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The Thu Thiem road tunnel located deep under the Saigon River is currently ventilated by a system of 12 jet fans that push dust and dirty air out into the environment. These jet fans are driven by Induction Motors (IMs) modeled by mathematical equations on the structural nonlinear dq coordinate system, so the conventional linear controllers partly fail to meet the response requirements. Therefore, this paper proposes the application of the exact linearization control method for the current loop in the Field Oriented Control (FOC) structure of an IM that drives a jet fan of the Thu Thiem road tunnel. This is a control method based on a linearization model with cascaded loops. The stator current controller controls two currents: isd controls the flux, and isq controls the torque. The control design is verified by the simulation results on Matlab/Simulink with data collected from the jet fan system of the Thu Thiem road tunnel. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study proposes enhancing induction motor (IM) drive systems by developing a DTC-MC with SVPWM integration to reduce ripple. DTC-MC is effective for precise torque control in AC drives, offering high control accuracy by isolating stator flux and torque. The method excels in sensor-less speed control, maintaining unity input power factor at low speeds, and constant switching frequency for rapid torque adjustments. Combining DTC-MC with SVPWM improves simplicity, dynamic behavior, and torque response. The DTC-SVM approach further refines the torque response by correcting flux and torque discrepancies. MATLAB/SIMULINK simulations validated the approach, showing a robust dynamic response and significantly reduced motor torque ripple and control of speed.

This paper introduces a neural network adjustment method for a single gain of an integral proportional (IP) speed regulator, to improve the speed control of an induction motor. Thanks to its simplicity and strength, the integral proportional (IP) controller is widely used in the industry for speed control. Yet, in some cases, when the load or mechanical parameters change according to its working conditions, the integral proportional (IP) efficiency decreases, and the setup quality degrades. In this case, a neural IP-self-tuning seems to overcome these difficulties and ensure a good control performance. The results obtained through the implementation of the proposed control on a dSPACE system and an induction motor clearly demonstrate the effectiveness of this method. [ABSTRACT FROM AUTHOR]

Induction motors (IMs) are extensively used in industrial sector. This kind of machine is subjected to several stresses that could interrupt their normal operation. An excessive stress can generate some symptoms before the IM fall in failure situation. Therefore, incipient detection of these symptoms permits the shutdown of IMs in order to avoid total destruction. Fault detection is then the main objective of diagnosis systems. Stator inter-turn short-circuits (SITSC) constitutes an important amount of cause of IM breakdown. However; unbalance supply voltage (USV) is one of the advantageous factors that affect IMs operation. Thus, in order to avoid false alarm induced by USV, the diagnosis system must make difference between USV and SITSC faults. This paper presents an efficient approach to estimate SITSC percentage and detect USV occurrence using Artificial Intelligent (AI) tool. Artificial neuronal network (ANN) plays the key-role of the proposed diagnosis system. A fault Classifier of SITSC and USV is carried out using multi-layer perceptron neuronal network (MLP-NN). The training, testing and validation phases of MLP-NN need the dataset creation. The required data is obtained from both simulated mathematical model of IM and laboratory test-bed. The reached results show the sensitivity and the well-functioning of the proposed diagnosis system. • The detection of Stator Inter-Turn Short-Circuits fault is much more based on its severity and location. • The presence of Unbalanced Supply Voltage makes us unable to know whether there is a SITSC fault or not; that's why identification of Unbalanced Supply Voltage is also very important. • The challenge of this work is to estimate the percentage of Stator Inter-Turn Short-Circuits and detect the presence Unbalanced Supply Voltage utilizing only current & voltage signals. • An MLP-NN is created and simulated for a mathematical model of the motor; in order to choose the appropriate architecture and to verify the efficacy of the proposed diagnosis system. • In the experimental investigation, no additional sensors are required since the terminal voltage and current measurements are sufficient. • the experimental investigation is adopted in order to prove the effectiveness of MLP-NN by using untreated cases of Stator Inter-Turn Short-Circuits fault and Unbalanced Supply Voltage. • The work in the paper has been compared to similar ones, and it has been found that the proposed method is efficient and has good accuracy compared to the others. • The work in the paper can be implemented on microcontroller due to its simplicity. [ABSTRACT FROM AUTHOR]

