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In industry, three-phase induction motors (IMs) are the most used motors. IMs' high starting supply current and large accelerating torque make their starting process a potential source of unnecessary energy waste, especially when it is repeated. To overcome the starting problems of an IM, an intelligent soft-starter controller based on an artificial neural network (ANN) is proposed. The controller contains two soft starting control schemes namely, current and speed controls. That allows one to select the soft starting control scheme based on the load requirements and/or supply utility capability. Current and speed controls are to keep the motor's starting current and accelerating torque constant at a specified level, respectively. That is achieved by selecting the appropriate firing angles for the thyristors in the soft starter. The online determination of the thyristor firing angles is resolved through the application of the ANN approach. First, the ANN models for two control techniques are developed using a MATLAB Neural Network Toolbox for training. Based on the current-speed and torque-speed characteristics, two ANN models are trained for a range of thyristor firing angles. Secondly, the ANN models of two control schemes are implemented using MatLab/Simulink for a 3kW three-phase IM. A variety of simulation tests prove that a validation on control technique's effectiveness under various load conditions (noload, pump, constant, and linear loads) and reference values exists. The least inrush current and smooth acceleration are obtained with two control schemes. [ABSTRACT FROM AUTHOR]

Introduction. A new control strategy based on the combination of optimal model predictive control (OMPC) with fractional iterative learning control (F-ILC) for speed regulation of an induction motor (IM) for electric vehicles (EVs) application is presented. OMPC uses predictive models to optimize speed control actions by considering the dynamic behavior of the IM, when integrated with the FILC, the system learns and refines the speed control iteratively based on previous iterations, adapting to the specific characteristics of the IM and improving performance over time. The synergy between OMPC and F-ILC named F-ILC-OMPC enhances the precision and adaptability of speed control for IMs in EVs application, and optimizes the energy efficiency and responsiveness under varying driving conditions. The novelty lies in the conjunction of the OMPC with the ILC-based on the fractional calculus to regulate the speed of IMs, which is original. Purpose. The new control strategy provides increased performance, robustness and adaptability to changing operational conditions. Methods. The mathematical development of a control law that mitigates the disturbance and achieves accurate and efficient speed regulation. The effectiveness of the suggested control strategy was assessed via simulations in MATLAB conducted on an IM system. Results. The results clearly show the benefits of the F-ILC-OMPC methodology in attaining accurate speed control, minimizing steady-state error and enhanced disturbance rejection. Practical value. The main perspective lies in the development of a speed control strategy for IMs for EVs and the establishment of reliable and efficient electrical systems using ILC-OMPC control. This research has the prospect of a subsequent implementation of these results in experimental prototypes. References 24, tables 2, figures 9. [ABSTRACT FROM AUTHOR]

Introduction. A new control strategy based on the combination of optimal model predictive control (OMPC) with fractional iterative learning control (F-ILC) for speed regulation of an induction motor (IM) for electric vehicles (EVs) application is presented. OMPC uses predictive models to optimize speed control actions by considering the dynamic behavior of the IM, when integrated with the F-ILC, the system learns and refines the speed control iteratively based on previous iterations, adapting to the specific characteristics of the IM and improving performance over time. The synergy between OMPC and F-ILC named F-ILC-OMPC enhances the precision and adaptability of speed control for IMs in EVs application, and optimizes the energy efficiency and responsiveness under varying driving conditions. The novelty lies in the conjunction of the OMPC with the ILC-based on the fractional calculus to regulate the speed of IMs, which is original. Purpose. The new control strategy provides increased performance, robustness and adaptability to changing operational conditions. Methods. The mathematical development of a control law that mitigates the disturbance and achieves accurate and efficient speed regulation. The effectiveness of the suggested control strategy was assessed via simulations in MATLAB conducted on an IM system. Results. The results clearly show the benefits of the F-ILC-OMPC methodology in attaining accurate speed control, minimizing steady-state error and enhanced disturbance rejection. Practical value. The main perspective lies in the development of a speed control strategy for IMs for EVs and the establishment of reliable and efficient electrical systems using ILC-OMPC control. This research has the prospect of a subsequent implementation of these results in experimental prototypes. References 24, tables 2, figures 9.

