Sensorless Control Of Permanent Magnet Synchronous Motor Research Articles

Transmission Line Modeling-Based Position Sensorless Control for Permanent Magnet Synchronous Machines

Position sensorless control has been widely used in permanent magnet synchronous motor (PMSM) drives in low-cost applications or in the fault-tolerance control of position sensors. Conventional sensorless control methods often adopt a back electromagnetic force (EMF)-based position observer, which results in bandwidth reduction in signal processing and lower estimation accuracy. This paper introduces a numerical solution based on transmission line modeling (TLM) to obtain the back EMF. The TLM method is used for the numerical calculation of electromagnetics due to the clear algorithm structure, robust convergence and stability, and easy implementation in dynamic circuit analyses. This paper first analyzes the 2D TLM method techniques. Then, a new application of TLM theory in position sensorless control of PMSMs is put forward. The proposed TLM-based sensorless control scheme can estimate the back EMF without decreasing the bandwidth, thereby enhancing the dynamic performance of the sensorless control. All numerical results are implemented using the proposed approach, which validates the effectiveness of the proposed method.

FPGA-Based High-Frequency Voltage Injection Sensorless Control with Novel Rotor Position Estimation Extraction for Permanent Magnet Synchronous Motor

This study developed a realization of sensorless control for a permanent magnet synchronous motor (PMSM) using a field-programmable gate array (FPGA). Both position and speed were estimated using a high-frequency (HF) injection scheme. Accurate estimation is essential to ensure the proper functioning of sensorless motor control. To improve the estimation accuracy of the rotor position and reduce the motor speed ripple found in conventional methods, a new extraction strategy for estimating the rotor position and motor speed is proposed. First, signal modulation compensation was applied to expand the information of the error function in order to provide more accurate data to the tracking loop system for rotor position extraction. Second, to minimize the motor speed ripple caused by the HF injection, motor speed estimation was performed after obtaining the rotor position information using a differential equation with a low-pass filter (LPF) to avoid the direct effect of the injected signal. Verified experimentally, the results showed that the rotor position error did not exceed 10 el.deg, so these methods effectively reduce the rotor position estimation error by about 30%, along with the motor speed ripple. Therefore, better performance in sensorless PMSM control can be achieved in motor control applications.

An apparent inductance online identification for sensorless control of permanent magnet synchronous motor

AbstractThe model‐based sensorless control of permanent magnet synchronous motor (PMSM) relies on the motor parameters. In practice, the considerable uncertainty of inductance and the difference between the apparent inductance and the incremental inductance exists. To overcome it, an online apparent inductance identification method for PMSM sensorless control is proposed. First, an initial incremental inductance table (IIT) is obtained offline. Then, an asymmetric high‐frequency square wave injection method is proposed to identify the incremental inductance at the operation point, and an adaptive minimum adjustment algorithm is proposed to adjust IIT automatically. Finally, the apparent inductance is calculated using the adjusted IIT. Based on it, the complete PMSM sensorless control is designed. The experimental results indicate this method is feasible and effective.

Inductance Estimation Based on Wavelet-GMDH for Sensorless Control of PMSM

In permanent magnet synchronous motor (PMSM) sensorless drive systems, the motor inductance is a crucial parameter for rotor position estimation. Variations in the motor current induce changes in the inductance, leading to core magnetic saturation and degradation in the accuracy of rotor position estimation. In systems with constant load torque, the saturated inductance remains constant. This inductance error causes a consistent error in rotor position estimation and some performance degradation, but it does not result in speed estimation errors. However, in systems with periodic load torque, the error in the saturated inductance varies, consequently causing fluctuations in both the estimated position and speed errors. Periodic speed errors complicate speed control and degrade the torque compensation performance. In this paper, we propose a wavelet denoising-group method of data handling (GMDH) based method for accurate inductance estimation in PMSM sensorless control systems with periodic load torque compensation. We present a method to analyze and filter the collected three-phase current signals of the PMSM using wavelet transformation and utilize the filtered results as inputs to GMDH for training. Additionally, a method for magnetic saturation compensation using the inductance parameter estimator is proposed to minimize periodic speed fluctuations and improve control accuracy. To replicate the load conditions and parameter variations equivalent to the actual system, experiments were conducted to measure the speed ripples, inductance variations, and torque component of the current. Finally, software simulation was performed to confirm the inductance estimation results and verify the proposed method by simulating load conditions equivalent to the experimental results.

