Sensorless Control Of Permanent Magnet Synchronous Motor Research Articles

Fuzzy adaptive super‐twisting algorithm based sliding‐mode observer for sensorless control of permanent magnet synchronous motor

Aiming at the issues of slow convergence, phase delay, and chattering in the sensorless vector control system of permanent magnet synchronous motor (PMSM) controlled by sliding mode observer (SMO), a fuzzy adaptive super-twisting (ST) SMO sensorless control algorithm is proposed. The fuzzy adaptive algorithm is used to estimate the uncertain boundary and adaptively adjust sliding mode gain, which is used in the ST algorithm to accelerate the convergence speed of sliding mode gain, and eliminate the system delay caused by phase locked loop and phase compensation, and improve the estimation accuracy of speed and rotor position. In this algorithm, the sigmoid function is used instead of the signum function in the traditional SMO to suppress system chattering. Lyapunov stability theorem is used to obtain the stable conditions of position and speed observer at motoring mode. The saturated ST-SMO algorithm is verified by Matlab/Simulink. The simulation results show that compared with the traditional SMO, the fuzzy ST-SMO algorithm proposed in this paper has faster convergence speed in the variable speed and the variable load of PMSM sensorless control system, which has significantly reduced chattering, obtained more accurate speed and rotor position and has better dynamic response and robustness.

Sensorless Control of PMSM Based on Backstepping-PSO-Type Controller and ESO-Type Observer Using Real-Time Hardware

In the case of using a Permanent Magnet Synchronous Motor (PMSM) linear model of limited-range parametric variations and of relatively low dynamic of the load torque, the Field Oriented Control (FOC) type strategy ensures good performance of the PMSM control. Therefore, when using a non-linear model of wide-range parametric variations and of high dynamic of the load torque, a backstepping-type controller is proposed, whose tuning parameters are optimized by using a Particle Swarm Optimization (PSO) method. By designing an Extended State Observer (ESO), which provides a good estimate of the PMSM rotor position and speed under uncertainty conditions and with a response time shorter than that of the backstepping-type controller, this observer can be incorporated into the PMSM sensorless control system. The superior performance of the proposed sensorless control system based on the backstepping-PSO-type controller and an ESO-type observer is demonstrated through numerical simulations. Given that the real-time implementation of the control algorithms and observers in an embedded system is a difficult task, consisting of several steps, it is presented after the numerical simulations, which can be assimilated into the Software-in-the-Loop (SIL) step, the Processor-in-the-Loop (PIL) intermediate step, and the Hardware-in-the-Loop (HIL) final step. A comparison between the backstepping-PSO-type controller and the PI-PSO-type controller is presented by means of the real-time implementation of these controllers and demonstrates the superiority of the backstepping-PSO-type controller.

Nonlinear sensorless speed tracking control for PMSM with unmodeled electromotive forces

AbstractIn this paper, a sensorless speed tracking control scheme is proposed for Permanent Magnet Synchronous Motor (PMSM) with unmodeled electromotive forces. Specifically, one observer is developed to estimate the angular velocity of PMSM and the estimated value is injected into a novel nonlinear feedback controller. The unmodeled electromotive forces are not estimated. The influences of the unmodeled electromotive forces on the speed tracking performance are overcome by constructing corresponding nonlinear damping terms in the controller. Under certain assumptions, the rigorous proof of the stability of the closed‐loop system is completed with Lyapunov theory. All the dynamic signals are bounded. Furthermore, the estimation error and the tracking error can converge to an arbitrarily small value by choosing the control parameters appropriately large. Finally, the simulation results of constant and time‐vary speed tracking illustrated the effectiveness of the proposed controller.

Disturbance rejection speed sensorless control of PMSMs based on full order adaptive observer

Speed sensorless control systems with a full order adaptive observer of the permanent magnet synchronous motor (PMSM) have received wide attention due to their advantages of simple structure, easy implementation and strong universality. However, they are sensitive to the load disturbances, which affects the speed performance of the control system. To solve this problem, this paper presents a disturbance rejection speed sensorless control of PMSMs based on full order adaptive observer to improve robustness against load disturbances. A load disturbance observer (LDO) is used to observe load disturbances, which feed-forward compensates the q-axis current to reduce the speed drop and accelerate the recovery time. Experimental results show that the proposed method has better anti-interference capability than full order adaptive speed sensorless control under the same steady-state performance.

