Model predictive MRAS estimator for sensorless induction motor drives

Ph. D. ThesisThe project presents a novel model predictive reference adaptive system (MRAS) speed observer for sensorless induction motor drives applications. The proposed observer is based on the finite control set-model predictive control principle. The rotor position is calculated using a search-based optimization algorithm which ensures a minimum speed tuning error signal at each sampling period. This eliminates the need for a proportional integral (PI) controller which is conventionally employed in the adaption mechanism of MRAS observers. Extensive simulation and experimental tests have been carried out to evaluate the performance of the proposed observer. Both the simulation and the experimental results show improved performance of the MRAS scheme in both open and closed-loop sensorless modes of operation at low speeds and with different loading conditions including regeneration. The proposed scheme also improves the system robustness against motor parameter variations and increases the maximum bandwidth of the speed loop controller. However, some of the experimental results show oscillations in the estimated rotor speed, especially at light loading conditions. Furthermore, due to the use of the voltage equation in the reference model, the scheme remains sensitive, to a certain extent, to the variations in the machine parameters. Therefore, to reduce rotor speed oscillations at light loading conditions, an adaptive filter is employed in the speed extraction mechanism, where an adaptation mechanism is proposed to adapt the filter time constant depending on the dynamic state of the system. Furthermore, a voltage compensating method is employed in the reference model of the MP-MRAS observer to address the problems associated with sensitivity to motor parameter variation. The performance of the proposed scheme is evaluated both experimentally and by simulation. Results confirm the effectiveness of the proposed scheme for sensorless speed control of IM drives

Investigation on SVM-Backstepping sensorless control of five-phase open-end winding induction motor based on model reference adaptive system and parameter estimation

This paper deals with a new control technique applied to five-phase induction motor under open-end stator winding (FPIM-OESW) topology using the backstepping nonlinear control. The main objective is to improve the dynamics of this kind of machine, which is intended to be used in high power industrial application, where the maintenance is difficult and the fault tolerant is needed to ensure the continuous motor operating mode with minimized number of interruption. This control technique is combined with the Space Vector Pulse Width Modulation (SVPWM) to maintain a fixed switching frequency. In addition, the Model Reference Adaptive System (MRAS) concept is used for the estimation of the load torque, the rotor flux and the rotor speed to overcome the main drawbacks presented with the previous sensorless systems concepts. However, the great sensitivity to the changes of the motor internal parameters and it operating instability problems, especially in low-speed operating region, that causes an estimation error of the rotor speed, is the most disadvantage of the MRAS technique. Therefore, to solve this problem, an estimation method of the motor internal parameters such as the rotor resistance, the stator resistance and the magnetizing inductance, is proposed in this paper. Where, the main aim is to improve furthermore the control performance, to reduce the computational complexity and to minimize the rotor speed estimation error. The obtained simulation results confirm the enhanced performance and the clear efficacy of the proposed control technique under a variety of cases of different operating conditions. - 2019 Karabuk UniversityScopu

Dynamic Performance Analysis of a Five-Phase PMSM Drive Using Model Reference Adaptive System and Enhanced Sliding Mode Observer

This paper aims to evaluate the dynamic performance of a five-phase PMSM drive using two different observers: sliding mode (SMO) and model reference adaptive system (MRAS). The design of the vector control for the drive is firstly introduced in details to visualize the proper selection of speed and current controllers’ gains, then the construction of the two observers are presented. The stability check for the two observers are also presented and analyzed, and finally the evaluation results are presented to visualize the features of each sensorless technique and identify the advantages and shortages as well. The obtained results reveal that the de-signed SMO exhibits better performance and enhanced robustness compared with the MRAS under different operating conditions. This fact is approved through the obtained results considering a mismatch in the values of stator resistance and stator inductance as well. Large deviation in the values of estimated speed and rotor position are observed under MRAS, and this is also accompanied with high speed and torque oscillations

A novel sensorless control for multiphase induction motor drives based on singularly perturbed sliding mode observer-experimental validation