Improvement Performances of the SMO Observer for PMSM Sensorless Control Based on DTC Strategy Using Simulated Annealing and Reinforcement Learning TD3 Agent

From the elements that contribute to increasing the reliability of the control system of a Permanent Magnet Synchronous Motor (PMSM), could be enumerated the replacement of the speed transducers with software-implemented speed observers. On this basis, this paper focuses on the sensorless regulation of a PMSM using a Direct Torque Control (DTC) type strategy, in which a speed observer is used in combination with a Reinforcement Learning-Twin Delayed Deep Deterministic Policy Gradient (RL-TD3) type agent to increase the accuracy of the PMSM rotor speed estimate. Simulated Annealing (SA) is also used to achieve superior performance of the velocity observer for optimal tuning of the PI-type velocity controller parameters. The latter can, after the training phase, provide correction signals to the speed observer so that the estimated speed is as close as possible to the estimated speed. The control structures, control algorithms, and operating equations of the PMSM, the control strategy of the DTC type, and the speed observer are presented in this paper. Numerical simulations carried out in the Matlab/Simulink programming environment validate the superiority of the PMSM rotor speed estimation performance in the case of the use of an RL-TD3-type agent in combination with a speed observer, compared to the case of the use of the speed observer alone.

An Adaptive-Gain Sliding Mode Observer with Precise Compensation for Sensorless Control of PMSM

In this paper, we propose a sensorless control strategy for permanent magnet synchronous motors (PMSMs) based on an adaptive-gain sliding mode observer (ASMO) with precise compensation. Firstly, the observer adopts a saturation function with a continuous boundary layer as the switching function to avoid the delay effect of the low-pass filter. In addition, the adaptive-gain method is designed based on a conventional sliding mode observer (SMO) with constant-gain and a saturation function. The adaptive-gain mathematical model is simplified by establishing a nonlinear feedback channel of an SMO. Secondly, in order to improve the practicability and facilitate debugging, the explicit stability condition of an ASMO is deduced according to Lyapunov’s second method. According to the proposed adaptive method, the chattering caused by the mismatch of the sliding-mode gain is suppressed, and the observable speed range is also improved. Thirdly, the position estimation delay problem of an SMO with a continuous switching function is analyzed in detail from the perspective of frequency characteristics. Then, a precise compensation method is proposed for the delay problem, which greatly improves the position estimation accuracy and the control performance. Finally, the correctness of the theory and the feasibility of the ASMO with precise compensation for the sensorless control of PMSMs are verified by experiments.

Finite Position Set-Phase-Locked Loop With Low Computational Burden for Sensorless Control of PMSM Drives

This letter proposes a novel finite position set-phase locked loop (FPS-PLL) for permanent-magnet synchronous motors (PMSMs) sensorless drives. A novel cost function is designed to combine with the dichotomy of position for ensuring the astringency of iteration. After the dichotomy of position, through adopting the Newton iteration, the accurate rotor position is obtained only by three iterations. The convergence analysis and calculation accuracy expression are given. Moreover, no parameters need to be adjusted and fast dynamic response is achieved. Compared with reported FPS-PLLs, the calculated burden is markedly reduced. Eventually, the effectiveness of proposed scheme is verified by experiments.

Improved Performance for PMSM Sensorless Control Based on the LADRC Controller, ESO-Type Observer, DO-Type Observer, and RL-TD3 Agent

Starting from the fact that in sensorless control systems of the Permanent Magnet Synchronous Motor (PMSM), the load torque can have short and significant variations, this paper presents the sensorless control of a PMSM based on a Linear Adaptive Disturbance Rejection Controller (LADRC) type controller. Essentially, the successful operation of the LADRC controller to achieve PMSM rotor speed control performance depends on a good estimation of the disturbances acting on the system. Traditionally, an Extended State Observer (ESO) is used to make such an estimate. In this paper, it is proposed to use a Disturbance Observer (DO) to estimate the external disturbances, and after their rejection, the LADRC controller ensures an equivalent global behavior of the control system with an ideal double integrator, thus increasing ease in achieving the desired control performance. Control structures and Matlab/Simulink implementation of the PMSM sensorless control system based on the LADRC controller with an ESO-/DO-type observer are presented, as is its use in tandem with a Reinforcement Learning Twin-Delayed Deep Deterministic Policy Gradient (RL-TD3) specially trained agent that provides correction signals for more accurate estimation of external disturbances and hence improved control performance. To optimize the gain value of the DO-type observer, a computational intelligence algorithm such as the Ant Colony Algorithm (ACO) is used. Qualitatively superior performance is achieved by using LADRC with the RL-TD3 agent control structure in terms of parametric robustness, response time, and steady-state error. In addition, by calculating the fractal dimension (DF) of the controlled signal and the PMSM rotor speed, it is found that the higher the DF, the better the performance of the control system. The validation of the superiority of the proposed control structures is carried out by means of numerical simulations in the Matlab/Simulink environment.