Improved ANFIS based MRAC observer for sensorless control of PMSM

Detection of the rotor position is an important prerequisite for controlling the speed and developed torque in permanent magnet synchronous motor (PMSM). Even though use of incremental encoder and resolver is one of the popular schemes for sensing the rotor position in a PMSM drive, it increases the size and weight of the drive and reduces its reliability. Dynamic modeling of the motor and control algorithms are often used in sensor-less control of PMSM to estimate rotor position and motor speed. Most sensor-less control algorithms use machine parameters like torque constant, stator inductances and stator resistance for estimating the rotor position and speed. However, with accuracy of such estimation and the performance of the motor degrades with variation in motor parameters. Model reference adaptive control (MRAC) provides a simple solution to this issue. An improved Adaptive neuro-fuzzy inference system (ANFIS) based MRAC observer for speed control of PMSM drive is presented in this paper. In the proposed method adaptive model and adaptive mechanism are replaced by an improved ANFIS controller, which neutralize the effect of parametric variation and results in improved performance of the drive. The modeling equations of PMSM are used to estimate the rotor position for speed and torque control of the drive. Simulation studies have been carried out under various operating condition using MATLAB/Simulink. In addition, a comparative analysis of the conventional MRAC based observer and improved ANFIS based MRAC observer is carried out. It is observed that the proposed method results in better performance of the PMSM drive.

New exponential convergence properties for Bernard–Praly observer and adaptive sensorless control of PMSMs

It is innovatively established, through a nonlinear Persistency of Excitation (PE) analysis, that the latest Bernard–Praly gradient adaptive observer – for nonsalient-pole surface Permanent Magnet Synchronous Motors (PMSMs) with uncertain flux of the permanent magnet (PM) – owns exponential convergence properties under well-known observability conditions. Such exponential properties can be crucially used to provide a new solution to the long-standing problem of guaranteeing position/speed tracking in sensorless PMSMs, in the presence of uncertain constant parameters such as load torque, PM flux and possibly stator resistance.

Sensorless control of PMSM using generalized extended state observer and adaptive resistance estimation

In this study, a novel sensorless control of the surface-mounted permanent-magnet synchronous motor (PMSM) is proposed. Firstly, by taking the derivative of the back electromotive force (EMF), the high-order voltage equations of PMSM, in which the dominant time-changing parts of back-EMF are separated and modelled, are deduced. Then a generalised extended state observer, which possesses the preferable tracking ability for time-varying states, is designed to estimate the back-EMF. Also, since the difference between the measured stator resistance and its real value, which changes with temperature, will lead to position errors, a resistance estimation scheme is proposed. Compared with the conventional sensorless method of PMSM, the proposed method can provide a more accurate and smooth position and speed estimation under resistance uncertainty without extra filter and compensator. Furthermore, since the effects of speed and current change rate are taken into consideration, the application of the proposed scheme is broadened. The effectiveness of the proposed method is verified by the experiments in different cases.

Open circuit fault detection and FTC for sensorless PMS motor control based on the back-EMF SMO

ABSTRACT The detection of the electrical fault in speed controller under a Motor Control Unit System (MCUS) has been amply viewed in the research paper. Nevertheless, the research work in this domain have been constantly followed on sensor-based vector control of synchronous motor. This paper combines the Power Inverter Voltage (PIV) faults detection (signal-based approach) with sliding mode technique (model-based) to provide Fault Tolerant Control (FTC) for sensorless speed Permanent Magnet Synchronous (PMS) motor drive. Back-EMF sliding mode observer (Back-EMF-SMO) is used for rotor position and stator currents estimation and simultaneously MCUS fault diagnosis. The fault diagnosis for MCUS faults of PMS motor drives using a Hilbert Transform. The motor phase currents signals shapes for various modes of MCUS faults are examined. A PIV Faults Detection and Isolation (FDI) algorithm is used to allow the switchover to a redundant leg. The obtained findings exhibit the effectiveness of the suggested FDI process particularly to detect and to isolate a PIV faults for sensorless PMS motor drives.

