Current Control Of Induction Motor Research Articles

Study and Evaluation a New Predictive Control Method for Speed and Stator Current Control of Induction Motor

It is clear that modern industries rely heavily on electric motors, especially induction motors. These motors convert electrical energy into mechanical energy. The distinction in the performance of the induction motor lies in that it is powerful when exposed to various operational and environmental variables, and it is also inexpensive. However, there are many traditional disadvantages that appear during the operation of the induction motor in its non-linear mechanical properties in addition to the difficulty in regulating the speed of the motor. In this paper , we present a new control method for controlling the stator current and speed of induction motor based on current control with speed control technique. The present model is based on conventional predictive controller development with a structure which is similar to rotor control and the direct torque control .It has double loops and both loops will use the prediction power. The inner loop controls the stator current based on Finite Control Set - Model Predictive Control (FCS-MPC) and the outer loop controls the speed to maximize the dynamic response of the loop. The MATLAB software has been used to implement the controller circuit. The obtained simulation results indicates that the presented control method has comparable performance to conventional controllers with some reduction in the overshoot and fast response interval.

Discrete Domain Design Scheme of Complex-Vector Current Controller for Induction Motor at Low Switching Frequency

The synchronous coordinates complex-vector proportional–integral (PI) controller is a high-performance current controller for vector-controlled ac motors, which is designed based on the continuous domain motor models. However, the application of digital signal processors in motor control necessitates the conversion of continuous domain models to discrete domain models. Moreover, the digital control itself has delay effects. Therefore, the original performance of continuous-domain-designed current controllers may be degraded. In order to improve the deteriorative performance, this article proposes corresponding delay compensation schemes for the forward Euler, backward Euler, and trapezoidal method discretized complex-vector PI controllers, respectively, which are analyzed based on discrete domain models. The root locus, frequency characteristics, and bandwidth are utilized to evaluate the performance of these three discretized controllers at the low switching frequency. Finally, the simulation and experimental results validate the analysis and the delay compensation methods proposed in this article.

Robust deadbeat predictive current control of induction motor drives with improved steady state performance

AbstractConventional deadbeat predictive current control (DBPCC) based on space vector modulation (SVM) shows quick dynamic responses and a good steady‐state performance in induction motor (IM) drives. However, the motor parameters change during operation due to temperature and saturation changes, leading to inaccurate reference voltage vectors and a degraded performance. Furthermore, conventional DBPCC uses a fixed vector sequence of 0127 over the entire speed range, which results in large current harmonics at high modulation indices. To address the above issues, this paper proposes a robust deadbeat predictive current control (RDBPCC) for IM drives. Based on an ultra‐local model, the proposed method updates the input voltage gain and unknown system components online according to the voltage and current of the previous two control cycles. Because the final control expression contains only the measured stator current and voltage values, the model shows a strong robustness. The steady‐state performance is significantly improved by selecting the optimal vector sequence according to the modulation index based on the principle of current harmonic minimization. The experimental results confirm that, compared with conventional vector control and conventional DBPCC, the proposed method achieves a strong parameter robustness and reduces the current total harmonic distortion (THD) by more than 10% and 20% at high‐modulation indices.

Robust Finite Control Set Model Predictive Current Control for Induction Motor Using Deadbeat Approach in Stationary Frame

The model predictive control increased its prominence in the field of induction machine drives. However, the performance of this strategy depends on the accuracy of the machine model parameters. In order to overcome this deficiency, this paper proposes a robust model predictive current control employing indirect field-oriented control in stationary reference frame using the stator current and the rotor flux vectors as state and stator voltage vector as the input. The control algorithm combines the classical model predictive control with the deadbeat approach in order to calculate the applied stator voltage vector in two components: one element considers the stator current reference, and another employs the disturbances caused due to the parameter errors, which allows to compensate the parameter mismatches in the plant model. The minimized cost function employs the predicted stator voltage vector to select the voltage vector to be applied to the stator terminals of the motor. The control method performance was verified using an experimental test bench analyzing the system steady-state and dynamic actions. In this way, the results corroborate the proposed controller robustness against parametric variations.

Convergence Trajectory Optimization of Supertwisting Sliding-Mode Current Control for Induction Motor Drives

For the induction motor (IM) current loop, the supertwisting sliding-mode control (ST-SMC) has been considered as an effective approach to achieve chattering suppression and steady-state errorless control. However, due to the system disturbance, the conventional ST-SMC suffers from control delay in the convergence trajectory, resulting in decreased antidisturbance capability. To address this problem, this article proposed a ST-SMC with convergence trajectory optimization. First, a nonlinear sliding-mode manifold is designed to achieve the ideal ST-SMC convergence trajectory. Then, a disturbance compensation term is added into the control law to eliminate the system control delay. Compared with the conventional ST-SMC, the studied method can effectively enhance the antidisturbance capability of IM current loop, leading to improved transient performance. Finally, the superiority of the investigated method is verified by the experimental results from a 3.7 kW IM test bench.