Introduction/purpose: Among excellent strategies available to control the torque of asynchronous motors, we distinguish direct torque control. This technique of control allows direct control of magnetic flux and electromagnetic torque without the need to decouple them. Also, direct torque control like each control strategy has some drawbacks, the major drawbacks of this technique being operation at a variable switching frequency and flux and electromagnetic ripples due to the use of hysteresis regulators. It worsens acoustic noise, especially at low speeds, as well as the control performances. Methods: To improve the performance of direct torque control especially at low speeds, the authors propose using fractional order PID in combination with type-2 fuzzy logic controllers to regulate the speed of an induction motor controlled by direct torque control. Results: The results obtained by the proposed regulators show the improvements made to the system. Conclusion: The proposed contribution can exert better control efforts.

Due to the susceptibility of low-power three-phase induction motors (IMs) to stator inter-turn short-circuits (ITSC), researchers have been required to develop practical and cost-effective online systems for detecting faults in the stator winding. It is highly recommended to detect faults at a low fault severity level, as the fault current circulating through the shorted turns exponentially increases due to a reduction in insulation resistance and associated insulation degradation. The proposed Voltage–Current (VI) loci-based technique is a non-invasive, less expensive, and fault-sensitive approach that has been scarcely implemented in industries for stator ITSC faults analysis and accurate faulty phase identification, even under low fault severity. The proposed algorithm can compensate for various factors such as unbalanced supply voltages, asymmetries in winding construction, and errors in sensing element calibration. Experimental results presented for a three-phase 1 hp, 415 V SCIM investigate and validate the competency of the proposed work.

Introduction/purpose: Among excellent strategies available to control the torque of asynchronous motors, we distinguish direct torque control. This technique of control allows direct control of magnetic flux and electromagnetic torque without the need to decouple them. Also, direct torque control like each control strategy has some drawbacks, the major drawbacks of this technique being operation at a variable switching frequency and flux and electromagnetic ripples due to the use of hysteresis regulators. It worsens acoustic noise, especially at low speeds, as well as the control performances. Methods: To improve the performance of direct torque control especially at low speeds, the authors propose using fractional order PID in combination with type-2 fuzzy logic controllers to regulate the speed of an induction motor controlled by direct torque control. Results: The results obtained by the proposed regulators show the improvements made to the system. Conclusion: The proposed contribution can exert better control efforts. [ABSTRACT FROM AUTHOR]

This paper focuses on the Fault-Tolerant Tracking Control (FTTC) design for a PV pumping system using an Induction Motor (IM) drive. This control strategy offsets the effect of the sensor faults and ensures the transfer of optimal power to unit motor–pump. First, to simultaneously estimate the system states and the sensor faults, we developed a Takagi Sugeno (TS) fuzzy descriptor observer. After that, a fault-tolerant controller is synthesized and it is able to track the desired trajectory delivered by a TS fuzzy reference model. The developed control strategy is based on the Lyapunov theory and the H∞ approach, to minimize the disturbances effect. Linear Matrix Inequality (LMI) was solved to calculate the controller and the observer gains. At last, simulations have been done to illustrate the Fault-Tolerant Tracking Control performance of the developed control strategy. [ABSTRACT FROM AUTHOR]

The problem of diagnosing inter-turn short circuits (ITSC) in the stator winding of an induction motor (IM) under various load conditions is considered. The enhancement of the reliability of the operations of IMs may be achieved by the timely detection of faults. Improvement of the methodology for diagnosis of IMs is required for this. An online methodology for diagnosing an inter-turn short circuit (ITSC} in the IM winding is presented. The proposed approach is based on the formation of the envelope of the stator current with the aid of the Hilbert transform by means of multiplying this current by the Tukey window, in order to reduce the effect of transient distortions. Then the discrete wavelet transform (DWT) is performed, to facilitate ITSC fault diagnosis. Finally, based on statistical analysis using the Weibull distribution, the fault thresholds are determined. Hence, by monitoring the estimation of the mean value, it is possible to detect an incipient fault condition of the induction motor. [ABSTRACT FROM AUTHOR]