Design of a Fuzzy Logic-based MPPT Controller for a PV System Employing Sensorless Control of MRAS-based PMSM

The permanent magnet synchronous motors (PMSM) are widely employed in industrial, robotic, water pumping and HVAC applications due to their numerous benefits such as small size, high-energy efficiency, high performance, low inertia and the ability to operate in full load at low speeds. In case the PMSM drive system is supplied from photovoltaic (PV) modules, it can be a perfect match for water pumping or HVAC applications. In such a system, in order to extract full energy from PV modules, a maximum power point tracking (MPPT) algorithm must be employed. This article presents a PV system-fed PMSM drive system with sensorless speed control. The proposed system consists of two main parts. The first part deals with MPPT algorithm based on fuzzy logic controller and the second part deals with PMSM drive system with a sensorless speed estimator by using Model Reference Adaptive System (MRAS) approach to eliminate the use of an encoder. The operation of PMSM is accomplished by using the vector control method to obtain a similar dynamic of the DC motor. The overall system is modelled in Matlab/Simulink environment and simulation results are collected under various operating conditions.

Comparative study of sensorless control of Permanent magnet synchronous motor realised by sliding‐mode observer

In this study, the permanent-magnet synchronous motor sensorless control systems realised by sliding-mode observers in stationary αβ and estimated γδ coordinates are systematically studied and compared. First, based on the sufficient condition of sliding-mode stability, a more reasonable selection method of boundary layer width and sliding-mode gain is derived, effectively reducing the system chattering. Furthermore, in extracting estimated extended electromotive force, the advantages and disadvantages of the backforward method in the αβ-axis and the influence of filter cut-off frequency on estimation error in the γδ-axis are analysed. Finally, the estimation error, speed range, stability, and the effect of speed error of these two sensorless control systems are analysed and compared. The results indicate that these two systems have equivalent position error above a certain speed, and the γδ-axis estimation system has a larger position error in low-speed range, but still operating well. Moreover, the γδ-axis estimation algorithm has better stability and wider-speed range. Owing to the fast track of phase-locked loop, the effect of speed error on estimation accuracy of the γδ-axis system can be neglected. Simulation and experiment verified the theoretical analysis and comparison.

Sensor-based and Sensorless Vector Control of Permanent Magnet Synchronous Motor Drives: A Comparative Study

Background: Speed and rotor position estimation is mandatory for vector control scheme of Permanent Magnet Synchronous Motor (PMSM). Methods: The estimation accuracy of Non-adaptive (Open loop) methods degrades as mechanical speed reduces. The system becomes more robust against parameter mismatch and signal noises by employing adaptive observers for estimation of speed and position. Sensorless scheme adopted for estimating the PMSM rotor position based on its performance which eliminates the need for speed sensors which are usually required in such control applications. Results: To achieve this goal, a Space Vector Pulse Width Modulation (SVPWM) control scheme is applied to work in conjunction with a vector control PMSM drive using Simulink. The PI controller uses from estimated speed feedback for the speed sensorless control of PMSM. Conclusion: In this paper, a comprehensive analysis of sensor-based and sensorless based on Sliding Mode Observer (SMO) techniques for vector control of PMSM is presented with regards to the steadystate and dynamic performance robustness against parameter sensitivity, stability and computational complexity. The control scheme is simulated in the MATLAB/Simulink software environment.

The Permanent Magnet Synchronous Motor Sensorless Control of Electric Power Steering Based on Iterative Fifth-Order Cubature Kalman Filter

Abstract A discrete mathematical model of a permanent magnet synchronous motor (PMSM) is established, then the fifth-order cubature Kalman filter (CKF) algorithm is introduced. A Gauss–Newton iterative method is introduced into the iterative process of the fifth-order CKF algorithm to generate the innovation variance and covariance. Therefore, an iterative fifth-order CKF algorithm is proposed as the basis of a PMSM sensorless control is implemented. Then, a PMSM sensorless control based on the iterative fifth-order CKF algorithm is applied to an electric power steering (EPS) system, whose control system is constructed by adopting the typical assist and return control strategy. Finally, to verify the performance of the proposed PMSM sensorless control method, the EPS system model of the PMSM sensorless control is built by using the common phase-locked loop (PLL), the CKF algorithm, the fifth-order CKF algorithm, and the proposed iterative fifth-order CKF algorithm. The simulation analyses and the experimental tests show that the proposed iterative fifth-order CKF algorithm can estimate the PMSM speed with good accuracy and has a strong resistance to disturbances in the load and speed. The assist and return performances of the EPS system are also improved.

