Speed Control Of Synchronous Motor Research Articles

Fixed-Time-Convergent Sliding Mode Control with Sliding Mode Observer for PMSM Speed Regulation.

This paper focuses on the speed control of a permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and external disturbances. Conventional sliding mode control (CSMC) can only converge asymptotically in the infinite domain and will cause unacceptable sliding mode chattering. To improve the performance of the PMSM speed loop in terms of response speed, tracking accuracy, and robustness, a hybrid control strategy for a fixed-time-convergent sliding mode controller (FSMC) with a fixed-time-convergent sliding mode observer (FSMO) is proposed for PMSM speed regulation using the fixed-time control theory. Firstly, the FSMC is proposed to improve the convergence speed and robustness of the speed loop, which can converge to the origin within a fixed time independent of the initial conditions. Then, the FSMO is used as a compensator to further enhance the robustness of the speed loop and attenuate sliding mode chattering. Finally, simulation and experimental results show that the proposed method can effectively improve the dynamic performance and robustness of the PMSM speed control system.

Comparative Investigation of DSP-Based Speed Control of PMSM Using Proportional Integral and Takagi-Sugeno Fuzzy Logic Controller

This paper presents the simulation and experimental results of speed control of a three-phase Permanent Magnet Synchronous Motor (PMSM). The control techniques employed in this work include a Proportional Integral (PI) controller and a Takagi-Sugeno Fuzzy Logic Controller (TS-FLC). While theory and simulation help in predicting the PI controller settings for real drive implementation, further adjustment of the PI controller coefficients is still needed for optimal performance. However, the complexity of PI controller tuning can be overcome by employing a fuzzy logic controller, which is less affected by variations in model parameters and load torque. Two variants of the proposed TS-FLC are implemented: a simple algorithm with 9 rules and a standard algorithm with 49 rules. The drive system utilizes Field Oriented Control (FOC). The control program is developed using the C/C++ programming language and executed on the Texas Instruments TMS320LF28335 Digital Signal Processor (DSP), known for its intelligent motor control capabilities. The drive system evaluation was performed through simulations and experimentation using the MCK28335 professional development kit provided by Technosoft Company. The simulation and experimental results of the proposed controllers are compared under various conditions, including speed reversal and load torque variations.

Anti-disturbance speed control of permanent magnet synchronous motor based on fractional order sliding mode load observer

Based on the fractional order sliding mode load observer, this paper presents an anti-disturbance speed control method of permanent magnet semi-direct drive transmission system for overhead manned equipment. According to the Lagrange equation, the dynamic model of semi-direct drive transmission system is established. Furthermore, the mathematical model of the permanent magnet synchronous motor (PMSM) is established based on the coordinate transformation theory. Subsequently, the fractional order sliding mode observer (FOSMO), which combines nonsingular terminal sliding mode control and fractional order theory is designed to observe the load disturbance changes in the permanent magnet semi-direct drive transmission system. Then, the concept of “active damping” is used to design the speed loop PI controller, and combined with the designed FOSMO to construct the composite speed controller. The designed composite speed controller is further improved by the anti-saturation design and parameter optimization. The results demonstrate that the designed FOSMO can precisely estimate the load disturbance on the PMSM output shaft. Additionally, the designed composite speed controller can realize stable speed control in the case of complex load disturbance, which meets the anti-disturbance speed control requirements of permanent magnet semi-direct drive transmission system, and the robustness of the control system is further improved by adding the anti-saturation link.

Permanent magnet synchronous motor speed control system based on fractional order integral sliding mode control

Permanent magnet synchronous motor speed control system based on fractional order integral sliding mode control

An enhanced switching active disturbance rejection controller for speed control of permanent magnet synchronous motor

An enhanced switching active disturbance rejection controller for speed control of permanent magnet synchronous motor

Disturbances rejection optimization based on improved two-degree-of-freedom LADRC for permanent magnet synchronous motor systems

Permanent magnet synchronous motor (PMSM) speed control systems with conventional linear active disturbance rejection control (CLADRC) strategy encounter issues regarding the coupling between dynamic response and disturbance suppression and have poor performance in suppressing complex nonlinear disturbances. In order to address these issues, this paper proposes an improved two-degree-of-freedom LADRC (TDOF-LADRC) strategy, which can enhance the disturbance rejection performance of the system while decoupling entirely the system's dynamic and anti-disturbance performance to boost the system robustness and simplify controller parameter tuning. PMSM models that consider total disturbances are developed to design the TDOF-LADRC speed controller accurately. Moreover, to evaluate the control performance of the TDOF-LADRC strategy, its stability is proven, and the influence of each controller parameter on the system control performance is analyzed. Based on it, a comparison is made between the disturbance observation ability and anti-disturbance performance of TDOF-LADRC and CLADRC to prove the superiority of TDOF-LADRC in rejecting disturbances. Finally, experiments are performed on a 750 W PMSM experimental platform, and the results demonstrate that the proposed TDOF-LADRC exhibits the properties of two degrees of freedom and improves the disturbance rejection performance of the PMSM system.

