SPWM Volt/Hz Based Speed Control of Induction Motor

Recently, many studies have been performed for the variable speed control of an induction motor. Direct torque control (DTC) is an emerging technique for the variable speed control of PWM inverter driven induction motors. DTC allows the direct control of stator flux and instantaneous torque through a simple algorithm. In this paper, an ASIC design technique using VHDL is applied to DTC based speed control of an induction motor. ASIC for DTC based speed control is designed through the descriptions of coordinate transformation, speed controller stator flux and torque estimator, stator flux and torque controller stator flux position detector, FSM (finite state machine) and inverter voltage switching vector. Finally the above system has been implemented on the FPGA (XC4052XL-PG411). Simulation and experiments have been performed to verify the performance of the designed ASIC.

Because of its low maintenance and robustness, induction motors have many applications in the industries. Most of these applications need fast and smart speed control system. This paper introduces a smart speed control system for induction motor using fuzzy logic controller. Induction motor is modeled in synchronous reference frame in terms of dq form. The speed control of induction motor is the main issue achieves maximum torque and efficiency. Two speed control techniques, Scalar Control and Indirect Field Oriented Control are used to compare the performance of the control system with fuzzy logic controller. Indirect field oriented control technique with fuzzy logic controller provides better speed control of induction motor especially with high dynamic disturbances. The model is carried out by using Matlab/Simulink computer package. The simulation results show the superiority of the fuzzy logic controller in controlling three-phase induction motor with indirect field oriented control technique.

In the induction motor speed control without sensors operated by the method Field Oriented Control (FOC) was required an observer to estimate the speed. Obsever methods have been developed, among others, was the method of Self-Constructing Fuzzy Neural Network (SCFNN) with some training algorithms such as backpropagasi (BP). Levenberg Marquard (LM) etc.. In the induction motor control techniques were also developed methods of Direct Torque Control (DTC) with observer Recurrent Neural Network (RNN). This paper compares the performance of the motor response to initial rotation between SCFNN observer method that uses the LM training algorithm with DTC control technique with RNN observer. From the observation performance of the motor response to initial rotation of the two methods shows that the LM method has better performances than the RNN. This can be seen on both the parameters : overshoot, rise time, settling time, peak and peak time. With the right method, can enhance better performance of the system. With the improvement of system performance, is expected to increase work efficiency in the industrial world, so overall, particularly for systems that require high precision, FNN methodcan be said to be better. Keywords: Motor Speed control without sensors, FOC, SCFNNO, DTC, Levenberg Marquardt and RNN. DOI: http://dx.doi.org/10.11591/ijpeds.v1i1.66

Fuzzy controlled sensorless speed control of induction motor with MRAS based approach is proposed in this paper. Fuzzy logic controller is expected to be better controller as compared to traditional PI and PID controllers. The mathematical modeling of the MRAS module with inputs from induction motor stator voltages and currents taken as feedback to estimate the speed of the machine is described. The speed control of the induction motor is achieved by IRFOC without speed sensor at the motor. Induction motor speed and electromagnetic torque comparison with PI and FIS controllers integrated into the structure are represented by graphs plotted with time as a reference. Fuzzy controller is modeled with 49 rule base including two inputs and one output variable. All the modules design and the analysis is carried out in MATLAB software with ‘powergui’ toolbox for generating graphs.

This paper proposes a design process of speed controller for induction motor using tabu search algorithm. The proposed process has two parts. The first part is optimization of the initial parameters of input-output. And the second part is changing parameters of input-output using tabu search. Proposed tabu search is improved by neighbor solution creation using Gaussian random distribution. In order to see the usefulness of the proposed method, it is applied to the sensorless speed controller of an AC induction motor system. The performance of this approach is verified through simulation.

This paper presents Pareto-based multi-objective optimization for speed control of induction motor with fractional order proportional integral ( $$\hbox {FOPI}^{\lambda }$$ ) controller. The aim of this study is to find optimum values of tuning parameters of $$\hbox {FOPI}^{\lambda }$$ by using Elman neural network (ENN) and Pareto-based multi-objective optimization. In this context, proportional gain $$K_{\mathrm{p}}$$ , integral gain $$K_{\mathrm{i}}$$ and the order of fractional integral $$\lambda $$ are selected as tuning parameters while settling time $${T}_{\mathrm{s}}$$ and overshoot $${M}_{\mathrm{o}}$$ are chosen as objective functions. Firstly, experiments have been carried out to obtain training and test data. Then, ENN has been trained to construct mathematical model which is necessary for multi-objective optimization. In the next step, accuracy and reliability of ENN model are tested by using test data taken from experimental set-up. Finally, Pareto-based multi-objective optimization method has been used to find the optimum values of tuning parameters that minimize both $${T}_{\mathrm{s}}$$ and $${M}_{\mathrm{o}}$$ values. The different three conditions of the Pareto solution set are applied to the experimental set-up to verify the effectiveness of the proposed method. Results show that ENN is well modelled for induction motor and Pareto solution is an effective method to find optimal values of controller coefficients according to desired $${T}_{\mathrm{s}}$$ and $${M}_{\mathrm{o}}$$ values.