Improved Performance for PMSM Sensorless Control Based on Robust-Type Controller, ESO-Type Observer, Multiple Neural Networks, and RL-TD3 Agent.

This paper summarizes a robust controller based on the fact that, in the operation of a permanent magnet synchronous motor (PMSM), a number of disturbance factors naturally occur, among which both changes in internal parameters (e.g., stator resistance Rs and combined inertia of rotor and load J) and changes in load torque TL can be mentioned. In this way, the performance of the control system can be maintained over a relatively wide range of variation in the types of parameters mentioned above. It also presents the synthesis of robust control, the implementation in MATLAB/Simulink, and an improved version using a reinforcement learning twin-delayed deep deterministic policy gradient (RL-TD3) agent, working in tandem with the robust controller to achieve superior performance of the PMSM sensored control system. The comparison of the proposed control systems, in the case of sensored control versus the classical field oriented control (FOC) structure, based on classical PI-type controllers, is made both in terms of the usual response time and error speed ripple, but also in terms of the fractal dimension (DF) of the rotor speed signal, by verifying the hypothesis that the use of a more efficient control system results in a higher DF of the controlled variable. Starting from a basic structure of an ESO-type observer which, by its structure, allows the estimation of both the PMSM rotor speed and a term incorporating the disturbances on the system (from which, in this case, an estimate of the PMSM load torque can be extracted), four variants of observers are proposed, obtained by combining the use of a multiple neural network (NN) load torque observer and an RL-TD3 agent. The numerical simulations performed in MATLAB/Simulink validate the superior performance obtained by using properly trained RL-TD3 agents, both in the case of sensored and sensorless control.

Sensorless PMSM control system based on luenberger observer

At present, sensorless becomes a research hit for its lower cost and smaller size, among the present sensorless methods, Luenberger Observer has outstanding advantages for its dynamic performance, parameter robustness and high system stability. In this paper, the model of Luenberger Observer which is based on the state equation of permanent magnet synchronous motor (PMSM), and the changes of residence and induce which may lead to the error of the system are also analysed, in order to increase the accuracy of the system, current compensator is also added. In addition, 2 conditions which PMSM runs at low speed and high speed are analysed under the MATLAB model, the results show that the Luenberger Observer has better performance at high speed, but the noisy data of the useful signal is more at low speed.

Research on Permanent Magnet Synchronous Motor Sensorless Control System Based on Integral Backstepping Controller and Enhanced Linear Extended State Observer

The traditional sensorless control system of permanent magnet synchronous motor (PMSM) has the problems of low estimation accuracy and poor anti-interference ability. Moreover, the position estimation performance is subjected to position harmonic ripples caused by inverter nonlinearities and flux spatial harmonics. To optimize the dynamic performance of the PMSM sensorless control system, this paper proposes a sensorless control scheme that combines integral backstepping control with enhanced linear extended state observer (ELESO). The ELESO consists of two linear extended state observers (LESOs), which estimate the internal and external disturbances of the system, to improve the estimation accuracy of rotor position. Then, the integral backstepping controller processes the estimated rotor position and speed information to obtain d and q-axis voltages. The sensorless control scheme is implemented in the Matlab/Simulink and verified by experiments. The simulation and experiment show that the scheme can effectively suppress load interference and improve control accuracy.