T-Source Inverter-Based Sensorless Speed Control for Permanent Magnet Synchronous Motor

Abstract Permanent magnet synchronous motors (PMSM) are used commonly in numerous industrial applications, for instance, in mechatronics, vacuum pumps, energy storage flywheels, automotive, centrifugal compressors, and robotics. Nowadays, the sensorless speed control of PMSM is getting more attention, and several studies are progressing because of its low cost and reliable features. Normally, the speed control methods in PMSM are achieved with the help of sensors for position or speed estimation and control. But, these sensors are easily prone to breakage. Also, the flexibility towards parameter variations is poor in the conventional speed control methods. So, a sensorless T-source inverter-based PMSM drive that integrates the Proportional Integral (PI) controller with an adaptive mechanism to cope with the time-varying system parameters is proposed in this article. A sensorless module, namely, a model reference adaptive system (MRAS), is employed to estimate the rotor position of PMSM based on its performance characteristics Simulation results are illustrated to investigate the performance of the proposed method with different speeds under no load and loaded conditions. Moreover, the proposed approach not only minimizes the cost and size of the motor but also maximizes the reliability and accuracy.

Sensorless Control of CSC-fed PMSM Drives with Low Switching frequency for Electrical Submersible Pump Application

In this article, current source converter (CSC)-fed permanent magnet synchronous motor (PMSM) drives are investigated for electrical submersible pump (ESP) applications. The CSC features motor-friendly waveform with low dv/dt , which is very suitable for long cable application. High-speed ESP by adopting a PMSM has higher efficiency and shorter length and diameter compared with the counterpart adopting induction motor. Sensorless control instead of mechanical sensor can further reduce the system size/cost and improve reliability due to the harsh downhole environment. However, low switching frequency and an inverter-side output filter cause great challenge in controller and observer design. These kinds of influence become more serious under a higher speed region due to the limited updates per fundamental cycle. To overcome these challenges, the dynamic capacitor voltage control is employed in a field-oriented control scheme to enhance the system dynamic response. Moreover, a discrete-time sliding mode observer based rotor position estimation method is proposed to reduce estimation error and improve parameter uncertainty robustness. The effectiveness of the proposed method is verified on a CSC-fed PMSM with simulation and experimental results.

Research on Startup Process for Sensorless Control of PMSMs Based on I-F Method Combined With an Adaptive Compensator

Speed control of permanent magnet synchronous motors (PMSMs) without position sensors is preferable in some applications due to cost and mounting space concerns. For applications in which the operating speed is relatively stable, the dynamic performance and efficiency demands of PMSMs are not severe during the startup process. Under such circumstances, a sensorless controller based on back electromotive force (EMF) estimation combined with a simple startup strategy is a suitable solution. In this paper, an I-f (current-frequency) startup method and a sliding mode observer are adopted to develop a sensorless control system, and the startup process which employs the I-f method is analysed in detail. Based on the analysis, this paper proposes a simple and robust startup strategy with an adaptive compensator to realize the smooth transition from I-f control to EMF-based control. The proposed strategy allows quick startup from standstill under different load conditions without initial position estimation. Furthermore, the strategy does not introduce any additional control coefficients, and none of the original control coefficients need to be adjusted. The strategy is suitable for both surface and interior PMSMs, and a test bench based on an interior PMSM is built to validate its properties. The experimental results show that the motor can smoothly accelerate from standstill to its rated speed in less than 2 s in both loaded and non-loaded situations, and the transition between the two sensorless control methods does not cause any large speed or current fluctuations.

