor equivalent circuit parameters is presented.FindingsIt is shown that the developed FPGA‐based DTC structure enables designing an efficient application for the induction motor control. Owing to the high‐processing frequency, the digital FPGA‐based DTC application is similar in its features to the analogue realisation based on the comparators. Yet all the advantages of the digital structure, i.e. high flexibility, parameterization capability, etc. remain unchanged. Furthermore, FPGA is hardware realisation of a digital data processing algorithm; hence the reliability of the control system is improved.Research limitations/implicationsThe investigations are performed in the developing prototype setup, based on PXI‐1042 Industrial PC equipped with Xilinx Virtex‐II FPGA matrix, programmed with LabVIEW.Practical implicationsThe experimental tests of the FPGA‐based implementation of the whole control structure of the sensorless DTC drive system are demonstrated. It is also shown, that the full‐order state observer with the speed adaptation loop is significantly sensitive to motor parameter variations in the low‐speed region, which must be taken into account while designing the adaptation algorithm for speed estimation in real application.Originality/valueThe paper's value lies in the overall, FPGA‐based design of the speed sensorless DTC structure for the induction motor including motor speed, torque and stator flux control loops, stator flux and rotor speed estimation.

Sensorless Direct Torque and Flux-Controlled IPM Synchronous Motor Drive at Very Low Speed Without Signal Injection

This paper proposes a novel speed-sensorless direct torque and flux control scheme for an interior permanent-magnet synchronous motor drive. The drive uses a new stator flux observer based on the extended rotor flux concept. Due to the simultaneous implementation of stationary and rotating reference frames, the proposed observer does not require any speed adaptation and is inherently sensorless. Unlike speed adaptive observers, the proposed observer is immune to speed estimation errors; thus, its performance at very low speed is improved significantly. A novel stator resistance estimator is incorporated into the sensorless drive to compensate the effects of stator resistance variation. The global asymptotic stabilities of both the flux observer and stator resistance estimator are guaranteed by the Lyapunov stability analysis. Simulation and experimental results at very low speeds, including 0 and 5 r/min, confirm the effectiveness of the proposed method.

Sensorless Direct Torque Control of Five-Phase Interior Permanent-Magnet Motor Drives

This paper presents the sensorless direct torque control (DTC) technique for five-phase interior permanent magnet (IPM) motors. By using the introduced technique fast torque response with low ripple in the stator flux and torque of the five-phase interior permanent magnet motor can be achieved. Having thirty-two space voltage vectors provides great flexibility in selecting the inverter switching states. Therefore, the stator flux and torque can be more precisely adjusted. Position information and speed are being estimated based on the position of the stator flux linkages. The mathematical model of the five-phase interior permanent magnet motor is first derived. Later, the speed sensorless direct torque control method of the five-phase IPM is introduced. A five phase interior permanent magnet motor and five leg IGBT based inverter were designed and fabricated in the laboratory. The control method is implemented on a TMS320C32 digital signal processor board.