Perancangan Self Tuning Dua Derajat Kebebasan dengan Metode Fuzzy Logic pada Pengendalian Kecepatan Motor Sinkron Magnet Permanen Menggunakan Metode Vector Control

Abstract — This paper proposes self tuning Proportional-Integral/Proportional gain controller parameter in a Two Degree of Freedom (2DoF) using fuzzy logic method for speed control of permanent magnet synchronous motor. The self tuning method can automatically determine the PI-P parameters using a fuzzy logic control system. Speed control of the 3-phase permanent magnet synchronous motor is carried out by changing the 3-phase system (a-b-c) to a 2-phase system (direct-quadrature) using the vector control method. SVPWM method is used to modulate six switches on a 3 phase inverter. The results obtained using MATLAB Simulink show that by using a self-tuning fuzzy logic control system, high motor performance results are obtained, where the speed response of the permanent magnet synchronous motor shows that the step response and disturbance response are close to the ideal response.
 Keywords— Permanent Magnet Synchronous Motor, Self Tuning, Two Degrees of Freedom, Fuzzy Logic, Vector Control.

Neural Network-Driven Sensorless Speed Control of EV Drive Using PMSM

To reduce pollution and energy consumption, particularly in the automotive industry, energy saving is the main concern, and hence, Electric vehicles (EVs) are getting significantly more attention than vehicles with internal combustion engines (IC engines). Electric motors used in Electric Vehicles (EVs) must have high efficiency for maximum utilization of the energy from the batteries or fuel cells. Also, these motors must be compact, lightweight, less expensive and very easily recycled. Further, to obtain better dynamic performance, various motor control strategies are used to control the speed of the motor. And to have increased reliability, sensorless speed control techniques that offer sufficiently high performance are used. The sensorless speed control techniques are largely divided into three groups: state observer methods, indirect measurement methods and saliency-based methods. Generally, the state observer uses back emf or flux linkage to estimate the speed of the motor. Since the back emf is directly proportional to the rotor speed, at low-speed back emf based method will give poor performance. The current-based Model Reference Adaptive System (MRAS) model is also popular for estimating low speed; however, assessments deteriorate during high performance applications such as EV. This paper presents an artificial neural network (ANN)-deployed sensorless speed control of permanent magnet synchronous motor (PMSM) drive used in EVs. In this paper, the estimation of speed using the current-based MRAS model is discussed and compared with the proposed ANN-based controller, which shows significant improvement in the performance of EV motor drives. The MATLAB simulation and experimental results are presented to validate the proposed algorithm.

Finite-time robust speed control of synchronous reluctance motor using disturbance rejection sliding mode control with advanced reaching law.

In recent years, there has been a significant focus on synchronous reluctance motors (SynRM) owing to their impressive efficiency and absence of magnetic material. Although the SynRM shows great potential for use in electric vehicles, its widespread adoption is limited by unmodeled dynamics and external disturbances. Moreover, the uncertainty factor significantly restricts SynRM's peak efficiency and superior control performance, leading to an unjustifiable current loop reference command. To address these issues, this work presents various new research contributions which focus on the robust control of SynRM to optimize performance through the novel reaching law-based sliding mode control. Initially, a novel advanced sliding mode control reaching law (ASMCRL) with adaptive gain is proposed, to enhance the acceleration of the system state reaching the sliding surface. After that, an extended state observer (ESO) is designed to estimate and compensate for the overall disturbances of the system. Finally, the ASMCRL and ESO are integrated to design two nonlinear controllers namely, the disturbance-rejection sliding mode controller (DRSMC) and the disturbance-rejection sliding mode speed regulator (DRSMSR) for SynRM. The proposed DRSMSR eliminates the steady-state error and eradicates inherent chattering in DRSMC. Moreover, this yields a system trajectory that converges to a predetermined proximity of the sliding surface, irrespective of any lumped disturbances. The steady-state error of DRSMSR is less as compared to DRSMC. Furthermore, the speed response of this technique is 22.62% faster as compared to the state-of-the-art finite-time adaptive terminal sliding mode control. Additionally, the asymptotic stability of the proposed system is validated using Lyapunov's theorem. Thus the experimental results demonstrate the effectiveness and robustness of the proposed approach.