An induction motor's speed can be managed in a variety of ways using a Variable Frequency Drive (VFD). In this study, the speed control of an induction motor will be controlled by applying Indirect Field Oriented Control (IFOC) combined with Linear Quadratic Gaussian (LQG). Conventional LQG control is a linear controller; therefore, if the system's dynamic is high and over the linear boundary, the LQG performance will not be optimal. Therefore, Adaptive LQG (ALQG) is proposed. Fuzzy logic is used as an adaptive algorithm with low complexity and ease of implementation. The significance of this study lies in its endeavor to tackle the challenges associated with nonlinearities and high dynamics in induction motor control. The average performance of speed variation and load variation tests proves that ALQG is superior in terms of settling time and undershooting than PID and LQG. PID has the highest overshoot with the smallest Integral Absolute Error (IAE). In comparison, ALQG is superior to conventional LQG in terms of IAE with 3.59% lower. [ABSTRACT FROM AUTHOR]

This paper introduces a streamlined space vector algorithm designed to regulate a three-level inverter-powered induction motor using direct torque control (DTC). Unlike the traditional two-level inverter, this drive utilizes a three-level inverter to achieve a reduction in torque ripple. The controller has been specifically designed to capitalize on the expanded range of inverter states that are made possible by utilizing a three-level inverter. The algorithm proposed in this study is flexible and can be applied to various rail clamping pulse width modulation (RCPWM) sequences. The RCPWM-3 demonstrates superior performance, which enhances the drive’s performance at near rated speeds. The findings indicate a reduction in harmonic distortion within the stator currents, alongside a consistent switching frequency of the inverter through the implementation of the suggested control system.

Three-phase induction motors are the main drivers of the industrial world because of their low price and good reliability. However, this type of motor does not have built-in speed control. These problems can be overcome by utilizing the Variable Frequency Drive (VFD) inverter. This research investigates the induction motor's characteristics in every load condition and combines a VFD inverter with an external speed controller based on Arduino. The motor is mounted on a Prony brake testbed frame to measure the motor's torque and mechanical power. The test results show the highest torque value obtained is 0.57 Nm, and the highest output power value is 0.042 kW. The motor cannot maintain the setpoint speed after loading in the open-loop control system. Meanwhile, the closed-loop control system has been successfully implemented, and the motor can return the speed to the setpoint value after loading, with an average settling time of 14.67 seconds. [ABSTRACT FROM AUTHOR]

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Induction motors tend to have better efficiency on rated conditions, but at partial load conditions, when these motors operate on rated flux, they exhibit lower efficiency. In such conditions, when these motors operate for a long duration, a lot of electricity gets consumed by the motors, due to which the computational cost as well as the total running cost of industrial plant increases. Squirrel-cage induction motors are widely used in industries due to their low cost, robustness, easy maintenance, and good power/mass relation all through their life cycle. A significant amount of electrical energy is consumed due to the large count of operational units worldwide; hence, even an enhancement in minute efficiency can direct considerable contributions within revenue saving, global electricity consumption, and other environmental facts. In order to improve the efficiency of induction motors, this research paper presents a novel contribution to maximizing the efficiency of induction motors. As such, a model of induction motor drive is taken, in which the proportional integral (PI) controller is tuned. The optimal tuning of gains of a PI controller such as proportional gain and integral gain is conducted. The tuning procedure in the controller is performed in such a condition that the efficiency of the induction motor should be maximum. Moreover, the optimization concept relies on the development of a new hybrid algorithm, the so-called Scrounger Strikes Levy-based dragonfly algorithm (SL-DA), that hybridizes the concept of dragonfly algorithm (DA) and group search optimization (GSO). The proposed algorithm is compared with particle swarm optimization (PSO) for verification. The analysis of efficiency, speed, torque, energy savings, and output power is validated, which confirms the superior performance of the suggested method over the comparative algorithms employed. [ABSTRACT FROM AUTHOR]