It is well known that the most common reason for electrical machines breakdown is the stator windings’ fault occurrence. Indeed, this type of fault represents almost 40% of faults occurring in induction machines. One of the major causes of stator defects is the occurrence of interturn short-circuit (ITSC) faults that have critical and dangerous effects on the motor itself, as well as on the related electrical equipment. Therefore, early detection and a precise severity estimation of the occurrence of ITSC faults for all working conditions can prevent failure breakdowns and increase reliability and safety of industrial facilities. In this context, this article proposes an efficient online diagnostics method based on calculating and monitoring a pertinent severity factor defined as the ratio between the zero and positive voltage symmetrical components. The online implementation of this method is performed on a LabVIEW environment, using the short-time least square Prony's (STLSP) method. It does not need any estimation of motor parameters and it requires only voltage sensors. Several tests under healthy and faulty conditions are carried out on a three-phase 3-kW induction motor. The obtained results demonstrate the effectiveness of the proposed method for diagnosing the occurrence of ITSC faults with high reliability, fastness, and high precision, even under load variations or unbalanced supply voltage. [ABSTRACT FROM AUTHOR]

Digital twins, a product of new-generation information technology development, allows the physical world to be transformed into a virtual digital space and provide technical support for creating a Metaverse. A key factor in the success of Industry 4.0, the fourth industrial revolution, is the integration of cyber–physical systems into machinery to enable connectivity. The digital twin is a promising solution for addressing the challenges of digitally implementing models and smart manufacturing, as it has been successfully applied for many different infrastructures. Using a digital twin for future electric drive applications can help analyze the interaction and effects between the fast-switching inverter and the electric machine, as well as the system's overall behavior. In this respect, this paper proposes using an Extended Kalman Filter (EKF) digital twin model to accurately estimate the states of a speed sensorless rotor field-oriented controlled induction motor (IM) drive. The accuracy of the state estimation using the EKF depends heavily on the input voltages, which are typically supplied by the inverter. In contrast to previous research that used a low-precision ideal inverter model, this study employs a high-performance EKF observer based on a practical model of the inverter that takes into account the dead-time effects and voltage drops of switching devices. To demonstrate the effectiveness of the EKF digital twinning on the IM drive system, simulations were run using the MATLAB/Simulink software (R2022a), and results are compared with a set of actual data coming from a 4 kW three-phase IM as a physical entity. [ABSTRACT FROM AUTHOR]

Induction motor (IM) drives have tremendous applications as high-performance drives in things such as mine winders, machine tools, electric vehicles, and elevators. Usually, IM drives controlled by direct torque control are preferred for these applications due to their fast torque control and simplicity compared with IM drives with field-oriented control. Proportional–integral–derivative (PID) controllers are commonly used to control IM drives using DTC. Though these controllers are simple and provide excellent response for linear systems with constant set points, they perform poorly with variable set points and IM motor parameter uncertainties. Hence, many control techniques and optimization algorithms have been applied to improve IM drive performance. This paper proposes an IM drive controlled using direct torque control principles, but with the power converter operation optimized to give fast torque performance. The IM drive speed response is improved using an optimized fuzzy PID (FPID). The FPID optimization is accomplished by the ant colony optimization (ACO) algorithm. All components of the IM drive with the optimized control system were simulated using the MATLAB/Simulink platform. The responses of the introduced drive using three different controllers—conventional PID, FPID, and optimized FPID—were compared. The simulation results indicate that the optimized FPID controller provided the best performance in terms of speed and torque. Additionally, the performance of the IM with the proposed optimized FPID under parameter uncertainties was studied. The simulation results indicated the robustness of the optimized FPID controller against parameter uncertainties. [ABSTRACT FROM AUTHOR]