This paper aims to develop an innovative sensorless control approach for a five-phase induction motor (IM) drive. The operation principle of the sensorless scheme is based on the sliding mode theory, within which a sliding mode observer (SMO) estimates the speed and rotor resistance simultaneously. The operation methodology of the proposed control technique is formulated using the mathematical model of the machine and the two-time-scale approach. The observation technique offers a simple and robust solution of speed and rotor resistance estimation for the sensorless control approach of the multiphase drive. The paper considers the five-phase induction motor (IM) as a case study; however, the proposed control algorithm can be employed by different types of multiphase machines. To test the applicability of the proposed sensorless control approach, the drive performance is firstly validated using MATLAB/Simulink-based simulation. Then, the simulation results are verified using real-time simulation and experimentally using TMS320C32 DSP-based control board. The obtained results confirm and validate the ability of the proposed control procedure in achieving a robust dynamic performance of the drive against the system uncertainties such as parameter variation.This research was supported by department of electrical engineering and computer science, Khalifa University, Abu Dhabi 127788, UAE.Scopu

Closed-Loop Drive Detection and Diagnosis of Multiple Combined Faults in Induction Motor Through Model-Based and Neuro-Fuzzy Network Techniques

In this paper, a fault detection and diagnosis approach adopted for an input-output feedback linearization (IOFL) control of induction motor (IM) drive is proposed. This approach has been employed to detect and identify the simple and mixed broken rotor bars and static air-gap eccentricity faults right from the start its operation by utilizing advanced techniques. Therefore, two techniques are applied: the model-based strategy, which is an online method used to generate residual stator current signal in order to indicate the presence of possible failures by means of the sliding mode observer (SMO) in the closed-loop drive. However, this strategy is not able to recognise the fault types and it can be affected by the other disturbances. Therefore, the offline method using the multi-adaptive neuro-fuzzy inference system (MANAFIS) technique is proposed to identify the faults and distinguish them. However, the MANAFIS required a relevant database to achieve satisfactory results. Hence, the stator current analysis based on the HFFT combination of the Hilbert transform (HT) and Fast Fourier transform (FFT) is applied to extract the amplitude of harmonics due to defects occur and used them as an input data set for the MANFIS under different loads and fault severities. The simulation results show the efficiency of the proposed techniques and its ability to detect and diagnose any minor faults in a closed-loop drive of IM

Induction Motors

AC motors play a major role in modern industrial applications. Squirrel-cage induction motors (SCIMs) are probably the most frequently used when compared to other AC motors because of their low cost, ruggedness, and low maintenance. The material presented in this book is organized into four sections, covering the applications and structural properties of induction motors (IMs), fault detection and diagnostics, control strategies, and the more recently developed topology based on the multiphase (more than three phases) induction motors. This material should be of specific interest to engineers and researchers who are engaged in the modeling, design, and implementation of control algorithms applied to induction motors and, more generally, to readers broadly interested in nonlinear control, health condition monitoring, and fault diagnosis

Development and Implementation of Some Controllers for Performance Enhancement and Effective Utilization of Induction Motor Drive

The technological development in the field of power electronics and DSP technology is rapidly changing the aspect of drive technology. Implementations of advanced control strategies like field oriented control, linearization control, etc. to AC drives with variable voltage, and variable frequency source is possible because of the advent of high modulating frequency PWM inverters. The modeling complexity in the drive system and the subsequent requirement for modern control algorithms are being easily taken care by high computational power, low-cost DSP controllers. The present work is directed to study, design, development, and implementation of various controllers and their comparative evaluations to identify the proper controller for high-performance induction motor (IM) drives. The dynamic modeling for decoupling control of IM is developed by making the flux and torque decoupled. The simulation is carried out in the stationary reference frame with linearized control based on state-space linearization technique. Further, comprehensive and systematic design procedures are derived to tune the PI controllers for both electrical and mechanical subsystems. However, the PI-controller performance is not satisfactory under various disturbances and system uncertainties. Also, precise mathematical model, gain values, and continuous tuning are required for the controller design to obtain high performance. Thus, to overcome these drawbacks, an adapted control strategy based on Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller is developed and implemented in real-time to validate different control strategies. The superiority of the proposed controller is analyzed and is contrasted with the conventional PI controller-based linearized IM drive. The simplified neuro-fuzzy control (NFC) integrates the concept of fuzzy logic and neural network structure like conventional NFC, but it has the advantages of simplicity and improved computational efficiency over conventional NFC as the single input introduced here is an error instead of two inputs error and change in error as in conventional NFC. This structure makes the proposed NFC robust and simple as compared to conventional NFC and thus, can be easily applied to real-time industrial applications. The proposed system incorporated with different control methods is also validated with extensive experimental results using DSP2812. The effectiveness of the proposed method using feedback linearization of IM drive is investigated in simulation as well as in experiment with different working modes. It is evident from the comparative results that the system performance is not deteriorated using proposed simplified NFC as compared to the conventional NFC, rather it shows superior performance over PI-controller-based drive. A hybrid fuel cell (FC) supply system to deliver the power demanded by the feedback linearization (FBL) based IM drive is designed and implemented. The modified simple hybrid neuro-fuzzy sliding-mode control (NFSMC) incorporated with the intuitive FBL substantially reduces torque chattering and improves speed response, giving optimal drive performance under system uncertainties and disturbances. This novel technique also has the benefit of reduced computational burden over conventional NFSMC and thus, suitable for real-time industrial applications. The parameters of the modified NFC is tuned by an adaptive mechanism based on sliding-mode control (SMC). A FC stack with a dc/dc boost converter is considered here as a separate external source during interruption of main supply for maintaining the supply to the motor drive control through the inverter, thereby reducing the burden and average rating of the inverter. A rechargeable battery used as an energy storage supplements the FC during different operating conditions of the drive system. The effectiveness of the proposed method using FC-based linearized IM drive is investigated in simulation, and the efficacy of the proposed controller is validated in real-time. It is evident from the results that the system provides optimal dynamic performance in terms of ripples, overshoot, and settling time responses and is robust in terms of parameters variation and external load