This paper presents the design, simulation, and analysis of the speed control of an induction motor powered by a voltage inverter with a pulse-wide modulation method. The derived model addresses issues related to the regulation of motor speed at various supply frequencies. The control strategy of the voltage inverter is based on the scalar control with a constant V/f ratio, which is important for automated control, controlled start-up, acceleration and stop, and constant flux operation of the motor. The Powersim software is used for the purposes of deriving the simulation model in this paper. The analysis of the output results compares the different speeds of operation, below and above the nominal speed of the motor. They are also compared with the theoretical calculations required for the simulation model. [ABSTRACT FROM AUTHOR]

This paper presents the application of a newly developed 21-level hybrid multilevel inverter. A high frequency modulation technique known as sinusoidal pulse width modulation (SPWM) is applied to the hybrid inverter. This modulation methodology operates the switching sequences of the multilevel inverter to produce the desired 21-level output voltage. To validate the proper application of this inverter, it is further utilized to maintain the speed of a single phase induction motor. The velocity control of the motor is established on the principle of V/f control technique. The speed control strategy along with the compatibility of the SPWM modulation technique were verified by means of simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper proposes an offset-free speed control method for induction motors using a model predictive control and disturbance observer. The proposed method has cascade control loops i.e. inner-loop model predictive torque control and outer-loop robust speed control. The outer-loop robust speed controller is composed of a stabilizing MPC and a discrete-time disturbance observer. The disturbance observer estimates the effects of the parameter uncertainties and the load torque to yield an offset free speed tracking, while taking the torque limit of the motor into account. This speed controller generates the reference torque for the inner-loop torque controller. A loss-minimizing continuous control set model predictive torque controller(CCS-MPTC) considering the current and voltage constraints of the motor is used as the inner-loop torque controller. Experimental results show a significant performance improvement when the torque constraints are considered in the DOB design. [ABSTRACT FROM AUTHOR]

In this paper, an enhanced Integral Sliding Mode Control (ISMC) for mechanical speed of an Induction Motor (IM) is presented and experimentally validated. The design of the proposed controller has been done in the d-q synchronous reference frame and indirect Field Oriented Control (FOC). Global asymptotic speed tracking in the presence of model uncertainties and load torque variations has been guaranteed by using an enhanced ISMC surface. Moreover, this controller provides a faster speed convergence rate compared to the conventional ISMC and the Proportional Integral methods, and it eliminates the steady-state error. Furthermore, the chattering phenomenon is reduced by using a switching sigmoid function. The stability of the proposed controller under parameter uncertainties and load disturbances has been provided by using the Lyapunov stability theory. Finally, the performance of this control method is verified through numerical simulations and experimental tests, getting fast dynamics and good robustness for IM drives.

This paper presents the characteristic behavior of direct vector control of two induction motors with sensorless speed feedback having the same rating parameters, paralleled combination, and supplied from a single current-controlled pulse-width-modulated voltage-source inverter drive. Natural observer design technique is known for its simple construction, which estimates the speed and rotor fluxes. Load torque is estimated by load torque adaptation and the average rotor flux was maintained constant by rotor flux feedback control. The technique’s convergence rate is very fast and is robust to noise and parameter uncertainty. The gain matrix is absent in the natural observer. The rotor speed is estimated from the load torque, stator current, and rotor flux. Under symmetrical load conditions, the difference in speed between two induction motors is reduced by considering the motor parameters as average and difference. Rotor flux is maintained constant by the rotor flux control scheme with feedback, and the estimation of rotor angle is carried out by the direct vector control technique. Both balanced and unbalanced load conditions are investigated for the proposed AC motor drive system. Experimental results presented in this paper show good agreement with the theoretical formulations.

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 paper presents a new approach to induction motor (IM) speed controller design with indirect field-oriented control structure. The designed discrete-time variable structure (VS) speed controller uses elements of reduced-order and full-order (integral) sliding mode (SM) control, and acts as a nonlinear equivalent of conventional PI control. The controlled plant is approximated by a first-order dynamical model. Therefore, the proposed approach leads to an output feedback-based SM control (SMC) system. To improve its disturbances rejection and tracking capability, the controller is supplied with a first-order disturbance compensator based on the switching function measurement. The proposed VS control structure provides a high-performance chattering-free discrete-time SMC system. Numerous experiments have been carried out to test the proposed control method and to compare its performance with the conventional PI control approach. The experimental results demonstrate high tracking accuracy and robustness of the proposed system. [ABSTRACT FROM AUTHOR]

