Rotor Resistance Variation Research Articles

Adaptive field-oriented control of current-fed induction motors: a discrete-time implementation

Indirect field oriented control (IFOC) is the industry standard for high performance current-fed induction motors. It is well-known that this controller preserves stability in the face of large rotor resistance variations – which are inevitable in practical scenarios – but its performance is significantly degraded. To overcome this drawback many adaptation schemes have been reported, both in drives and control-oriented publications, with the overwhelming majority of these developments done in continuous-time. This, in spite of the fact that the IFOC, as well as their proposed adaptive versions, involve the solution of highly nonlinear differential equations, whose discretization is far from obvious. In this paper we try to reverse this trend and present a discrete-time estimator of the motor parameters and an adaptive IFOC based on it. It is shown that the proposed estimator and adaptive controller are globally convergent under very weak prior knowledge and excitation assumptions. Simulations, that validate the theoretical claims and illustrate the robustness of the schemes, are also presented.

Rapid Prototyping and Hardware-In-the-Loop Verification of Enhanced Sliding Mode Control of an Asynchronous Machine Using a Xilinx System Generator and an FPGA-Zynq Board

This article describes rapid prototyping using the Xilinx system generator (XSG) of a direct field oriented control (DFOC) strategy based on improved super twisting sliding mode controllers (ISTSMCs) of an asynchronous machine to succeed a hardware implementation on a field programmable gate array (FPGA) board. The main goal is to enhance regulation loops governing rotor speed, rotor flux, and stator current components within the classical DFOC structure. These ISTSMCs replace integral proportional controllers, resulting in improved system dynamics, faster speed and torque responses, and heightened robustness against load and rotor resistance variations, surpassing other control methods. Additionally, the article aims to implement this DFOC-ISTSMC method on an FPGA board to reduce control system sampling time and loop delays, leveraging the FPGA’s parallel processing capabilities. The hardware architecture is designed using XSG in the MATLAB/Simulink environment, enabling effective simulation, testing, discrete algorithm creation, and VHDL code generation for FPGA implementation via the hardware-in-the-loop (HIL) process. Assessment involves digital simulation studies and HIL processes using XSG with a Xilinx FPGA Zynq 7000 under MATLAB/Simulink, demonstrating improved system performance, reduced time delays, and efficient FPGA utilization. This approach validates the effectiveness of the proposed DFOC-ISTSMC algorithm in enhancing control strategy for asynchronous machines.

Compensation of Current Sensor Faults in Vector-Controlled Induction Motor Drive Using Extended Kalman Filters

In electric drive systems, one of the most common faults is related to measurement equipment, including current sensors (CSs). As information about the stator current is crucial to ensure precise control of AC drives, such a fault significantly affects the quality and security of the entire system. For this reason, a modified extended Kalman filter (EKF) has been presented in this paper as an algorithmic solution to restore stator current in the event of CS failure. In order to minimize the impact of rotor and stator resistance variations on the quality of the estimation, the proposed model includes an estimation of the general coefficient of their changes. In contrast to solutions known in the literature, the presented model considers changes in both resistances in the form of a single coefficient. This approach allows us to maintain a low order of the estimator (fifth) and thus minimize the tendency to system instability and decrease computation burden. Extensive simulation tests have shown a significant improvement in the accuracy of stator current estimation under both motor and regenerating modes, a wide speed range (1–100%), and changes in motor parameters.

Robustness of the Fuzzy Adaptive Speed Control of a Multi-Phase Asynchronous Machine

Fuzzy controllers are a powerful tool for controlling complex processes. However, its robustness capacity remains moderately limited because it loses its property for large ranges of parametric variations. In this paper, the proposed control method is designed, based on a fuzzy adaptive controller used as a remedy for this problem. For increase the robustness of the vector control and to maintain the performance of the five-phase asynchronous machine despite the presence of disturbances (variation of rotor resistance, rotor inertia variations, sudden variations in the load etc.), by applying the method of behaviour model control (BMC). The results of simulation show that the fuzzy adaptive control provides best performance and has a more robustness as the fuzzy (FLC) and as a conventional (PI) controller.