Investigation of traction motor control systems for electric vehicle applications.

Masters Degree. University of KwaZulu-Natal, Durban.Electric vehicles are a promising solution to the current pollution and greenhouse gas issues faced by the transport sector. As such, the traction motor control system of an electric vehicle is worthy of investigation. Direct torque and indirect field-oriented control are commonly applied control techniques, enabling advanced control of the induction and permanent magnet synchronous motors currently used in most electric vehicles being produced. Various improvements have been made to current traction motor control schemes to reduce ripple, improve parameter insensitivity, and increase powertrain efficiency. Consequently, the objective of the research conducted is to contribute to the field of electric vehicle powertrains through comprehensive investigations into the suitability and performance of direct torque and indirect field-oriented control in the traction motor control system of an electric vehicle. A four-stage simulation-based investigation was undertaken, with five motor control techniques initially assessed, which were conventional direct torque and field-oriented control, two space vector modulation-based direct torque control systems and fuzzy logic-based direct torque control. Results from the first stage of the simulation-based study highlighted expected issues with conventional direct torque control and showed that fuzzy logic-based direct torque control and space vector modulational-based direct torque control with closed-loop torque and flux control present promising solutions for use in the traction motor control system of an electric vehicle. Extensions of the simulation-based investigation in stages two and three included the integration and assessment of field-weakening control and sensorless speed estimation. Furthermore, stage four concluded the investigation with an essential analysis of a complete control mechanism in realistic urban and highway driving conditions. The fourth stage utilised sections of the New York City Cycle and Highway Fuel Economy Test cycle, with a simulated vehicle load. The complete study indicated that space vector modulation-based direct torque control with closed-loop torque and flux control performs suitably for electric vehicle applications, providing favourable speed, torque, current and stator flux results with a faster computation time than some comparable control options. The comprehensive investigation extends current literature and forms a basis for further investigation in the field of traction motor control systems for electric vehicle applications