This paper proposes a servo system designed for speed control of AC induction motors using polynomial differential operator to track more complicated types of reference speed and disturbance such as step, ramp, parabola, etc. To do this task, the followings are done. First, modeling for an induction motor is introduced and is linearized at equilibrium points using Taylor's series. Second, observer is designed to estimate flux, and an extended system incorporating the internal model principle to construct the servo system is derived using polynomial differential operator in case that the types of reference inputs are polynomials. Third, a state feedback control law for the servo system to track the given reference input is designed. To implement the proposed controller and servo system, a control system is constructed for speed control of 1.5 Kw AC induction motor. The simulation and experimental results are conducted to verify the effectiveness and the applicability of the proposed controller compared to the conventional PID controller and MRAC controller for more complicated higher order types of the references and disturbance such as step, ramp, parabola, etc. [ABSTRACT FROM AUTHOR]

This paper proposes the speed control of induction motor fed by wind turbine using Imperialist Competitive Algorithm (ICA). The wind turbine plays as a prime mover to a connected DC generator. Pulse-width modulation is used to get three-phase AC voltage from the output of DC generator. The proposed design problem of speed controller is established as an optimization problem. ICA is adopted to search for optimal controller parameters by minimizing the time domain objective function. The behavior of the proposed ICA has been estimated with the behavior of the conventional Ziegler-Nichols and genetic algorithm in order to prove the superiority of the proposed ICA in tuning PI controller. Also, the behavior of the proposed controller has been tested over a wide range of operating conditions. Simulation results confirm on the better behavior of the optimized PI controller based on ICA compared with other algorithms. [ABSTRACT FROM AUTHOR]

This paper reports an automated procedure for the design of an optimal fuzzy logic controller to be used as an induction motor speed controller. The procedure consists of selection of a suitable well known fuzzy logic controller and tuning via particle swarm optimization optimal for the selected criteria. In this way the time required for tuning of the controller is significantly reduced in comparison with trial and error methods. As a benchmark a proportional-integral (PI) controller is used. The PI controller is tuned via the symmetrical optimum procedure, the standard procedure for tuning a speed controller of an induction motor. Simulation results are obtained via a mathematical model developed in Matlab/Simulink. Experimental verification is carried out with a laboratory model based on the DS1104 digital control card. To minimize iron losses and to provide better motor performance for low loads, flux is reduced from nominal and speed is kept below nominal. Results are presented in tables and graphics. The optimal fuzzy logic controller provides a slight practical advantage.

This paper proposes the speed control of induction motor (IM) fed by wind turbine using imperialist competitive algorithm (ICA). The wind turbine plays as a prime mover to a connected direct current (DC) generator. Pulse width modulation (PWM) is used to get three-phase alternating current (AC) voltage from the output of DC generator. The proposed design problem of speed controller is established as an optimization problem. ICA is adopted to search for optimal controller parameters by minimizing the time domain objective function. The behavior of the proposed ICA has been estimated with the behavior of the conventional Ziegler-Nichols (ZN) and genetic algorithm (GA) to prove the superiority of the proposed ICA in tuning proportional plus integral (PI) controller. Also, the behavior of the proposed controller has been tested over a wide range of operating conditions. Simulation results confirm the better behavior of the optimized PI controller based on ICA compared with other algorithms. [ABSTRACT FROM AUTHOR]

Induction motors (IMs) are widely used in many industrial applications due to their robustness, low cost, simplicity and relative good efficiency. One of the major considerations for IMs is their speed control. PI (proportional-integrator) controllers are usually used as speed controller. Adjusting the gain of PI controller is time-consuming which needs thorough considerations. Hence, fuzzy controllers are proposed to overcome such problems. In this paper, firstly drive of a three-phase induction motor is designed based on PI controller and then fuzzy logic controller is implemented. This paper presents a novel speed control technique based on fuzzy logic with two inputs and one output for drive of an IM. The inputs are speed error and derivation of speed error and the output is speed. Finally comparison is done between the PI and fuzzy controllers which shows superiority of the fuzzy controller over PI controller. [ABSTRACT FROM AUTHOR]