Hybrid sensorless control of PMSM in full speed range using HFI and back-EMF

The permanent magnet synchronous motors (PMSM) are more and more used because of their high performance compared with other AC motors. The present paper proposes a hybrid controller which consists of a high frequency injection estimator and a back-electromotive-force observer in full speed range for the sensorless control of PMSM. The aim objective of the study to prevent speed overshot in startup time of the motor and provides a better dynamic response in transient and permanent states using this structure. A hybrid algorithm is applied to realize a smooth transition from low to high speed. At standstill and very low speed region, HF injection technique is used to detect the rotor initial position. In this first step study, the position estimation is derived from a HF current injection by using only one filter. When the rotor speed goes up to a certain value where back-EMF can provide adequate information, a back-EMF observer will dominate. Thanks to this structure, the mechanical sensor can be engaged using the best estimates and the developed control method is fast, simple, and flexible. The effectiveness, superiority, and performance of the proposed control method and extensive simulation results are provided on a 1 kW permanent magnet synchronous motor drive, demonstrating the expected performances.

Position Sensorless Control for PMSM Drives With Single Current Sensor

The aim of this article is an attempt to provide a more credible control mode or a fault-tolerant control strategy for permanent magnet synchronous motor (PMSM) drives when an unexpected failure occurs to the current or position sensor. Considering that, a position sensorless control method that uses only one current sensor is proposed. Different from a traditional position sensorless control scheme that utilizes additional current sensors to obtain information of multiple phase currents, only a single current sensor (SCS) arranged on one of the current branches is included among the whole control circuit. Three-phase currents are reconstructed by sequentially sampling the SCS under specific voltage vectors, and directly employed for motor position estimation. A nonlinear position observer established according to the gradient descent is adopted. Focusing on the special current-acquisition pattern in this article, a step-size optimization method based on golden section search is proposed to minimize position estimation error. The experimental results reveal that the method in this article is comparable to the traditional full-current-sensor method in terms of position estimation, which confirms the fault-tolerant capability as one certain sensor of the control structure malfunctions.

Second-Order ESO-Based Current Sensor Fault-Tolerant Strategy for Sensorless Control of PMSM With B-Phase Current

Usually, two-phase current sensors are required to realize sensorless control of permanent magnet synchronous motor (PMSM). However, once the phase current sensor fails, the whole system will not work. In this article, a novel second-order extended state observer (SO-ESO) based current sensor fault-tolerant strategy for realizing PMSM sensorless control and multiparameter identification is proposed, which can significantly improve the system reliability. When a fault occurs in the A-C two-phase current sensor, the proposed scheme uses only a B-phase current sensor to estimate the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> - <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">q</i> axis stator current and time varying resistance, achieving a high-performance sensorless control function. In order to reduce the chattering of the system, a sigmoid function is introduced in the SO-ESO. In addition, an SO-ESO based parallel speed and multiparameter identification scheme are proposed by using two model reference adaptive system observer (MRASO). The first MRASO is designed based on super twisting algorithm with a corrective feedback loop and is used for estimating rotor speed and position. The second MRASO only needs to identify inductance and permanent flux because the stator resistance is estimated by SO-ESO. The second MRASO and SO-ESO updates the three identified electrical parameters (i.e., stator resistance, inductance, and permanent flux) and estimated currents to the first MRASO to achieve high robustness sensorless control. The relevant results show that the scheme gives good results, and the system has good dynamic performance and better fault tolerance.

A novel nonsingular fast terminal sliding mode observer combining I‐F method for wide‐speed sensorless control of PMSM drives

AbstractBased on the consideration of optimizing speed piecewise and transitioning smoothly, a hybrid position sensorless control strategy integrating with a novel nonsingular fast terminal sliding mode observer (NFTSMO) and the current‐frequency (I‐F) control method for surface‐mounted permanent magnet synchronous motor (PMSM) is proposed in this paper. In zero‐low speed regions, the I‐F control method is employed for starting steadily and possessing the ability of anti‐interference. In middle‐high speed regions, an improved sliding mode observer (SMO) based on a novel nonsingular fast terminal sliding surface is designed for the closed‐loop sensorless operation. Making use of the novel sliding surface, not only the estimated errors of rotor position caused by the conventional sliding surface can be eliminated effectively with a faster rate of convergence to improve the stability of system, but also the chattering of the estimated back EMF can be restrained by the sigmoid function. Meanwhile, the phase‐locked loop is utilized to lessen the burden of calculation and phase delay. Furthermore, a transition function is designed so as to fulfill the smooth transition between two different control ideologies. The effectiveness of the proposed hybrid sensorless control strategy for both dynamic and steady state operations during wide‐speed region is verified by simulation and experimental analyses.