Speed Sensorless Induction Motor Drive Control for Electric Vehicles

Fast diminishing fossil fuel resources, deterioration in air quality and concerns for environmental protection, continuously promote the interest in the research and development of Alternative Energy Vehicles (AEVs). Traction motor drive is an integral part and common electric propulsion system in all kinds of AEVs. It plays an utmost significant role in the development of electrified transport industry. Application of Induction Motor (IM) drive is not only limited to the domestic and industrial applications but also has an ubiquitous influence in the modern electrified transport sector. IM is characterized by a simple and rugged structure, operational reliability, low maintenance, low cost, ability to operate in a hostile environment and high dynamic performance. However, IM is one of the widely accepted choices by Electric Vehicles (EVs) manufacturer. At present, Variable speed IM drive is almost replacing the traditional DC motor drive in a wide range of applications including EVs where a fast dynamic response is required. It became possible after the technological advancement and development in the field of power switching devices, digital signal processing and recently intelligent control systems have led to great improvements in the dynamic performance of traction drives. Speed Sensorless control strategies offer better system’s reliability and robustness and reduce the drive cost, size and maintenance requirements. Sensorless IM drives have been applied on medium and high speed applications successfully. However, instability at low speed and under different load disturbance conditions are still a critical problem in this research field and has not been robustly achieved. Some application such as traction drives and cranes are required to maintain the desired level of torque down to low speed levels with uncertain load torque disturbance conditions. Speed and torque control is more important particularly in motor-in-wheel traction drive train configuration EVs where vehicle wheel rim is directly connected to the motor shaft to control the speed and torque. The main purpose of this research is to improve the dynamic performance of conventional proportional-integral controller based model reference adaptive system (PI-MRAS) speed observer by using several speed profiles under different load torque disturbance conditions, which is uncertain during the whole vehicle operation apart from the vehicle own load. Since, vehicle has to face different road conditions and aerodynamic effects which continuously change the net load torque effect on the traction drive. This thesis proposes different novel methods based on the fuzzy logic control (FLC) and sliding mode control (SMC) with rotor flux MRAS. Numerous simulations and experimental tests designed with respect to the EV operation are carried out to investigate the speed estimation performance of the proposed schemes and compared with the PI-MRAS speed observer. For simulation and experimental purpose, Matlab-Simulink environment and dSPACE DS-1104 controller board are used respectively. The results presented in this thesis show great performance improvements of the proposed schemes in speed estimation & load disturbance rejection capability and provide a suitable choice of speed sensoless IM drive control for EVs with cost effectiveness

Stability Analysis and Robust Controller Design of Indirect Vector Controlled Induction Motor

The thesis considers stability analysis and controller design through different performance measures for indirect vector controlled induction motor (IVCIM).These problems are known to be complex due to nonlinearity, large order and multi-loop scenario. Some new approaches and results on IVCIM are proposed in this work. IVCIM dynamics is well known for having different bifurcation behavior, viz., saddle-node, Hopf, Bogdanov–Takens and Zero–Hopf bifurcations due to rotor resistance variation. These bifurcations affect the control performance and may lead to stalling or permanent damage of motor. A numerical analysis of these bifurcations for proportional integral (PI) controlled IVCIM is made in this thesis using full-order induction motor model (stator dynamics is included). This analysis aids to determine the allowable bifurcation parameter variation range as well as suitable choice of speed-loop gains to avoid these. Some new observations on the bifurcation behavior are made. Simulation and experimental results are presented validating the bifurcation behaviors. For improving dynamic performance in the presence of load torque and rotor resistance variation, a new method for designing PI gains is proposed for IVCIM. The inner-loop current PI controllers are tuned simultaneously along with the speed controller. This method is implemented using a static output feedback scheme in which iterative linear matrix inequality (ILMI) based∞control technique is employed. Such a design makes stator currents and speed response to be robust against rotor resistance and load variations. A comparison between proposed design and a conventional one is shown using simulation and experimental results that validate the superiority of the proposed approach. Owing to multi-loop and nonlinear system behavior, IVCIM dynamics is known to have coupling in between the two inner-loop stator current components (flux and torque). Such coupling affects the dynamic torque output of the motor. Decoupling of the stator currents are important for smoother torque response of IVCIM. Conventionally, additional feedforward decoupler is used to take care of the coupling that requires exact knowledge of the motor parameters and additional circuitry or signal processing. A method is proposed to design the regulating PI gains while minimizing coupling without any requirement of additional decoupler. The variation of the coupling terms for change in load torque is considered as the performance measure. The same ILMI based∞control design approach is used to obtain the controller gains. A comparison between the conventional feedforward decoupling and proposed decoupling scheme is presented through simulation and experimental results that establish the effectiveness of the proposed method riding over its simplicity. Finally, since the PI controller can yield limited performance, a dynamic controller is designed for the IVCIM drive system. In the design process, iron-loss dynamics are incorporated into induction motor model to fetch benefit through better performance. A sequential design method is used for the controller design in which, first, the inner-loop controllers are designed. The designed inner-loop controllers is then used for designing the outer speed-loop controller. The proposed design employs ILMI based∞control design for dynamic output feedback controller that makes stator currents and speed response to be robust against disturbances. A comparison among proposed dynamic controller design, PI controller and compensator design is shown using simulation and experimental results demonstrate enhanced performance of the proposed controller and suitability for industrial purpose