Nonlinear control of an induction motor taking into account saturation and rotor resistance variation effects

<span lang="EN-US">Nowadays, electrical drives require more and more precision and reliability. Induction machine is one of the most robust actuators in terms of maintenance and reliability. Their control requires a good knowledge of the physical phenomena governing its operation. Saturation and heating are two main phenomena that must be taken into account to achieve the desired performance. In this paper, we will synthesize a nonlinear control law based on the “Backstepping” method, to regulate rotor speed and flux. This law takes into account saturation and rotor resistance variation effects. The immunity of the control to temperature rise will be tested. This control strategy is studied by simulation in the MATLAB/Simulink environment.</span>

СПОСТЕРІГАЧ ПОТОКОЗЧЕПЛЕННЯ, АДАПТИВНИЙ ДО ЗМІН АКТИВНОГО ОПОРУ РОТОРА АСИНХРОННИХ ДВИГУНІВ

A flux observer for induction motors which is adaptive to the active rotor resistance variations is presented. Due to the added fluxes overestimation in the observer structure, the global exponential stability properties of the current and flux vector components and active rotor resistance estimation are ensured under conditions of persistency of excitation. The proposed observer has a simpler structure compared to existing solutions with the global stability properties. The simulation results of the observer dynamic performance investigation confirm its effectiveness. It is shown that even if the conditions of persistency of excitation are not met, the active rotor resistance is estimated correctly; consequently, the designed observer can be implemented as an identification algorithm in self-commissioning systems of induction electric drives. References 9, figures 5.

A Neural Controller for Induction Motors: Fractional-Order Stability Analysis and Online Learning Algorithm

In this study, an intelligent control scheme is developed for induction motors (IMs). The dynamics of IMs are unknown and are perturbed by the variation of rotor resistance and load changes. The control system has two stages. In the identification stage, the group method of data-handling (GMDH) neural network (NN) was designed for online modeling of the IM. In the control stage, the GMDH-NN was applied to compensate for the impacts of disturbances and uncertainties. The stability is shown by the Lyapunov approach. Simulations demonstrated the good accuracy of the suggested new control approach under disturbances and unknown dynamics.

SIMULATION OF SPEED CONTROL OF DRIVES : CONTROLLING BY APPLIED VOLTAGE

The induction machine is the work horse of the industry. It has rugged construction and is suitable for many high power applications. Induction motors are the most widely used electrical motors due to their reliability, low cost and robustness. However, induction motors do not inherently have the capability of variable speed operation. Due to this reason, earlier dc motors were applied in most of the electrical drives. But the recent developments in speed control methods of the induction motor have led to their large scale use in almost all electrical drives. Out of the several methods of speed control of an induction such as pole changing, frequency variation, variable rotor resistance, variable stator voltage, constant V/f control, slip recovery method etc., the closed loop constant V/f speed control method is most widely used. In this method, the V/f ratio is kept constant which in turn maintains the magnetizing flux constant so that the maximum torque remains unchanged. During starting of an induction motor,

Observer-based speed estimation for vector controlled induction motors

A speed observer for field-oriented controlled induction drives is presented. The proposed solution exploits the concept of the classic full-order flux observer which is adaptive to the rotor resistance variations. Due to the structural similarity of the rotor speed and active rotor resistance in motor model, the speed observer can be designed using similar structure. The observer guarantees local asymptotic estimation of the rotor fluxes, stator currents and rotor speed in all operating conditions, excluding DC stator excitation. The stability properties of the observer are studied using Lyapunov’s second method. It is experimentally shown that the observer provides an acceptable dynamics of the speed estimation if speed is slowly varying. The proposed observer is suitable for the applications with medium requirements for speed regulation performance. References 13, figures 5.

Adaptive doubly fed induction generator’s control driven wind turbine using luenberger observer optimized by genetic algorithm

The calculation of control parameters for a system control method is based on the model of the system with assumed fixed internal parameters. However, these parameters can vary greatly due to several phenomena. This paper presents an adapted control of a doubly fed induction generator machine robust against the rotor resistance variations of the machine used as a generator in wind energy conversion systems. The adaptation is ensured by a system allowing to identify in real time the value of the resistance, the system used is mainly based on a Luenberger observer. The conversion system is divided into two parts, the first mechanical part containing the turbine and the gearbox, the second electrical one consisting of a double fed induction generator, linked on the stator side directly to the grid, and on the rotor, side linked to the grid through two power electronics converters interposed with a direct current (DC) link. The machine-side converter is used to control the active and reactive powers, and the second on the grid side is used to control the DC link voltage. The converters are controlled by the sliding mode strategy, and the validity of the methods is checked by simulation using MATLAB/Simulink.