Model predictive flux control (MPFC) is an alternative control solution to the classic model predictive torque control (MPTC) for driving induction motors (IMs) without the complexity of tuning the weighting factors. However, when applied in motor drives fed by a two-level converter, it results in higher flux and torque ripples. To improve its performance, this article proposes a virtual three-level MPFC (V3-MPFC) method. The virtual vector method increases the total number of voltage vectors crucial for improving the closed-loop performances of the model predictive control. To reduce the computational burden, direct torque control and novel deadbeat (DB) control strategies are proposed. Compared with existing methods, the proposed DB-based method reduces V3-MPFC to a suboptimization problem and still ensures that the suboptimal solution is equivalent to the global optimal solution provided by V3-MPFC. In addition, the redundant states are exploited to lower the switching frequency (SF) without extending the cost function. The simulation and experiment results show that, compared with existing methods, the proposed strategy effectively reduces the flux and torque ripples, and requires a lower SF and execution time. [ABSTRACT FROM AUTHOR]

Owing to the phase delay and resonance oscillations introduced by the LC filter connected in-between the voltage-source inverter (VSI) and the induction motor (IM), the “L” and “C” design methodology is critical. Also, the closed-loop control and the speed sensorless operation of such drives are complex without stator voltage sensors. This article addresses these issues by proposing a simple filter inductor ($L_{f}$) selection criterion for an LC filter equipped IM drive, which allows retaining the designed dc-bus capacitor, heat-sink, and power devices of VSI upon LC filter insertion in-between the VSI and IM. Furthermore, an existing filter capacitor selection criterion is improved adhering to the constraint on voltage drop ($V_{f}$) across $L_{f}$. In addition, this article also examines the existing active damping (AD) techniques to perform the speed sensorless operation on the IM + LC (IMLC) filter drive without stator voltage sensors and improves one of them to achieve the same. Summarily, through the filter selection criteria and improved active damping technique, this article proposes to retrofit the LC filter into the IM drive and performs speed and voltage-sensorless operation. The simulation and experimental results obtained from a 5-hp IM drive are presented to validate the proposed work. [ABSTRACT FROM AUTHOR]

In the motor drive system of electric vehicles, there are some nonlinear factors, such as the deadtime and the conduction voltage drop of switching devices, which will generate low-order harmonics of the stator current and the torque ripple. The frequency of the harmonic may coincide with the natural frequency of the motor, so resonance may occur on the motor drive system. To reduce the noise caused by motor resonance, the characteristics of harmonic distortion caused by the deadtime, and the conduction voltage drop of the switching device, are analyzed firstly. Then, a motor vector control strategy with specific low order is proposed. The sixth-order harmonic resonance controller in d-q axis is introduced into the control loop, and the parameter designing principle of the controller is also presented. Without affecting the control performance of the current loop, the sixth-order harmonic of the stator current near the natural frequency can be significantly suppressed. Finally, the simulation and the experiment are carried out to certify the correctness and effectiveness of the proposed harmonic suppression method. [ABSTRACT FROM AUTHOR]

• Efficiency estimation of low voltage three-Phase induction motors via a non-intrusive technique has been proposed. • The proposed technique is developed based on the simulation of 425 induction motors (IMs) in MATLAB software. • The suggested technique only needs line voltages, line currents, and IM nameplate information. • Unlike previous IM efficiency estimation methods, the proposed method is non-intrusive. This paper introduces a non-intrusive technique based on the air–gap torque (AGT) method to estimate the efficiency of induction motors (IMs). The technique uses a 3rd-degree equation to calculate the sum of windage and friction losses (FWL) and rotor stray load losses (SLLr), considering the number of IM poles. IM speed is estimated using motor current signature analysis, and a new procedure to estimate stator resistance is presented. Efficiency is then determined by applying the estimated rotor speed, stator resistance, and the sum of FWL and SLLr in the AGT equations. This method requires only nameplate information, IM line voltages, and currents. Simulations and experimental tests for balanced, unbalanced, and harmonic feeding modes show the proposed technique's estimated efficiency values are very close to measured values, unlike the AGT method. This demonstrates the proposed technique's high accuracy, making it suitable for non-intrusive efficiency estimation of in-service IMs in industrial programs. [ABSTRACT FROM AUTHOR]

