Optimal control of induction motor using high performance frequency converter

In this paper, we present a new technique to unify and intensify the magnetic fields that results in higher performance of Anisotropic Magneto-Resistive (AMR) current sensors and consequently develop a closed loop controller for 100W synchronous GaN buck converter at 1MHz. The closed loop operation of high switching frequency converters at high power has always been a big challenge due to lack of access to current information. The proposed method that also intensifies the magnetic fields through the sensor, significantly improves the bandwidth limits, and reduces electromagnetic interference (EMI) on AMR sensors, making them applicable for high switching frequency and high current power electronics converters. After verifying uniform distribution concept through simulation, we also implemented a prototype of AMR current sensors onto Printed Circuit Board (PCB) for verification of the concept at high frequency converter. We then present the design procedure and associated challenges of an integrated analogue peak current controller for creating the closed loop operation of a GaN buck converter at high switching frequency.

Control of high performance induction motors: theory and practice

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.

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.

In this paper, the model predictive control (MPC) technique for controlling the speed of sensorless induction motor drive is presented. To decrease the cost and increase the reliability and affectivity of the motor drive, a full order observer for speed estimation based on the model reference adaptive system MRAS is used to estimate the rotor speed. The adaptive full-order observer based on IM equation is used to estimate stator currents and rotor flux. Lyapunov's stability criterion is employed to estimate rotor speed based on the error between the actual and estimated currents. The same algorithm deduced from Lyapunov's stability criterion is given to estimate the stator resistance, which results in the speed estimation error. A simple model of induction motor is employed in the MPC structure so as to minimize the computational load. The MPC controller design is taken into account the effect of uncertainty due to motor parameters variation and load disturbance could be reduced. The effectiveness of the proposed scheme has been successfully verified through simulations. The results proved that the induction motor with the MPC speed controller has superior transient response, and good robustness in face of uncertainties including load disturbance. Moreover, accurate tracking performance has been achieved.

Modeling and control of V/f controlled induction motor using genetic-ANFIS algorithm

Induction motors are robust and inexpensive machines and are widely used for variable speed control because of recent development of electronic technique. In the case that loads of the motors are compressors, pumps, and so on, the constant V/F control of the induction motors is usually employed because it is difficult to install speed sensors and accurate speed control is not required. In such loads, the rotational speed of the motors is considerably fluctuated because the load torque is pulsated. When frequency of the torque pulsation is close to the resonant frequency of the mechanical system, large vibration and acoustic noise are produced especially in low frequency region.In this paper, authors propose a method to suppress the variation of the rotational speed of the V/F controlled induction motor with a fluctuated load by feedforward compensation using a timing sensor of 1 pulse/rev. considering that the load torque varies periodically. The feedforward data by a period for the compensation is obtained by the learning control based on the repetitive control in which the motor speed is controlled by periodically reflecting the past speed error on the present V/F input to the inverter. Effectiveness of the proposed method is confirmed by approximate analysis, simulations and experiments.

The paper analyze the basic principle of model reference adaptive system(MRAS) algorithm. In this paper, rotor position and speed estimation algorithm of permanent magnet synchronous motor was deduced based on MRAS, and it is applied to sensorless vector control system of permanent magnet synchronous motor. Sensorless vector control system based on MRAS is built under the Matlab/Simulink environment. The simulation experiment and result analysis for the situation of motor's starting, speed mutation and load mutation are done. Simulation results prove that the sensorless vector control system of permanent magnet synchronous motor based on the algorithm of MRAS takes good control performance, and the algorithm can accurately estimate the rotor position and speed of the motor.

This work compares the use of direct torque and flux control (DTFC) and model predictive control (MPC) for induction motor (IM) control. These two strategies are fundamentally different in operation since (i) DTFC decides the current control action based on a switching table constructed using a simplified model of the IM, whereas (ii) MPC decides the current control action by on-line minimization of a cost function that uses the available inverter output voltages as optimization variables. Emphasis is given in this work to the reconfiguration of the control action after voltage source inverter faults. We assume that the fault can be suitably detected and isolated and that the inverter can be reconfigured after the specific fault to continue operation, albeit with a reduced set of achievable output vectors. Based on this reduced set of vectors, we propose to reconfigure the induction motor control algorithm by (i) instructing DTFC to use a reconfigured switching table or (ii) providing the reduced set of inverter vectors as the reconfigured constraint set of optimization variables for MPC. Simulation results show that MPC considerably outperforms DTFC at a modest increment of computational cost. Moreover, this increment is less pronounced under fault since the number of optimization variables is reduced.