Integral Backstepping Control of Induction Machine

The goal of this work is to propose a latest design of a rotor speed and rotor flux modulus control approach for an induction machine using a Backstepping corrector with an integral action. The advantage of the Backstepping Strategy is the ability to manage a nonlinear system. The Lyapunov theory has been used to ensure the system stability. To improve the controller robustness proprieties the integral action is used, despite the system uncertainties and the existence of external disturbances. The unavailable rotor flux is recovered by estimation of the rotor flux of the machine based on the integration of the stator voltage expressions. The simulation results illustrate the effectiveness of the proposed control scheme under load disturbances, rotor resistance variation and low and high speed.

ROBUST DIRECT FIELD ORIENTED CONTROL OF INDUCTION GENERATOR

A novel and robust field oriented vector control method for standalone induction generators (IG) is presented. The proposed controller exploits the concept of direct field orientation and provides asymptotic rotor flux modulus and DC-link voltage regulations when a DC-load is constant or slowly varying. Flux subsystem, designed using Lyapunov’s second method, has, in contrast to standard structures, closed loop properties and therefore is robust with respect to rotor resistance variations. A decomposition approach on the base of the two-time scale separation of the voltage and torque current dynamics is used for design of the voltage subsystem. The feedback linearizing voltage controller is designed using a steady state IG power balance equation. The resulting quasi-linear dynamics of the voltage control loop allows use of simple controllers tuning procedure and provides an improved dynamic performance for variable speed and flux operation. Results of a comparative experimental study with standard indirect field oriented control are presented. In contrast to existing solutions, the designed controller provides system performances stabilization when speed and flux are varying. It is experimentally shown that a robust field oriented controller ensures robust flux regulation and robust stabilization of the torque current dynamics leading to improved energy efficiency of the electromechanical conversion process. The proposed controller is suitable for energy generation systems with variable speed operation. References 18, figures 8.

Adaptive proportional-integral fuzzy logic controller of electric motor drive

This paper presents the indirect field vector control of induction motor (IM) which is controlled by an adaptive Proportional-Integral (PI) speed controller. The proposed solution can overcome the rotor resistance variation, which degrades the performance of speed control. To solve this drawback, an adaptive PI controller is designed with gains adaptation based on fuzzy logic in order to improve the performances of IM with respect to parameters variations, particularly the rotor resistance (Rr). The proposed control algorithm is validated by simulation tests. The obtained results show the robustness towards the load torque disturbances and rotor resistance variation of the adaptive Proportional-Integral fuzzy logic control with respect to classical PI control, and adaptive control based on rotor resistance observer.

Robust ANFIS Vector Control of Induction Motor Drive for High-Performance Speed Control Supplied by a Photovoltaic Generator

This paper presents the vector control of Induction Motor (IM) supplied by a photovoltaic generatorwhich is controlled by an adaptive Proportional-Integral (PI) speed controller. The proposed solution is used toovercome the induction motor rotor resistance variation problem, which can affect negatively the performanceof the speed control. To overcome the rotor resistance variation, an adaptive Proportional-Integral controller isdeveloped with gains adaptation based on Adaptive Neuro-Fuzzy Inference System (ANFIS) in order to guaranteea high performances of electric drive systems against the parametric variations. The proposed control algorithmis tested by Matlab-Simulink. Analysis of the obtained results shows the characteristic robustness to disturbancesof the load torque and to rotor resistance variation compared to the classical PI control and Model ReferenceAdaptive System (MRAS) rotor resistance observers.

Linear parameter varying sensorless torque control for singularly perturbed induction motor with torque and flux observers

In this paper, a new approach being different from the concept of DTC and IFOC for a robust torque control design for induction motor is addressed. The design is based on the framework of singularly perturbed system theory and linear varying parameter systems. In these systems, the rotor flux is considered to be a time-varying parameter in order to guarantee a robust torque control with LPV flux observer with respect to the speed and resistance variations. In fact, this observer is designed to estimate the rotor flux as well as an MRAS observer is introduced to estimate the mechanical speed and rotor resistance. The main feature of this proposed structure is the enhancement of robustness with flux, speed and rotor resistance variation. This improvement leads to a considerable decrease of the torque ripples and ensures the stability for the entire operating range. The obtained simulations and experimental results are used to validate the effectiveness of the proposed control strategy.