This study developed a predictive direct torque control (PDTC) application-specific integrated circuit (ASIC) with a fuzzy proportional–integral–derivative (PID) controller and a new round-off calculation circuit for improving the ripple response of a hysteresis controller when sampling and calculating delay times in an induction motor drive. The proposed PDTC ASIC not only calculates the stator’s magnetic flux and torque by detecting three-phase currents, three-phase voltages, and rotor speed but also eliminates large ripples in the torque and flux by using the fuzzy PID controller. Furthermore, the proposed round-off algorithm reduces the calculation error of the composite flux. A fuzzy voltage vector switching table is proposed not only to speed up the calculating speed but also to resolve the instability generated by its large torque and flux ripples. The Verilog hardware description language was used to implement the hardware architecture, and the aforementioned ASIC was fabricated using the 0.18- $\mu \text{m}$ 1P6M CMOS process of the TSMC by employing the cell-based design method. The predictive calculations, fuzzy PID controller, fuzzy voltage vector switching table, and round-off calculation algorithm improved not only the ripple issue faced in traditional direct torque control but also the control stability and robustness. The measurement results indicate that the proposed PDTC ASIC has an operating frequency, a sampling rate, and a dead time of 50 MHz, 100 kS/s, and 100 ns, respectively, at a supply voltage of 1.8 V. The power consumption and chip area of this ASIC are 1.0027 mW and 1.169 $\times $ 1.168 mm2, respectively. The main advantages of the proposed PDTC ASIC are its low power consumption, small chip area, robustness, and convenience.

The most often used motor in commercial drives is the induction motor. While the induction motor is operating, electrical, thermal, mechanical, magnetic, and environmental stresses can result in defects. Therefore, many researchers who are involved in condition monitoring have been interested in the development of reliable and efficient fault diagnostic technologies. This paper's goal is to provide an overview of available fault detection methods for the broken rotor bar problem, one of several defects associated to induction motors. Despite the fact that it is less common than bearing or insulator failure, this fault may cause electrical machines to fail catastrophically. It can be quite harmful, especially in large motors, and it can develop as a result of manufacturing faults, repeated starting of the machine, mechanical stress, and thermal stress. Hence, a review on rotor defect diagnosis was conducted. In order to confirm rotor bar fracture, this research provides probable defect signatures that can be extracted from the current signal. Each defect signature is reported according to (a) loading level, (b) the number of BRBs, (c) validation, and (d) methodologies. [ABSTRACT FROM AUTHOR]

This paper analyzes the digital signal processing techniques and estimates induction motor (IM) rotational speed operating in stationary or non-stationary conditions. Rotor slot harmonics present in the stator current waveform are used to estimate the induction motor speed with a given or identified rotor slot numbers. This paper's contribution is the following: First, zoom improved short-time Chirp-Z transform is used to find supply frequency and the rotor slot harmonic frequency to improve the estimation accuracy without increasing computing complexity. Second, a technique is described that can be used to determine whether or not a motor can generate principal slot harmonics (PSH). Finally, an algorithm is designed to figure out the perfect window length and estimate the motors' speed. This proposed technique was investigated when the motor was fed by an inverter-fed supply driving a variable load and operating in non-stationary conditions. Experimental test results on 5.5 kW and 22 kW induction motors have confirmed the correctness of this method. [ABSTRACT FROM AUTHOR]