An improved deadbeat predictive current control for induction motor drives

An improved deadbeat predictive current control for induction motor drives

Integral Sliding Mode Observer-Based Ultralocal Model for Finite-Set Model Predictive Current Control of Induction Motor

The ultralocal model of a plant expresses the behavior of the output variable in relation to the input without requiring any specific information about the plant. Replacing the conventional model of the system with an ultralocal model can effectively improve the robustness of the model predictive control (MPC) because all types of uncertainties that correlate with the system modeling are removed in the ultralocal model. This article proposes an integral sliding mode observer (ISMO)-based ultralocal model for the finite-set model predictive current control (FS-MPCC) of an induction motor (IM). The ISMO is constructed based on the Lyapunov theory to guarantee the stability of the proposed control method. Moreover, an analytical comparison is made between the proposed ISMO and the conventional extended state observer (ESO) in the application of the ultralocal model. This comparison shows that the stability of ESO depends on the unknown term of the ultralocal model. In contrast, the stability of the proposed ISMO does not rely on any terms of the ultralocal model. Experimental tests confirm that the proposed FS-MPCC method is practically applicable to the IM drive system. Also, it improves the robustness of the predictive method against model uncertainty.

Active Disturbance Rejection Control-based Robust Model Predictive Current Control for Induction Motor

Active Disturbance Rejection Control-based Robust Model Predictive Current Control for Induction Motor

Robust Current Control of Voice Coil Motor in Tip-Tilt Mirror Based on Disturbance Observer Framework

In this paper, a control methodology based on the disturbance observer (DOB) framework is proposed to improve the current dynamic characteristic and the robustness of the voice coil motor (VCM) in the tip-tilt mirror. It is shown that the open-loop current characteristic is a third-order plant, which is influenced obviously by both the electrical and mechanical uncertainties under different environment temperatures. Although the traditional PID control is helpful to improve the current dynamics, it is not able to provide enough robustness. Therefore, a new control methodology based on DOB is proposed. The plant model is simplified from third-order to first-order by considering the back-electromotive force (EMF) as the disturbance. The perturbation of the electrical parameters is compensated by the inner-loop of the DOB framework, and the perturbation of the mechanical parameters is compensated by suppressing the back-EMF. Moreover, new sufficient conditions for robust stability are presented in the control method based on H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> algorithm. Compared with the traditional researches, the upper bound of the uncertainties is calculated directly in this paper. Therefore, the ranges of the electrical parameters are very clear according to the Q-filter. Based on the stability conditions, new design guidelines for the DOB-based robust current control for induction motor are also presented. Experiment results are given to show the design details and the superiority of the proposed control method.

Hardware in the loop co-simulation of finite set-model predictive control using FPGA for a three level CHB inverter

Along with the development of powerful microprocessors and microcontrollers, the applications of the model predictive controller, which requires high computational cost, to fast dynamical systems such as power converters and electric drives have become a tendency recently. In this paper, two solutions are offered to quickly develop the finite set predictive current control for induction motor fed by 3-level H-Bridge cascaded inverter. First, the field programmable gate array (FPGA) with capability of parallel computation is employed to minimize the computational time. Second, the hardware in the loop (HIL) co-simulation is used to quickly verify the developed control algorithm without burden of time on hardware design since the motor and the power switches are emulated on a real-time platform with high-fidelity mathematical models. The implementation procedure and HIL co-simulation results of the developed control algorithm shows the effectiveness of the proposed solution.

Advanced model predictive current control for induction motor drive system fed by indirect matrix converter

To decrease both the number and tuning difficulty of weighting factors, an advanced model predictive current control is proposed for an induction motor drive system fed by an indirect matrix converter, where the input and output currents of the indirect matrix converter are designated as control objectives. The reference input currents are established on the basis of the instantaneous power theory and optimized using a low-pass filter. In addition, the reference output currents are determined using a reference flux vector based on the deadbeat theory. As a result, there is only one weighting factor for parameter tuning, and the predictive models are significantly simplified. In addition, both the phase and the quality of the input currents are considered and controlled, which can improve the grid power quality. Simulation and experimental results show that the sinusoidal grid/output currents, a unity power factor, and good steady-state and dynamic performances of the induction motor have been achieved. In addition, the execution time of the entire algorithm was noticeably shortened.