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.

Induction motor is a cast of alternating current motor where charge endures allotted to the rotor close-at-hand deputation of conductive charge. These motors are broadly applied in industrial claim due to they are arduous along with adhere no contacts. The speed controller of deltoid phase induction motor is applied to alleviate the aberration of speed. The central constructivist of this paper is to accrue the performance of speed sensorless control of three phase induction motor. To increase its performance, this paper presents a modified method for speed controller of an indirect vector-controlled induction motor drive using cloud computing technique. Our methodology depends on speed sensorless scheme to obtain the speed signal feedback; the speed estimator is based on model reference adaptive control that uses the stator current and rotor flux as state variables for estimating the speed. In this method, the stator current error is represented as a function of first degree of the estimated speed error. An analysis and simulation of the tried algorithm is birthed and applied easing a TMS320C31 floating-point notational alert Processor. And accumulate the action of the three phase induction motor we conceived our appraisals affixed to the accountant based on cloud computing tactics. This intelligent policy uses the guidelines of the speed controller efficiently. Simulation and experimental results depicted that the motor speed is decelerated articulately to destine its illusion apprise without above and inferior smack and with about zero steady state error. The apprised accelerate alert and its dispatching buoy amassed off line from burlesque. After effects display an advantageous affinity among the accounted speed alert and it's dispatching allocated as well as aped speed flares.

Induction motor drives are grabbing attention from many researchers due to its features and applications. Among many available control methods of the induction motor drives, Direct Torque Control (DTC) is a powerful technique and it is having a wide range of applications in industries. In the conventional DTC method, only one controller is utilized to obtain reference torque where reference flux becomes constant. Hence, speed control of induction motor under DTC having its limitation on flux region. Consequently, a second controller is included in this paper to manage the flux by generating a reference flux derived from the discrepancy between the motor speed and its reference. However, conventional PI or PID controllers are unable to deliver its output effectively under rapid variations in the system. Hence, Fractional Order Proportional-Integral-Derivative (FOPID) controllers are incorporated in the proposed DTC method where utilized two FOPID controllers to regulate both torque and flux simultaneously. Further, Space Vector Pulse Width Modulation (SVPWM) is also included in the proposed control method to produce accurate and instant pulses for achieving accurate responses. In this study, the inverter is utilized with two FOPID controllers alongside the SVPWM technique. The proposed control method can effectively minimize ripples in both flux and torque. OPAL-RT modules based Hardware - in the - Loop (HIL) system is developed for presenting various outcomes to enhance the presented control.

The speed control of induction motors can be divided into two distinct strategies, depending on the type of dynamics that is required: scalar control (static control of the torque) and vector control (dynamic control of the torque) (Blaabjerg et al. 2005; Bose, 2000, 2006; Filote et al. 2009; Holtz, 2002; Leonhard, 1990; Umanand & Bhat, 1995; Vas, 1998). Since the couple and flux levels depend on the motor behavior to frequency and voltage applied to it, maintaining the flux constant is strongly required in scalar control (V/f control). Despite the simplicity and the low cost implementation of the control method, it still presents the disadvantage of poor torque dynamics. Vector control reassesses one of the advantages of direct current (dc) drives, which is the separation of speed and couple loops. According to its structure and to its own functioning principle, the dc drive is naturally field oriented, hence, the separation of the speed and current loops. In the case of vector controllers of induction motor, the magnitude and phase stator current are controlled in accordance with the flux vector. There are three vector control strategies according to the type of drive-controlled flux: stator flux, rotor flux and air gap flux. We can determine the magnitude and position of the rotor flux by using flux sensors (direct field-oriented control), estimators or observers (indirect field-oriented control) and by measuring some electrical and mechanical measurable states of electrical drives induction motor systems. When the rotor flux estimation is performed after measuring only the electrical measurable states (voltages and stator currents), in this case we have a sensorless vector control system. The implementation of the direct field-oriented control requires the measurement or calculation of the flux space vector (magnitude and position). The measurement of the air gap flux requires the use of some Hall sensors (Umanand & Bhat, 1995), which requires specially constructed induction motor. On one hand, they are very sensitive to temperature and mechanical vibrations. The flux signal is highly distorted by slot harmonics (Kreindler, 1994), whose spectrum and amplitude depend on the rotor speed (hence, the difficulty to be filtered). The implementation of the indirect field-oriented control requires the identification of rotor flux instantaneous position, and the calculus of stator current prescribed value in sensorless vector control system (Gadue et. al. 2009; Griva et al. 1997; Lascu et al. 2004). The