Improved Federal Test Procedure (FTP75) driving cycle performance for PMSM‐fed hybrid electric vehicles using artificial neural network

SummaryThe sensorless speed control of permanent magnet synchronous motor (PMSM) is gaining popularity in hybrid electric vehicle (HEV) applications leading to its enhanced safety, reliability, and cost savings. Speed control using vector control for PMSM‐fed HEV requires the speed encoder. When the speed sensor information fails, the inverter must ensure power delivery to the PMSM continuously by estimating the speed; this mode of operation is referred as limp‐home mode in HEV. In this paper, a speed sensorless scheme has been proposed for PMSM‐based HEV during limp‐home mode operation. This paper presents a model reference adaptive system (MRAS) speed estimator based on an adaptive neural network controller (NNC) for speed estimation of PMSM. In the HEV application, in case of speed/position encoder failure, the speed of the PMSM can be estimated by stator flux using stator current.The proposed method employs stator currents in the reference model to eliminate the DC drift problem. Furthermore, the NNC is employed in the adaptation mechanism to improve the Federal Test Procedure (FTP75) driving cycle performance. The performance of the proposed control scheme has been validated with dSPACE 1104 R & D rapid development controller using vector control for the PMSM during variable speed and torque, including the zero‐speed applications

Fuzzy controller-based predictive speed control of a permanent magnet synchronous motor

Fuzzy controller-based predictive speed control of a permanent magnet synchronous motor

Autoregressive Moving Average Model-Free Predictive Current Control for PMSM Drives

To eliminate the influence of the parameter mismatches and obtain high model quality, a model-free predictive current control (MF-PCC) strategy based on the autoregressive moving average (ARMA) structure is proposed in this paper and applied to the permanent magnet synchronous motor (PMSM) speed control system. Since the ARMA model group which is a family of mathematical models containing AR, MA and ARMA structures considers operating states within several sampling periods to achieve better model accuracy, the plant is online designed as this type, and its coefficients are estimated according to the sampled data by the normalized least-mean-square (NLMS) algorithm with adaptive normalized step length to achieve improved model quality with reduced calculation burden. Compared with the ultra-local MF-PCC strategy, advantages of better stator current quality and robustness are demonstrated by the experimental results, as well as the reduced calculation burden compared with the recursive least square (RLS) algorithm used to estimate the coefficients.

Generalized Data-Driven Model-Free Predictive Control for Electrical Drive Systems

The performance of model predictive control has a strong correlation to the precision of the physical parameters of the plant, and these parameters are hard to determine since they are continuously changing during the operation process. To fully eliminate the influence of the physical parameters and enhance robustness, a model-free predictive control is proposed in this article to suit the electrical drive systems. The plant model is designed as several discrete-time transfer functions used to decouple the input and output signals and to describe their relationships, and the coefficients of these functions are online designed based on the recursive least square algorithm. An observer is designed to obtain accurately sampled current components considering the delays. The proposed method is applied to a permanent magnet synchronous motor speed control system as the stator current controller, and the simulation and experimental results show the advantages of the improved dynamics, stator current quality, and robustness compared with the conventional model-free predictive current control strategy.

Decoupled Speed and Flux Control of a Three-Phase Permanent Magnet Synchronous Motor under an Open-Circuit Fault Using a PR Current Controller

Presented in this article is a method for decoupling the speed and flux control of a three-phase permanent magnet synchronous motor (PMSM) during an open-circuit fault (OCF) using a current controller based on proportional resonant (PR) control techniques. The suggested control approach is relatively simple to implement and maintains good motor operation during the open circuit. PMSM performance under pre-fault, OCF, and post-fault conditions were investigated using Matlab/Simulink and an experimental setup based on a dSPACE DS1104. The conducted investigations provide strong evidence supporting the efficacy and resilience of the suggested control approach during OCF conditions.

Model Predictive Direct Speed Control of Permanent-Magnet Synchronous Motors with Voltage Error Compensation

Traditional strategies for model predictive direct speed control of permanent-magnet synchronous motors are known to be vulnerable to voltage errors. In this paper, we present a novel approach that compensates for voltage errors arising from inverter nonlinearity and bus voltage uncertainties, while remaining unaffected by parameter errors. Initially, we conducted a detailed analysis to assess the impact of inverter nonlinearity and bus voltage uncertainties. Subsequently, we proposed a voltage error compensation strategy based on bus voltage identification. Using this strategy, the identified voltage error is effectively compensated within candidate voltage vectors. To validate the effectiveness of our proposed method, we conducted comprehensive experiments. The results demonstrate notable improvements compared with traditional model predictive control. Specifically, our method successfully reduces the total harmonic distortion of phase currents from 23.2% and 49.6% to 11.6% and 13.9%, respectively. Additionally, it accurately identifies voltage errors, even in the presence of parameter errors. Overall, our proposed method presents a robust and reliable solution for addressing voltage errors, thereby enhancing the performance and stability of the system.