Integral FCS Predictive Current Control of Induction Motor Drive

This paper derives the algorithm of integral plus finite control set (FCS) -predictive control for AC motor drives. In the paper, it is shown that the original FCS-predictive control algorithm in the d – q reference frame is equivalent to a dead-beat control system in the presence of constraints, where the closed-loop system is approximated by a unit time delay. Without integral action, the original FCS-predictive control system contains steady-state errors in both d-axis and q-axis currents, hence compromising closed-loop performance. Using an integral control in a cascaded structure to the original FCS-predictive control, a simple algorithm is proposed to eliminate the steady-state errors of the current control system and improve its closed-loop performance. The sampling interval of the current control system is used as a performance tuning parameter for reduction of current variations. Furthermore, the algorithm is expressed in a velocity form for convenience in implementation using a digital signal processor. Experimental results are used to show the successful design and implementation of the integral finite control set (I-FCS) predictive control.

Adaptive neuro‐fuzzy current control for multilevel inverter fed induction motor

PurposeThe paper aims to propose an adaptive and robust on‐line trained neuro‐fuzzy current controller based on indirect field oriented control (IFOC) for the current control of multilevel inverter fed induction motor (IM).Design/methodology/approachTorque current of IM is controlled with Sugeno type neuro‐fuzzy controller (NFC) which has the ability of self tuning against parameter variations and load disturbance. Input variables of the neuro‐fuzzy current controller are chosen error and integral of error in order to eliminate steady state error. The consequent parameters of neuro‐fuzzy current controller are trained on‐line through backpropagation learning algorithm.FindingsThe validity of proposed current control algorithm is shown with experimental results carried out under different speed commands, parameter variations and load disturbances. The experimental results show that control performance of NFC in the current control of IMs is satisfactory because of its adaptive and robust structure.Originality/valueThis paper presents the design of an on‐line trained neuro‐fuzzy current control to improve the current control performance. The performance of the current controller largely depends on using converter systems. In this study, a multilevel inverter is used to obtain less harmonic distortion and near sinusoidal form of output voltage and current waveforms of the converter.

Torque and Current Control of Induction Motor Drives for Inverter Switching Frequency Reduction

In this paper, an indirect field-oriented control (FOC) induction motor (IM) drive with instantaneous current and torque control is presented. This proposed control scheme employs hysteresis current and torque controllers to regulate the stator currents. The torque controller is proposed to serve the current controller so that full advantage of the zero voltage vector can be taken to reduce the switching frequency of the inverter. As a result, the actual stator currents can follow the current references as closely as possible, and the current ripple and torque ripple can be greatly decreased compared with the conventional adaptive pulsewidth modulation control method. To verify the feasibility of the proposed scheme, computer simulations and experiment results demonstrate that the proposed method can obtain a high-performance IM drive system.

Current control for induction motor drives using random PWM

Current control in voltage-source inverters with random pulsewidth modulation (RPWM) is investigated. The random modulation is introduced to alleviate the undesirable acoustic, vibration, and EMI effects in inverter-fed AC drive systems. A novel RPWM digital technique with dithering of the switching frequency and compensation of the processing time is described. Design of the current control loop is discussed. Results of investigation of an experimental drive system are presented, proving the feasibility of the proposed solutions.

Variable structure current control for induction motor drives by space voltage vector PWM

In this paper, a variable structure current controller based on a space voltage vector PWM scheme is presented for induction motor drives. In this current controller design, only the current sensors are employed and we attempt to force the stator currents to be exactly equal to the reference currents rapidly. This proposed current controller, which is based on the space voltage vector PWM drive, exhibits several advantages in terms of reduced switching frequency, robustness to parameter variations, elimination of current/torque ripple, and improved performance in induction motor drive. It shows that the current control laws can be demonstrated in theory. Finally, simulation and experimentation results verify the proposed control scheme.

A novel vector control hysteresis current controller for induction motor drives

In this paper, a novel vector control hysteresis current controller for induction motor drives is proposed. Coordination of three phase switches is made in the d-q phase plane. In addition to the current error, information of the current error derivative is further employed so that one can take full advantage of adding the zero voltage vector for reducing the switching frequency. A simple hardware implementation is also proposed such that merits of the conventional hysteresis current controller can still be kept. The theoretical basis and some simulation and experimental results are also covered in this context. >

A novel vector control hysteresis current controller for induction motor drives

A novel vector control hysteresis current controller for induction motor drives