Matlab Simulation of DPC-SVM of DFIG Based on Wind Energy System

This paper presents Mat-lab simulation of direct power control – space vector modulation (SVM) of doubly fed induction generator (DFIG) for wind energy system. It is applied as an alternative method to the classical field oriented control. Field-oriented control is a complex system which has the cur-rent controller, power controller, and frame transformation. Its behavior is more sensitive to the parameter variations of rotor and stator resistance and the inductance. Direct power control (DPC) technique provides robust performance and power quality improvement. Space vector modulation scheme provides constant switching frequency that results in reduced oscillation of power and making system performance robust with fast response time. In this paper, performance of DPC-SVM of grid connected DFIG is investigated at different wind speed conditions and are simulated in Matlab Simulink.

Fuzzy MRAS rotor resistance identification of BL-IM based on reactive power

As for the inverse decoupling control system of a bearingless induction motor (BL-IM), in order to eliminate the influence of rotor resistance variation on its control performance, on the basis of the reactive power calculation of torque system, a novel fuzzy model reference adaptive (MRAS) identification method of rotor resistance is proposed. The reference model and adjustable model of instantaneous reactive power are derived in detail. In order to improve the identification performance of rotor resistance, a fuzzy PI adaptive law based on popov super stability theory is constructed. On this basis, a rotor resistance identifier is constructed, and it is used to on-line correct the rotor resistance parameter in the inverse system mathematical model of a BL-IM system. Based on the inverse decoupling control system of a BL-IM, the simulation experimental analysis and verification are carried out. The simulation experimental results have shown that when the proposed identification method of rotor resistance is used, not only the identification- and tracking-speed of rotor resistance can be effectively improved, but also the identification accuracy of rotor resistance can be improved; as for the BL-IM system, after the rotor resistance parameter is on-line corrected, not only the inverse dynamic decoupling control performance can be effectively improved, but also the robustness of BL-IM system to the variation of rotor resistance parameters can be improved.

Speed-Sensorless Vector Control of an Induction Generator Including Stray Load and Iron Losses and Online Parameter Tuning

Field-oriented control (FOC) is standardly used in high-performance induction machine (IM) applications. However, the performance of FOC algorithms strongly depends on the level of agreement between the actual IM and the respective model used for the algorithm design. IM parameters' values are known to vary with the operating conditions, so their online identification is preferable. In addition, it is often preferred to acquire the rotor speed by estimation because speed sensors increase the cost and size of the system while reducing its reliability. Model-reference-adaptive-system (MRAS) estimators are popular due to their simple implementation, but they are sensitive to IM parameters and, hence, usually include a parameter tuning mechanism. This article proposes an indirect rotor-field-oriented controller with the parallel MRAS speed estimation and IM parameter tuning - implemented in an induction generator system. Both the control algorithm and the MRAS include the stray load and iron losses, magnetic saturation, and rotor resistance variation, whereas the MRAS additionally accounts for variations of the stator and stray-load resistances. The system performance is experimentally evaluated over wide ranges of the IM flux, speed, torque, and temperature.

A robust control of a class of induction motors using rough type-2 fuzzy neural networks

In this paper, a new adaptive control method is presented for a class of induction motors. The dynamics of the system are assumed to be unknown and also are perturbed by some disturbances such as variation of load torque and rotor resistance. A type-2 fuzzy system based on rough neural network (T2FRNN) is proposed to estimate uncertainties. The parameters of T2FRNN are adjusted based on the adaptation laws which are obtained from Lyaponuv stability analysis. The effects of the uncertainties and the approximation errors are compensated by the proposed control method. Simulation results verify the good performance of the proposed control method. Also a numerical comparison is provided to show the effectiveness of the proposed fuzzy system.

Model-Based Field-Oriented Control of a Three-Phase Induction Motor with Consideration of Rotor Resistance Variation

The paper represents a model based three-phase induction motor underlying field oriented control (FOC) system that receives updated values of the rotor resistance from a proposed mathematical model intended to estimate the rotor’s resistance based on the induction motor’s performance. The rotor’s resistance value is a paramount parameter in the field-orientation equations that control three-phase induction motors. This resistance value is subject to continuous variation due to temperature variation of the motor; hence, it has to be either estimated or computed using a mathematical model to guarantee the solidity of the field-oriented control (FOC) and its accuracy. Therefore, there is an urgent demand to develop a mathematical model to update the implication of the rotor’s resistance value for inclusion in the whole motoring process in time-based simulations. The proposed mathematical model depends on temperature variation of the rotor’s windings as well as on the convective heat transfer model. The proposed model has been implemented on an FOC controlled induction motor using Matlab/Simulink for validation. The results obtained illustrate the effects imposed by the rotor’s resistance variation on the performance and integrity of the induction motor.