Neutrosophic Valued PID Controller for Closed Loop V/f Speed Control of Permanent Magnet Synchronous Motor

In this article, a neutrophic logic-based closed loop V/f control system has been established by creating a fuzzy inference system and a neutrophic fuzzy logic controller (NFLC) in Matlab. Also, the NFLC-PID block diagram has been established to test in a Simulink environment with permanent magnet synchronous motor (PMSM). The simulation results demonstrate that the neutrosophic fuzzy logic controller managed the PMSM efficiently and successfully.

Sliding-mode anti-disturbance speed control of permanent magnet synchronous motor based on an advanced reaching law

In order to improve the performance of a permanent magnet synchronous motor (PMSM) speed controller, an advanced reaching law sliding mode control (ASMC) strategy is proposed in this study. The advanced sliding mode reaching law (ASMRL) introduces a power term of the system state and a checkmark function term about the sliding mode function based on the traditional constant-proportional rate reaching law(TSMRL) , and replaces the sign function with a hyperbolic tangent function. A detailed theoretical analysis of the characteristics of the ASMRL is then presented. The theoretical analysis shows that the ASMRL converges to the sliding mode surface more quickly and with less chattering than the TSMRL. In addition, a sliding mode disturbance observer (SMDO) is designed to estimate the total disturbance of the system, and the estimated disturbance is compensated to ASMC. Then the stability of the system with ASMC and the stability of the system with ASMC+SMDO is proved by Lyapunov’s theorem. Finally, the proposed control strategy is validated on an experimental platform of PMSM. The experimental results show that the ASMC has a faster convergence speed, smaller chattering, better disturbance rejection performance than the traditional constant-proportional rate reaching law sliding mode control(TSMC), and better performance with the addition of SMDO.

Full-order adaptive sliding mode control with extended state observer for high-speed PMSM speed regulation

In order to achieve speed control of high-speed permanent magnet synchronous motor with high precision, the sliding mode control (SMC) is usually adopted. However, the inherent chattering phenomenon affects the speed control performance. In order to solve this problem, a composite speed regulator is proposed in this paper, which is made up of two parts: the adaptive full-order SMC and extended state observer (ESO). Switching gain adaption law is proposed for minimizing chattering as much as possible while ensuring the robustness of sliding mode control. The total disturbance is estimated by the ESO and through feedforward, thus improving the system anti-disturbance ability. Finally, the effectiveness of the proposed speed regulator has been validated in the test bench.

A Robust Predictive Speed Control for SPMSM Systems Using a Sliding Mode Gradient Descent Disturbance Observer

This paper proposes a sliding mode gradient descent disturbance observer-based adaptive reaching law sliding mode predictive speed control (GD-SMPC+ARL) for surface-mounted permanent magnet synchronous motor (SPMSM) systems to achieve outstanding disturbance rejection ability and tracking performance. Firstly, an SPMSM model with disturbance is given by incorporating the lumped disturbances into the q-axis current's coefficient. Then, a stable sliding mode gradient descent disturbance observer (SM-GDDO) is designed to identify the q-axis current's coefficient that varies with the lumped disturbance. Finally, a GD-SMPC+ARL strategy, which utilizes an adaptive reaching law-based cost function, is developed on the basis of the proposed SPMSM model, where the q-axis current's coefficient is estimated by utilizing SM-GDDO and updated at each control period. Compared with conventional reaching laws, the proposed adaptive reaching law suppresses the chattering while maintaining a fast following speed. Simulation and experimental results verify the excellent robustness and tracking performances of the proposed method.

Speed Control of an Interior Permanent Magnet Synchronous Motor using a Disturbance Observer

For precise speed control of an interior permanent magnet synchronous motor (IPMSM), information on load is required. Therefore, in the mechanical system of the motor, the load acting on the rotating shaft was considered as a disturbance, and in the electrical system, a disturbance observer was designed by considering the nonlinear terms as disturbance. The disturbance estimated from the designed observer is reflected in the speed controller and the current controller, respectively. As a result of operating the motor with a constant load of 1 [Nm], it can be confirmed that the undershoot that occurs when a load is applied is improved by about 13.2 [%].