This article introduces a family of carrier-based pulse width modulation (PWM) schemes for three-level (3 L) inverter fed motor drive for low-speed operation. The proposed PWM in dual-inverter topology (DIT) simultaneously clamps two phases of each inverter throughout the fundamental cycle, which reduces the switching transition in the pole voltage and common-mode voltage (CMV). Four PWM variants in the family (i.e., PWM-1–PWM-4) are discussed and compared with conventional discontinuous PWM schemes. A mapping of the gating pulse is derived to extend the proposed PWM to a classical 3 L inverter fed star-connected motor drive. The gating pulses are generated using triangular carrier comparison with synchronous sampling. The steady-state and dynamic performances of PWM are validated both in DIT fed open-end winding induction motor (IM) drive and neutral point clamped (NPC) inverter fed star-connected IM drive. It is observed that the proposed PWM gives inherent capacitor voltage balance in the NPC topology. PWM-1 has a higher linear modulation range than conventional zero clamp PWM and leads to reduced CMV in the NPC topology. PWM-2 and PWM-3 give reduced CMV in DIT. PWM-4 has fault tolerance to single-phase open-switch and short-switch failure in DIT. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this article, in order to improve the power quality and decrease the consumed power of an induction motor (IM), which is supplied by an alternate battery-powered system, an algorithm that can be used to save its energy consumption has been proposed. The control mechanism is used to reduce the wasted energy caused by IMs start-up current based on bounding its optimal starting voltage. The proposed algorithm includes two parts: First, use branch-and-bound theory to derive the control rule of the IMs start voltage and give corresponding offline calculation procedure framework. Second, according to the control rule, adjust online voltage of the zinc–bromine flow battery, which is used to feed the IM. Due to the proposed approach, the minimum start-up voltage of the battery-powered system can be predicted and by which one the IMs surge current has been suppressed online. Moreover, the relationship of the output voltage of the battery and inverter supply to the load current has been derived by modeling the battery-powered system. The experiments demonstrate that compared with before optimization, the amount of energy consumption of the IM supplied by zinc–bromine flow battery decreases by 8.5% and corresponding indicator parameters of the power quality can reach the standard IEC TS62749-2015. [ABSTRACT FROM AUTHOR]

An adaptive predictive current controller (APCC) for a direct field-oriented controlled (DFOC) three-phase asynchronous motor (AM) drive is implemented in this paper. Firstly, DFOC is implemented with conventional hysteresis current controller (HCC) and performance of HCC is being compared to that of the APCC. Stator current of induction motor (IM) is controlled using APCC according to the reference stator current produced by DFOC. An objective function defined in APCC is utilized to reduce the stator current error. The switching vector, which yields the least value of the objective function is opted and applied to the VSI. This controller does not need any linear regulators and modulation stage. Moreover, a stator resistance observer is also implemented to adapt to the change in the stator resistance. The dynamic performance of the machine under load torque, speed variations, and speed reversal are compared and analysed in MATLAB/Simulink and laboratory. The validation simulation results are made experimental results with dS1104. The fast dynamics response with respect to speed and torque, effective decoupling of flux and torque, robust operation of drive, and fast speed tracking are the benefits of the proposed APCC over classical HCC. [ABSTRACT FROM AUTHOR]

This article proposes a novel nine-level multilevel inverter topology with an instantaneous voltage balancing scheme of stacked dc-link capacitors for an induction motor (IM) drive application. Three neutral points (NPs, terminal joints of four series-connected capacitors) across a single dc-link are balanced instantaneously (within a sampling interval) by ensuring zero current at the NPs. The proper selection of pole voltage from the redundancies provides zero current at any NP during the pulsewidth modulation operation under a steady-state and transient operation. A five-level stacked inverter and three cascaded hybrid-bridge (CHB) inverter cells are used in each phase. Along with the balancing of dc-link capacitors, CHB capacitors’ voltage balancing is also achieved using the pole voltage redundancies at all modulation indexes for all power factor and load. It is also possible to increase more number of levels using more low-voltage switches, and a generalized form of the topology is presented. The concept is validated using a laboratory-developed nine-level inverter with a three-phase IM load, operated under “V/f” control. The detailed experimental results for the steady and transient condition, simulation studies for switching loss, and harmonic content in the phase voltage are also presented. [ABSTRACT FROM AUTHOR]

