Sensorless Control of PMSM using Backstepping Control and ESO-type Observer

In this paper, a sensorless speed controller is proposed for a class of systems of permanent magnet synchronous motor(PMSM). The load torque and stator resistance are as the generalized unmeasurable states. An extended state observer (ESO) is designed to estimate both the unmeasurable system speed and uncertain parameters. A new interconnected observer scheme is constructed by the Kalman filter only using the measurements of motor current and voltage. A nonlinear backstepping controller based on the observer signals is developed and the stability of the closed-loop is guaranteed. It is shown that the given control scheme has good performance for the change of the stator resistance and the load torque.

In this article is presented a sensorless control structure of the speed of a Permanent Magnet Synchronous Motor (PMSM) rotor based on the classic Field Oriented Control (FOC) strategy, where the PI outer speed loop controller in the classical approach supplies the current reference i <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">qref</sub> for a Synergetic controller, which supplies the output controls u <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sub> and u <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</sub> for the PMSM control. The synergetic control is considered as a generalization for the Sliding Mode Control (SMC). Among the remarkable properties of this type of design of control are the decoupling procedure and a reduced order model for the controller. The PMSM operating equations, fractional order calculus elements and a Sliding Mode Observer (SMO) type speed observer of are presented herein. By replacing the Synergetic current controller with a Fractional Order (FO) Synergetic current controllers, superior performance is achieved due to the use of the fractional calculus.

In the permanent magnetic synchronous motor (PMSM) system with active disturbance rejection controller (ADRC), the estimation accuracy of extended state observer (ESO) will decrease when the ADRC does not depend on the system model completely. In order to improve the estimation accuracy, this paper proposes an improved ADRC approach by adding a model compensation term. Furthermore, the rotor inertia and viscous friction coefficient in the model compensation term is identified by the model reference adaptive identification (MRAI) algorithm. The load torque is estimated according to the mechanical equation of PMSM system. Then the identification values of rotor inertia, viscous friction coefficient, and load torque make up the compensation term of the ESO. Simulation results indicate that this improved ADRC approach has the better parameter robustness and anti-load-disturbance performance.

This paper compares some sensorless Permanent Magnet Synchronous Motor (PMSM) controls for driving an electric vehicle in terms of operating speed. Sensorless control is a type of control method in which sensors, such as speed and position sensors, are not used to measure controlled variables. The controlled variable value is estimated from the stator current measurement. Sensorless control performance is not as good as a sensor-based system. This paper aims are to recommend a control method for the PMSM sensorless controls that would be used to drive an electric vehicle. The methods that we will discuss are divided into four categories based on the operation speed area. They are a startup, low speed, high speed, and low and high-speed areas. The low and high-speed area will be divided into with and without switching. If PMSM more work at high speed, the most speed area that is used, we prefer to choose the method that works at high speed, that is, the modification or combination of two or more conventional methods.

The field-oriented control (FOC) strategy of a permanent magnet synchronous motor (PMSM) in a simplified form is based on PI-type controllers. In addition to their low complexity (an advantage for real-time implementation), these controllers also provide limited performance due to the nonlinear character of the description equations of the PMSM model under the usual conditions of a relatively wide variation in the load torque and the high dynamics of the PMSM speed reference. Moreover, a number of significant improvements in the performance of PMSM control systems, also based on the FOC control strategy, are obtained if the controller of the speed control loop uses sliding mode control (SMC), and if the controllers for the inner control loops of id and iq currents are of the synergetic type. Furthermore, using such a control structure, very good performance of the PMSM control system is also obtained under conditions of parametric uncertainties and significant variations in the combined rotor-load moment of inertia and the load resistance. To improve the performance of the PMSM control system without using controllers having a more complicated mathematical description, the advantages provided by reinforcement learning (RL) for process control can also be used. This technique does not require the exact knowledge of the mathematical model of the controlled system or the type of uncertainties. The improvement in the performance of the PMSM control system based on the FOC-type strategy, both when using simple PI-type controllers or in the case of complex SMC or synergetic-type controllers, is achieved using the RL based on the Deep Deterministic Policy Gradient (DDPG). This improvement is obtained by using the correction signals provided by a trained reinforcement learning agent, which is added to the control signals ud, uq, and iqref. A speed observer is also implemented for estimating the PMSM rotor speed. The PMSM control structures are presented using the FOC-type strategy, both in the case of simple PI-type controllers and complex SMC or synergetic-type controllers, and numerical simulations performed in the MATLAB/Simulink environment show the improvements in the performance of the PMSM control system, even under conditions of parametric uncertainties, by using the RL-DDPG.