A Comparative Study and Optimization of Switching Functions for Sliding-Mode Observer in Sensorless Control of PMSM

The sensorless control of the permanent magnet synchronous motor (PMSM) has attracted wide attention due to its high reliability, economic and safety benefits. A fast and high-precision rotor-position estimation is inevitable for the implementation of sensorless control. Sliding-mode observer (SMO) is a preferred solution for sensorless control by many industrial companies. This article addresses the comparison of different switching functions employed in the control structure of sensorless field-oriented control with SMO. The switching functions are classified and their influence on the performance of the PMSM is verified for different shaping coefficients (SC). In addition, a statistical evaluation of the switching functions is provided to find the optimal values of SC. An experimental and statistical evaluation validated the substitutability of signum and hyperbolic switching functions and optimal values of SC have been found.

Improvement of PMSM Sensorless Control Based on Synergetic and Sliding Mode Controllers Using a Reinforcement Learning Deep Deterministic Policy Gradient Agent

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.

Sensorless Control of PMSM in Low Speed Region Using HF Pulse Signal Injection Method

Abstract The sensorless control of the permanent magnet synchronous motor (PMSM) has attracted wide attention due to its economic and safety benefits. A fast and high-precision rotor-position estimation is necessary for the implementation of sensorless control. In low-speed region, high frequency (HF) signal injection methods are mostly adopted. They suffer to bandwidth deterioration as some digital filters must be included in the current feedback loop or the speed observation signal processing. The HF signal injection method based on the injection of voltage pulses is presented in this paper together with its implementation in MATLAB/Simulink. The method is based on the injection of voltage pulses where injection itself is separated from the motor control algorithm. The simulation results show that the proposed method has good dynamic performance for the sensorless control of PMSM.

Switched PI Control Based MRAS for Sensorless Control of PMSM Drives Using Fuzzy-Logic-Controller

With the use of sensorless control strategy, mechanical position sensors can be removed from the gearbox, so as to decrease the maintenance costs and enhance the system robustness. In this paper, a switching PI control based model reference adaptive system (MRAS) observer using Fuzzy-Logic-Controller (FLC) is introduced for sensorless control of permanent magnet synchronous motor (PMSM) drives. The main work and innovation of this paper include: 1) A disturbance observer based voltage compensation method is proposed to solve the problems of voltage distortion in voltage source inverter (VSI) fed PMSM systems. 2) A double closed-loop FLC is designed for speed and current control. The response performance of speed regulation and the accuracy of the command voltage are improved, and the difficulty of manual adjustment of control parameters is avoided. 3) A sensorless control strategy of a switching PI control based MRAS observer is proposed for stator resistance tracking. By setting different thresholds, the proposed MRAS observer can choose the appropriate PI adaptive mechanism based on the amplitude of the current error variable, which can improve the accuracy of resistance estimation and improve the dynamic performance of sensorless control. 4) The experimental results are given to verify the availability of the proposed scheme.

Novel tilt integral sliding mode controller and observer design for sensorless speed control of a permanent magnet synchronous motor

PurposeThis study aims to design and implement a novel tilt integral sliding mode controller and observer for sensorless speed control of a permanent magnet synchronous motor (PMSM).Design/methodology/approachA control strategy combining the tilt integral derivative (TID) with sliding mode control (SMC) is proposed to determine the tilt integral sliding mode manifold. Using this manifold, tilt integral sliding mode controller (TISMC) and observer (TISMO) are designed. The stabilities are verified by using Lyapunov method. To prove the effectiveness and robustness of proposed methods, sensorless speed control of PMSM is performed for various operating conditions such as constant and variable speed references, load disturbance injection, parameter perturbation, whereas sensor noises are not taken into account. The performance of proposed method is compared with TID controller, proportional integral derivative controller and conventional SMO.FindingsSimulation results demonstrate that TISMC and TISMO have better performance in all operating conditions. They are robust against parameter uncertainties and disturbances. TISM based sensorless control of PMSM is well guaranteed with superior performance.Originality/valueThe proposed method has not been tackled in the literature. By combining TID and SMC, novel tilt integral sliding manifold is presented and used in designing of the controller and observer. It is proven by Lyapunov method that errors converge to zero.