This research paper presents a novel method for the speed control of induction motors without using a speed sensor. The rotor speed can be accurately computed using an optimal control observer named the Kalman filter designed in this research paper. This replaces a speed sensor and eliminates the difficulty of the sensor installation in many applications. This research paper presents an advanced field oriented control of induction motors, based on a specific d-q coordinate model with the d-coordinate chosen to be in line with the rotor flux and the q-coordinate chosen to be 90⁰ lagging. The position of the rotor flux can be accurately computed using the Kalman filter. This eliminates the position sensors required accurately to monitor the flux. This research paper shows that as a result of this specific d-q transformation, the motor torque is proportional to the product of the rotor flux and the q-coordinate stator current. This significantly simplifies the induction motor control, such that the rotor flux is simply controlled by regulating the flux-related d-coordinates stator current and the motor torque is controlled just by regulating the q-coordinate stator current. This research paper presents a computational efficient recursive algorithm for Kalman filter which is specifically designed for the induction motor control. The Kalman filter provides the minimum variance state estimation and tolerates induction motor modelling and measurement errors. The Kalman filter can process all available measurements regardless of their precision (only two input current measurements required for the motor control), and provides a quick and optimal estimate of the variables of interest (the rotor speed and flux selected as outputs), as well as achieves a fast convergence. This research paper presents the digital signal processor (DSP) implementation of the field oriented control of induction motors using Kalman filter. The hardware requirements and all software modules are detailed. The experimental verification of the control method designed in this research paper is provided. Typical measurements are given to demonstrate the efficiency of the novel control presented in this research paper.

Indirect vector control or Indirect Field Oriented Control (IFOC) is known to produce high performance in induction Motor (IM) drives by decoupling rotor flux and torque producing current components of stator current. The most commonly used controller for the vector control of ac motor is Proportional- Integral (P-I) controller. However, the P-I controller has some disadvantages such as high starting overshoot, sensitivity to controller gains and sluggish response to sudden disturbances. So, the Integral-Proportional (I-P) controller is proposed as speed controller for induction motor drives to overcome the disadvantages of the P-I controller. Simulation results are presented and analyzed for both the controllers and it is observed that Integral-Proportional (I-P) controllers give better responses than the traditional P-I controllers for the Indirect Field Oriented Control (IFOC) of ac motor drives.

Sliding mode control (SMC) of electric drives constitutes a very popular control method for nonlinear multivariable and time-varying systems, e.g., induction motor (IM) drives. Nowadays, IM are the most popular electrical machines (EM) applied in many industrial applications as motion control devices, including electrical and hybrid vehicles. Nowadays, the control systems of EM are mostly realized using digital techniques (microprocessors and microcontrollers). Therefore, all control algorithms should be discretized or the whole control system should be designed in the discrete-time domain. This paper deals with a discrete-time sliding mode control (DSMC) for IM drives. The discrete algorithms for sliding mode control of the motor speed and rotor flux are derived in detail and next tested in simulation research. The simulation tests include the discrete nature of the power converter supplying the IM and present excellent performance of the developed control structure. To obtain the rotor speed regulation invariant to external disturbances, like load torque or inertia, especially during the reaching phase of the switching line, the discrete version of a time-varying switching line was introduced. It is shown that the assumed dynamics of the IM flux and speed is achieved and the proposed control algorithm can be realized using commonly available microcontrollers. The paper is illustrated with comprehensive simulation results for 1.5 kW IM drive, which are verified by experimental tests.

This paper presents the scalar control as well as direct torque control for speed control of induction motor. The scalar control is an easy to implement but it gives poor dynamic response. In addition to the scalar control the space vector pulse width modulation (SVPWM) is used for effective utilization of the dc-link voltage i.e. SVPWM is having the good voltage regulation and reduces the considerable harmonics in voltage as well as current of the inverter. The dynamic response of the induction motor is improved using direct torque control with SVPWM technique. The performance of induction motor with scalar control and direct torque control is simulated in the Matlab environment and compared their response under similar operating conditions. The dynamic performance, the speed regulation, THD in the current, and the torque distortion of induction motor are effectively improved with direct torque control (i.e. lesser transient time) even while applying the load in comparison to scalar control.

Induction motor is most commonly used drive in industrial applications. Many applications require precise speed control of induction motor drive with both steady state as well as dynamic state matching the desired pattern and in all cases immunity to disturbance is desired. In the past induction motors have been used for constant speed only but now due to availability of high performance, low loss semiconductor devices the speed control has become fast, accurate and efficient. Here in this study for more realistic results the voltage source SPWM inverter has been simulated with P-Spice and other blocks have been simulated in MATLAB-Simulink and both the aspects of speed set-point tracking control and regulatory control for load variations have been considered for an induction motor using closed loop control technique. Then using SLPS interfacing the results have been obtained for the two cases. The focus of this study is to consider the effect of characteristic of components used in the nonlinear final control element the inverter.