The objective of this paper is to control the speed of Permanent Magnet Synchronous Motor (PMSM) over wide range of speed by consuming minimum time and low cost. Therefore, comparative performance analysis of PMSM on basis of speed regulation has been done in this study. Comparison of two control strategies i.e. Field oriented control (FOC) without sensor less Model Reference Adaptive System (MRAS) and FOC with sensor less MRAS has been carried out. Sensor less speed control of PMSM is achieved by using estimated speed deviation as feedback signal for the PI controller. Performance of the both control strategies has been evaluated in in MATLAB Simulink software. Simulation studies show the response of PMSM speed during various conditions of load and speed variations. Obtained results reveal that the proposed MRAS technique can effectively estimate the speed of rotor with high exactness and torque response is significantly quick as compared to the system without MRAS control system.

In order to optimize the speed-control performance of the permanent-magnet synchronous motor (PMSM) system with different disturbances and uncertainties, a nonlinear speed-control algorithm for the PMSM servo systems using sliding-mode control (SMC) and load torque compensation techniques is developed in this paper. A SMC strategy is designed based on field oriented control (FOC) theory, which is adopted in the speed loop of PMSM system. Meanwhile, considering the SMC need providing large gain to restrain disturbances resulting in large chattering, an adaptive extended sliding mode torque observer (ESMO) is proposed to estimate and compensate load torque. Through torque estimation for feed-forward compensation, one new composite SMC algorithm has been proposed to take a smaller value of switching gain without large chattering. The control scheme is verified by comprehensive simulation and experimental results.

Direct Torque Control (DTC) of Permanent Magnet Synchronous Motor (PMSM) has quick response and simple structure, but it has the disadvantages of large torque ripples and inconstant switching frequency. An improved DTC method of PMSM based on backstepping control is proposed in this paper. For direct torque control, speed, torque and flux linkage are selected as virtual state variables and then a backstepping controller is designed to produce reference stator voltage components. Then according to those voltage components, space vector modulation (SVM) is used to produce switching states of inverters. Simulation results show that the performance of the proposed DTC system has been dramatically improved. Compared to the traditional DTC, the proposed DTC based on backstepping control could effectively decrease flux and torque ripples, make inverters have constant switching frequency. Compared to the DTC based on PI control, the backstepping DTC has fewer adjusted parameters and has good dynamic performance and good robustness.

Permanent magnet synchronous motors (PMSMs) are increasingly used in high performance variable speed drives of many industrial applications. PMSM has many features, like high efficiency, compactness, high torque to inertia ratio, rapid dynamic response, simple modeling and control, and maintenance free operation. Presence of position sensors presents several disadvantages, such as reduced reliability, susceptibility to noise, additional cost and weight and increased complexity of the drive system. For these reasons, the development of alternative indirect methods for speed and position control becomes an important research topic. Advantages of sensorless control are reduced hardware complexity, low cost, reduced size, cable elimination, increased noise immunity, increased reliability and decreased maintenance. The key problem in sensorless vector control of ac drives is the accurate dynamic estimation of the stator flux vector over a wide speed range using only terminal variables (currents and voltages). The difficulty comprises state estimation at very low speeds where the fundamental excitation is low and the observer performance tends to be poor. Moreover, the noises of system and measurements are considered other main problems. This paper presents a comprehensive study of the different sliding mode observer methods of speed and position estimations for sensorless control of PMSM drives.

With the widespread application of permanent magnet synchronous motors (PMSMs), drive control technology for these motors has gradually become a focal point of research. To overcome the drawbacks associated with installing separate sensors, sensorless drive control technology has attracted significant attention. This paper presents a sensorless flux linkage estimation method for permanent magnet synchronous motors (PMSMs) utilizing a nonlinear observer. In the absence of a position sensor, this method employs a Nonlinear Extended State Observer (ESO) along with advanced flux linkage techniques to accurately estimate the stator flux linkage. By integrating a voltage-current hybrid model, the approach facilitates adaptive switching between the voltage and current models, effectively addressing issues such as DC offset and integrator saturation that are common in first-order integration of the voltage model. Furthermore, the Nonlinear Extended State Observer is utilized to estimate and compensate for noise and disturbances in the voltage model, ensuring precise determination of the stator flux linkage during motor operation. Finally, a phase-locked loop (PLL) is implemented to estimate the rotor angle and speed, thereby enhancing the accuracy of these estimations and improving the overall performance of sensorless control in PMSMs.