This article proposes an improved fault diagnosis strategy to enhance the diagnosis accuracy for the induction motor under the slight fault situation. The additional even and triple harmonics, caused by the faulty asymmetric structure, are taken into account. As a result, the stator current faulty characteristic frequency components, caused by faults from the stator side, the rotor side and the air-gap side, are enlarged. The Hilbert transform and the support vector machine (SVM) multiclassification method are applied to improve the sensitivity of fault identification. To increase the diagnosis accuracy and speediness in different applications, the grid search method, the genetic algorithm and the particle swarm algorithm are employed for the parameter optimization of the SVM classification prediction model. Finally, compared with the traditional strategy, the diagnosis accuracy can be increased by 6%–10% based on the proposed strategy. Comprehensive simulation and experimental results have fully verified the proposed diagnosis method in this article. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to illustrate the dynamical response of speed using the design of a Fuzzy Logic Controller (FLC) to regulate the motor speed, while the load changes. Induction motor power control has become popular in recent years in high-performance drive systems. It is due to its amazing qualities, such as high-performance, a high energy factor, and significant toughness. The overall performance of the controller is estimated using MATLAB or Simulink software and a common Proportional Integral (PI) management technique. This work discusses the design and construction of a voltage supply inverter-based Space Vector Pulse Width Modulation (SVPWM) system for regulating the speed of an induction motor. This observation also incorporates a fuzzy controller into the SVPWM to maintain the motor speed constant even when the load varies. FLC is used to alter the pulse width of the Pulse Width Modulation (PWM) converter, which controls the motor pace. This paper describes the application of a rule-based Mamdani type FLC to a closed loop induction motor model. [ABSTRACT FROM AUTHOR]

In this article, a new design of the state observer is proposed to reduce the unstable low-speed region of the adaptive full-order observer (AFO) based speed sensorless speed control of induction motors (IM). The proposed state observer is designed in z-domain rather than in s-domain following the pole-placement approach. The convergence rate of the proposed observer can be made faster than that of the IM poles without extra oscillation effects and the unstable low-speed region of AFO can be reduced to the zero-synchronous-frequency (ZSF) line. Also, a modified adaptation law of the AFO is derived to estimate the rotor speed. Based on the modified AFO, a continuous control set model predictive control (CCS-MPC) is designed for the inner-loop torque control. The cost function of the CCS-MPC is made of the predicted tracking errors on the state and control input. Finally, the dual-loop speed sensorless speed control using the modified AFO and CCS-MPC is presented in simulations and experiments. [ABSTRACT FROM AUTHOR]

To control the induction motor stably under the condition of uncertain disturbances, an induction motor speed control method based on robust sliding mode control and field oriented control was proposed based on switching gain adaptive technology. By introducing the switch adaptive gain and integrator interpolation into the speed and flux sliding mode controller, the same robustness and dynamic performance as the traditional sliding mode control algorithm were guaranteed, and the stator voltage chattering phenomenon was effectively suppressed. Moreover, the proposed control method was insensitive to load torque variation and electrical parameter uncertainty. Finally, the proposed control method was verified by simulation and physical experiments. The results show that the proposed control method can track the reference signal accurately and quickly, and has good robustness. [ABSTRACT FROM AUTHOR]

This article proposes a robust adaptive supertwisting sliding-mode controller (STSMC) for high-precision IM drive. First, the STSMC is developed for controlling and stabilizing the IM. However, the control performance may be influenced due to exterior disorders along with parameter variations since the IM model is not accurately known during operation. Therefore, it is essential to estimate the lumped disturbance to strength the robustness of the STSMC using system model-based disturbance estimator. Second, to optimize the control performance, a robust adaptive neural-network tracking controller is developed to evade the constraints on knowing the disorders and uncertainties upper bounds. The RANTC combines an STSMC and a recurrent radial basis function network (RRBFN) estimators. The RRBFNs are employed to approximate the IM dynamics along with estimating the optimum super-twisting control algorithms online. The RRBFN training is developed via adaptive particle swarm optimization (APSO) algorithm to attain enhanced performance in less learning iterations, which is the critical issue in real-time applications. Third, to imitate the STSMC algorithms for preserving the robust control characteristics without the necessity of the IM parameters, a direct adaptive intelligent controller (DAIC) based on Takagi–Sugeno–Kang-type recurrent Petri fuzzy-neural-network is developed. Furthermore, the online adaptive laws are derived according to Lyapunov theory, so that the system stability can be assured. The validity of control schemes is verified by simulation and experimentation. The simulation and experimental results confirm the superiority of the STSMC-SMDE, RANTC, and DAIC schemes compared with STSMC irrespective of exterior disorders along with indefinite model uncertainties. [ABSTRACT FROM AUTHOR]