This paper proposes a control strategy for energy efficiency improvement of three-phase induction motors (TIM). The main control is based on the indirect field-oriented approach. A loss model-based controller is proposed in order to reduce the cooper and iron losses of TIM for different load values. A nonlinear equation based only on quadrature currents is derived and used to obtain suboptimal flux reference in steady-state conditions. Thus, for dynamic implementation (motor transient), a low-pass filter is included and designed based on the rotor time constant. MATLAB simulations are performed to test the proposed strategy for several operation conditions. To verify the approach in real situations, a 4hp motor drive platform was implemented using F28069 DSP. The effectiveness of the proposed model is demonstrated through simulations and experimental results. [ABSTRACT FROM AUTHOR]

Sensorless-based direct vector control techniques are widely used for three-phase induction motor drive, whereas in case of multiple-motor control, it becomes intensively complicated and very few research articles in support to industrial applications were found. A straight-forward direct vector control with sensorless operation for parallel connected two similar-rated induction motors driven by single three-phase inverter is proposed and verified numerically by simulation software test under balanced and unbalanced conditions. The proposed control algorithm adapts the natural observer to estimate the rotor speed, rotor flux, and load torque of both motors. Simulation results along with theoretical background provided in this paper confirm the feasibility of operation of the ac motors and proves reliability for industrial applications. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid recurrent neuro-fuzzy (RNF) architecture for rotor speed regulation of indirect field oriented controlled (IFOC) induction motor (IM) drive. This approach incorporates Takagi-Sugeno-Kang (TSK) model-based fuzzy logic (FL) laws with a four-layer artificial neural networks (ANNs) scheme. Moreover, for the proposed RNF an improved self-tuning method is developed based on the IM theory and its high performance requirements. The principal task of the tuning method is to adjust the parameters of the FL in order to minimize the square of the error between actual and reference output. The convergence/divergence of the weights is discussed and investigated by simulation. [ABSTRACT FROM AUTHOR]

This study presents a novel neuro-fuzzy (NF)-based auto-tuning proportional integral controller (NFATPI) for accurate speed control, and to ensure optimal drive performances of the indirect field controlled induction motor drive, under system disturbances and uncertainties. The training mechanism of the proposed NF have been developed and illustrated through mathematical formulations. Then, the NF parameters have been updated on-line using a suitable training algorithm. The learning rates of the NF are derived on the basis of the discrete Lyapunov function is also illustrated, in order to confirm the stability and the performance of prediction of the proposed NFATPI. The simulation results confirm the effectiveness of the strategy NFATPI as a robust controller for high performance industrial motor drive systems. [ABSTRACT FROM AUTHOR]

This paper proposes the speed control of IM (Induction Motor) fed by wind turbine using ICA (Imperialist Competitive Algorithm). The wind turbine plays as a prime mover to a connected DC (Direct Current) generator. PWM (Pulse Width Modulation) is used to get three phase AC (Alternating Current) voltage from the output of DC generator. The proposed design problem of speed controller is established as an optimization problem. ICA is adopted to search for optimal controller parameters by minimizing the time domain objective function. The behavior of the proposed ICA has been estimated with the behavior of the conventional ZN (Ziegler–Nichols) and GA (Genetic Algorithm) in order to prove the superiority of the proposed ICA in tuning PI (Proportional plus Integral) controller. Also, the behavior of the proposed controller has been tested over a wide range of operating conditions. Simulation results confirm on the better behavior of the optimized PI controller based on ICA compared with other algorithms. [ABSTRACT FROM AUTHOR]

In this paper, robust PI controllers are designed to control the speed of induction motors based on a vector control strategy. The design methodology defines the robust stability and robust performance regions in the kp - ki (PI controller coefficients) plane using the Kharitonov theorem. In the control system design procedure, a nonlinear induction motor is modeled as an uncertain linear model. The procedure of modeling the uncertainties is presented. The required scientific foundations for designing a robust PI controller are also introduced in the general case while the necessary equations are derived. In the final step, the design procedure for a special motor is presented thoroughly. The simulation results indicate the efficiency of the method. [ABSTRACT FROM AUTHOR]