This paper proposes a robust optimal nonlinear control with an observer to reject the offset errors of position tracking for surface mounted permanent magnet synchronous motors. We provide the control method to reject offset errors and load torque for designing field oriented control (FOC) based the alternating current (AC) frame. The proposed method consists of a torque generator, a commutation scheme, an electrical controller, and a load torque observer. The mechanical controller is designed to compensate for load torque and the offset error and generate the desired torque. The commutation scheme is proposed to create the desired currents for the desired torque. The electrical controller is developed to guarantee the desired currents. The observer is designed to estimate both the velocity and the load torque. In order to obtain the robustness to parameter uncertainties and a gain tuning guide, the linear quadratic regulator method is applied to the proposed method. The closed-loop stability is proven. A detailed process for the FOC design and an analysis of the control methods based on the AC frame are presented. The performance of the proposed method was validated via experiments. The proposed method obtains the FOC based on the AC frame. Furthermore, the position tracking performance of the proposed method is superior to that of the conventional method.

This paper deals with the performance analysis of the field oriented control (FOC) of permanent magnet synchronous motor (PMSM) drive with a PID (proportional plus integral plus derivative) in DC link voltage control and fuzzy PID for speed control in closed loop operation. A mathematical model of the PMSM drive has been developed by considering each accessories of the model to analyze both the steady state and transient performances of the PMSM drive system. The current controlled inverter feeding power to the PMSM motor is powered from a PWM current controlled converter. The advantages of the integrated PMSM drive are demonstrated. The PID voltage control takes care of the constant DC link voltage to feed the inverter. The fuzzy controller provides a better response to the drive system specially in the steady state condition. The state space model developed in terms of derivatives of winding currents, DC link voltage, supply currents, rotor speed, and rotor position are simulated to obtain the required information. The study also examines the effectiveness of the PMSM drive under steady state and transient conditions for different parameter variation.

In order to estimate the vibration and acoustic noise in a permanent magnet (PM) synchronous motor, the natural frequencies of the stator structure should be determined during the design stage. In this paper, analytical formulas to predict the natural frequencies of the stator are derived. The analytical model of the stator includes stator teeth, winding, stator core, and stator case. It is observed that the natural frequencies calculated with the integrated components exceed those based on the stator core alone only. In order to verify this analytical model, numerical simulation and experimental measurement are carried out using a PM synchronous motor which has 5 pole-pairs and 12 slots structure configuration. Good agreements are observed among the results obtained by analytical formula, simulation and experiment.

Model reference adaptive system (MRAS) is one of the popular methods to observe the speed and the angle information of the Permanent magnet synchronous motor (PMSM). This paper proposes a new adaptation scheme for MRAS to replace the conventional PI controller based on Popov Hyperstability theorem. In this project, the speed of PMSM is controlled by using field oriented control (FOC) method and the MRAS is used to observe the speed and the rotor position of the motor. The reference model for the MRAS is the PMSM itself while the adjustable model is the current model in the rotor reference frame. The Sugeno Fuzzy Logic Inference System (FIS) is implemented in the adaptation scheme in order to tune the error between the reference and the adjustable model. The new proposed method shows it is capable to track the motor speed efficiently at wide range of operating speeds.

This study compares Field-Oriented Control (FOC) and trapezoidal control techniques for Permanent Magnet Synchronous Motors (PMSMs) in modern industrial variable-speed applications. Traditionally, variable-speed applications have relied on DC machines, which have inherent drawbacks such as increased maintenance, spark losses, higher inertia, and overall higher costs. This FOC has emerged as a sophisticated method that enables independent control of torque and magnetization flux in AC motors, allowing for precise regulation of torque and speed tailored to the motor's electromagnetic state. FOC leverages Sinusoidal Pulse-Width Modulation (SPWM) and Space Vector Pulse Width Modulation (SVPWM) techniques to enhance DC voltage utilization and minimize switching and harmonic losses. In contrast, the paper presents a detailed model of a PMSM drive system based on electronic components rather than standard mathematical blocks, leading to more realistic simulation results. All simulation modules, including the inverter and PWM generator, were custom-built, allowing for performance comparison under varying speed and torque conditions. Brushless DC (BLDC) motors, which are typically categorized as PMSMs with trapezoidal back-EMF waveforms, have gained traction due to their simplicity and cost-effectiveness. The trapezoidal control technique, also known as six-step commutation, simplifies the control process by aligning motor phase switching with the rotor position, resulting in a quasi-square-wave current. However, this method introduces torque ripple and presents control challenges, particularly in low-speed applications. Given the rising economic constraints and stringent governmental standards, there is an increasing demand for efficient, low-interference, and adaptable electrical systems. This study demonstrates that FOC provides a more robust and efficient solution for high-performance applications than the trapezoidal control technique in PMSMs.