This article presents the proportional–integral (PI) controller design, its limitation, and remedies for $dq$ -axis currents in a vector-controlled voltage-source-inverter-fed induction motor (IM) drive with an inverter output $LC$ filter. The idea of designing PI controllers by incorporating the $LC$ filter dynamics into the IM dynamics is applied for the vector-controlled IM + $LC$ filter drive. This article shows that the PI controller, a first-order controller, has limitations of stability margins and performance criteria for an IM + $LC$ filter system. These limitations in the PI controller are demonstrated by deriving the complete range of stabilizing PI gains ($K_{p}$ and $K_{i}$) for the IM + $LC$ filter system and segregating them to satisfy the desired frequency-domain specifications. As a remedy to the limitations, this article proposes to use a second-order controller instead of a PI controller to provide better stability margins, attenuation at the resonance frequency, and more robustness. The controller design and resulting closed-loop stability are thoroughly analyzed, and the experimental results are presented to validate the same. [ABSTRACT FROM AUTHOR]

The overmodulation-based nonlinear voltage extension could increase the maximum output torque of the induction motor (IM) in the field-weakening (FW) region. Since the voltage distortion increases with the deepening of overmodulation degree, the extreme nonlinear voltage extension (six-step voltage) is only worthwhile in maximum torque demand conditions. However, the conventional overmodulation-FW scheme always adopts the six-step voltage regardless of torque demand, leading to severe torque ripple. To solve this problem, the minimum-nonlinear-voltage (MNV) method is proposed to satisfy the torque demand with minimum overmodulation-voltage nonlinearity. The difference between the limiting and the feedback values of the torque current is used for suppressing the nonlinear voltage extension during a nonmaximum torque demand state. The quantitative relation between the torque ripple and torque demand of the MNV method is calculated and compared with that of the conventional six-step-FW method. Analysis shows that the MNV method can eliminate the torque ripples of low and medium torque demand conditions completely and partially, respectively. The effectiveness of the proposed method is verified experimentally on a 3.7 kW IM platform. [ABSTRACT FROM AUTHOR]

The performance of a sensor-based rotor flux-oriented vector control induction machine drive is highly influenced by the estimated value of the rotor time constant/rotor resistance which varies continuously with temperature when it is driven with the variable loads. Therefore, to achieve accurate torque control, online tunning of the rotor time constant is necessary. This article proposes a novel and simple adaption technique to estimate the rotor time constant. In this proposed method, the reference model of the rotor flux vector is derived using the voltage model of the induction machine, which is independent of the rotor time constant. The current controller uses the model of the rotor flux vector that is derived using the current model of the induction machine. This current model is dependent on the rotor time constant. The error between the rotor flux vectors derived using the current model and the voltage model is minimized using the least-squares method. In this process, the rotor time constant is always tuned to its actual value. The article also presents a simple approach to estimate the parameters of induction machine like the stator resistance, the net leakage inductance, and the initial value of the rotor time constant in an offline mode at a standstill condition. To validate the proposed algorithm, two experimental prototypes are developed for two different power ratings of 3.7 and 67 kW. Experimental results from these prototypes confirm the effectiveness, reliability, and stability of the proposed algorithm both in the motoring and regenerative modes of operation. This method of the adaptation of the rotor time constant is simple and, therefore, useful for practicing engineers. [ABSTRACT FROM AUTHOR]