Sensorless control of PMSM with fuzzy model reference adaptive system

<p>To improve the performance of permanent-magnet synchronous motor (PMSM) drives powered by the voltage inverter with PWM control, a sensorless control scheme based on a Model Reference Adaptive System (MRAS) a fuzzy logic controller (FLC) based in with fuzzy supervisor structure. The major drawbacks of the conventional MRAS, namely chattering phenomena, high-order harmonics andexternal noise, are discussed. These drawbacks affect the estimated speed accuracy of the MRAS and reduce the control reliability of the system. To eliminate these drawbacks, an FLC is designed and integrated into the MRAS to adjust the observer gain to reduce the chattering in closed loop speed and closed loop current/torque. Comparative simulations using the proposed Fuzzy-MRAS and the conventional MRAS are performed to validate the effectiveness of the proposed FLC structure. Performance simulations of the overall proposed Fuzzy-MRAS based sensorless control scheme are performed to verify the robustness and control reliability of the system. The results show that the proposed Fuzzy MRAS has satisfactory performances with reduction of total harmonic distortion generated in the phase currents.</p>

Research on Position Sensorless Control of PMSM Based on Improved SMO

The sliding mode observer (SMO) can effectively achieve the permanent magnet synchronous motor (PMSM) to perform position sensorless control, but there are still drawbacks of system chattering and high complexity. In this paper, an improved SMO is established based on hyperbolic tangent function and Kalman filter. The system chattering is effectively suppressed, and the accuracy of position and speed observation error is significantly improved without phase compensation. It is found that the convergence rate of the hyperbolic tangent function has a strong correlation with the system chattering degree and the speed observation error. When a is between 3 and 4, the speed error accuracy of the improved SMO is the optimum situation.

Design and performance analysis of an iterative flux sliding-mode observer for the sensorless control of PMSM drives

To improve the performance of permanent magnet synchronous motor (PMSM) drives, a sensorless control scheme based on a novel iterative flux sliding-mode observer (IFSMO) is proposed in this paper. Two major drawbacks of the conventional sliding-mode observer (SMO), namely, chattering phenomena and high-order harmonics, are discussed. These drawbacks affect the estimation accuracy of the SMO and reduce the control reliability of the system. To eliminate high-order harmonics, a flux SMO is designed by expanding the PMSM state equations with the PM flux. The flux SMO estimates the rotor speed and position using the flux linkage instead of back-EMF information. Moreover, to reduce the chattering in the estimation results, the proposed flux SMO is iteratively used in one current sampling period to adaptively adjust the observer gain. An overall PMSM sensorless control system based on the proposed IFSMO is designed, and an experimental platform using the TMS320F28335 digital signal processor (DSP) controller is built. The superior chattering reduction and harmonic suppression characteristics of the proposed IFSMO are experimentally validated, and the experimental results verify the feasibility of using the proposed IFSMO-based PMSM sensorless scheme in practical applications.

Sensorless control of PMSM using an adaptively tuned SCKF

This study reports the application of an adaptively tuned square-root Cubature Kalman filter (SCKF) for the speed and position estimation of a permanent magnet synchronous motor (PMSM) drive. The proposed estimator is observed to exhibit improved noise rejection characteristics as compared to the hitherto widely applied extended Kalman filter (EKF) observer. A third degree spherical–radial cubature rule is used in the Cubature Kalman filter (CKF) to numerically compute the multivariate moment integrals of the general Bayesian estimation equation. CKF is a non-linear filter which avoids linearisation and the associated errors. The realisation of CKF using the square-root algorithm results in numerical stability, as with the realisation of EKF using the square-root algorithm. Simulation results are presented for a three-phase inverter-fed PMSM, along with the experimental results. The estimator and the control algorithms are realised on the MATLAB real-time environment, interfaced with the hardware using the National Instruments data acquisition system NI PCI-6221.

PSO-Based HMLP Network Controller for Speed Sensorless Control of PMSM

A sensorless control of permanent magnet synchronous motor (PMSM) by using model reference adaptive system (MRAS) and artificial neural network is presents in this paper. The objective for this study is to improve the speed and position estimation of the PMSM rotor which used the MRAS with the conventional PI controller. In this study, the multilayer perceptron (MLP) network and hybrid multilayer perceptron (HMLP) network from family of artificial neural network (ANN) were evaluated. Before the controller can be used, the value of weight between the network layers need to be optimised. To train the controller weight, particle swarm optimization (PSO) is used. Finally, the proposed method is evaluated by comparing with the proposed controller in controlling the speed and position of PMSM. Simulation results under various speed and load conditions indicated that the PSO-HMLP network controller achieved well results than the compared controller in terms transient response and overall system analysis.