The induction motor drive is simple in construction, rugged, safe, low-maintenance, and are variable speed motor drive but the cost has increased while making variable speed drive with use of modern control schemes. Therefore, researchers are discovering ways to reduce the cost while achieving variable speed control. One way is by getting rid of speed sensor in the motor shaft. It can reduce program complexity and improve reliability while minimizing the cost. The recent trend in the sensorless control of induction motor drive is to achieve successful reference tracking of estimated speed at low or zero speed. The vector control due to decoupled control of stator flux and rotor torque in induction motor is widely applied for speed control. In this paper, a sensorless vector control of induction motor with fuzzy-based rotor-flux MRAS topology is proposed. The fuzzy logic controller in the speed estimator block has achieved tremendous improvement in the speed estimation at low and even zero speed proving it to be superior to other sensorless control methods. The controller parameter calculation methods are also presented. The model is simulated in MATLAB/SIMULINK software. The results showed satisfactory improvement in the system performance especially at low or even zero speed.

Use of induction motor (IM) at it's highest efficiency is a big demanding task because of their complex mathematical model and non linear features during saturation. These elements make the control of IM strenuous and call for the use of high performance control algorithm such as field orientation control. This paper introduces a speed controller, particularly at minimum speeds by utilizing Fuzzy logic controller (FLC) for indirect field-oriented control (IFOC) of induction motor (IM) drives fed by a four-switch three-phase (FSTP) inverter. From suggested viewpoint, the IM drive is used with a FSTP inverter as an alternative for the conventional six-switch three-phase (SSTP) inverter. Utter IFOC programme includes the FLC of IM drives with the suggested FSTP inverter is raised in MATLAB/Simulink. By considering the good dynamic performance, cost minimization and low total harmonic distortion (THD), FSTP inverters are comparable with SSTP inverters. The dynamic performance and robustness of proposed FLC with the FSTP inverter fed IM drive is verified with PI controller. It is established that the suggested FLC is further powerful than the PI controller under speed tracking and load disturbances

This paper presents literature review on Implementation of IOT (Internet Of Things) for monitoring and control of Induction Motor for various applications such as Electric Vehicles, Industries, Agriculture field etc. This review presents block diagram approach of IOT based monitoring and control of Induction Motor proposed by various authors. The Induction Motor parameters like temperature, speed, current, voltage etc. can be monitored remotely and can be sent to the processing unit for analysis to take necessary actions especially under abnormal conditions for better reliability and efficiency. The data can be accessed from anywhere in the globe through Wifi.

This project investigates the application of model reference adaptive system (MRAS) for the speed sensorless control of an induction motor. The rotor speed can be accurately estimated by employing the closed-loop observer named reactive MRAS. Therefore, this observer eliminates the need of a speed sensor for the control of the motor speed. The method is robust to stator and rotor resistance variations due to change of temperature. The dynamic system equations of the induction machines are formulated, and the motor control system performance is studied. Both scalar voltage-to-frequency (V/f) control and vector field oriented control (FOC) schemes, implemented using digital signal processor (DSP), are investigated. The design of the speed sensorless DSP-based controller is completed. Software packages have been developed to implement the design. An experimental system using the proposed controller has been built. Various tests have been conducted to verify the technical feasibility of the control technique. The experimental results confirm the feasibility of the proposed speed sensorless V/f control scheme using MRAS speed estimator. The designed V/f profile has been tested. Even with step change of the load or that of the command speed, the system can achieve the correct steady state after a short transient operation. The experimental results also confirm the feasibility of the proposed speed sensorless FOC control scheme using MRAS speed estimator. The current regulators meet the design requirements. Both the flux-producing current component and the torque-producing current component can be controlled separately. In the implementation, digital signal processor (DSP) TMS320 FL2407 and voltage source inverter (VSI) Skiip 342GD120-316CTV are employed. The modular strategy is adopted to develop the software package.

Energy optimized sliding-mode control of sensorless induction motor drives

Speed and torque control of an induction motor is usually attained by application of a speed or position sensor. However, speed and position sensors require the additional mounting space, reduce the reliability in harsh environments and increase the cost of the motor. Various control algorithms have been proposed for the elimination of speed and position sensors. This paper investigates a novel speed sensorless control of an induction motor. The proposed control strategy is based on MRAS (model reference adaptive system) using state observer model with current error feedback and rotor current model as two models for flux estimation. The rotor speed is estimated so that the difference between the outputs of state observer model and rotor current model may be zero. This algorithm may overcome several shortages of conventional MRAS: integrator problems, small EMF at low speed, and relatively large sensitivity to resistance variation. The proposed algorithm is verified through simulation and experiment.