Changes In Motor Parameters Research Articles

Sensorless control of permanent magnet synchronous motor based on adaptive back-EMF observer

Aiming at the problem that the change of motor parameters in actual operation will significantly reduce the control accuracy of the motor, this paper proposes a sensorless control method of permanent magnet synchronous motor based on an adaptive back-EMF observer. Firstly, in the sensorless vector control algorithm, the mathematical model of the permanent magnet synchronous motor based on the coordinate axis transformation is established, online identification of permanent magnet synchronous motor flux linkage, and the adaptive back EMF observer is constructed. The parameters update the motor model to achieve accurate control of the rotor position and speed of the permanent magnet synchronous motor. Then the back-EMF observer and the adaptive back-EMF observer are verified in the simulation environment. Then the simulation model of the back-EMF observer and the adaptive back-EMF observer is carried out, and the comparison analysis is made. Finally, a permanent magnet synchronous motor control platform is built in the laboratory, and the method proposed in this paper is verified. The results show that, under the condition that the permanent magnet synchronous motor parameters change, the online identification of the parameters and the accurate speed of the permanent magnet synchronous motor can be realized control.

Adaptive Nonlinear Control of Salient-Pole PMSM for Hybrid Electric Vehicle Applications: Theory and Experiments

This research work deals with the problem of controlling a salient-pole permanent-magnet synchronous motor (SP-PMSM) used in hybrid electric vehicles. An adaptive nonlinear controller based on the backstepping technique is developed to meet the following requirements: control of the reference vehicle speed in the presence of load variation and changes in the internal motor parameters while keeping the reliability and stability of the vehicle. The complexity of the control problem lies on the system nonlinearity, instability and the problem of inaccessibility to measure all the internal parameters, such as inertia, friction and load variation. For this issue, an adaptive backstepping regulator is developed to estimate these parameters. On the basis of formal analysis and simulation, as well as test results, it is clearly shown that the designed controller achieves all the goals, namely robustness and reliability of the controller, stability of the system and speed control, considering the uncertainty parameters’ measurements.

Changes in Motor and Sensory Parameters in Patients with Lumbar Disc Herniation

Changes in Motor and Sensory Parameters in Patients with Lumbar Disc Herniation

Current Control Method of Vehicle Permanent Magnet Synchronous Motor Based on Active Disturbance Rejection Control

Due to the frequently changing working conditions and complex operating environment of electric vehicle permanent magnet synchronous motor(PMSM), the motor parameters change dramatically. However, the performance of the PI current regulator, which is the most widely used, is sensitive to motor parameters and has weak robustness, which will lead to the deterioration of motor control system performance. To address this problem, active disturbance rejection control (ADRC) technology is applied to the PMSM current loop control. Firstly, the traditional ADRC current regulator is designed, and the performance and parameter tuning laws of the extended state observer are analyzed by the method of frequency domain analysis. Then, the traditional ADRC algorithm is improved in three aspects: observation error compensation, utilization of model information and anti-windup. After that, simulations and bench test validation are performed. The simulation results show that the improved ADRC current regulator is more robust in the face of parameter changes. The torque step test results show that the improved ADRC current regulator has fast dynamic response without overshoot and has high robustness when the motor parameters change. The dynamic test results show that the improved ADRC current regulator has high robustness when the load, speed and motor parameters change, and the anti-windup measures designed can effectively overcome the integral saturation phenomenon.

Simulation Research on Ship-borne PMSM Speed Regulation Control System Based on Fuzzy PID Control

As the important actuator of ship-borne electromechanical equipment such as offshore cranes, the control system of Permanent-magnet synchronous motor (PMSM) is a complex system that features nonlinearity, time-varying parameters, and multi-variable coupling. Due to working in a swing environment, the ship-borne PMSM speed regulation control system is confronted with some problems, such as abrupt load change, external interference signals, motor parameters change, and given signals change frequently. To improve the control performance, this study designs the 2-dimensional Fuzzy PID controller and builds the control system simulation model with a double closed-loop structure in the MATLAB/Simulink. By comparing the control system under various simulation situations, the simulation findings demonstrate that the control system using the Fuzzy PID controller far outperforms the PID controller in terms of control indicators such as stability, tracking ability, and anti-disturbance ability, which can better adapt to working in swing environment.

Self-starting control strategy of variable speed pumped storage unit based on adaptive full order state observer

When the variable speed pumped storage unit operates in the electrical state, the self-starting control strategy is generally used to start the process from zero speed to grid connection, which saves the starting device of the traditional constant speed unit and saves the construction cost of the unit. For the self-starting control process, the traditional open-loop flux calculation method will produce cumulative errors in the amplitude and angle of the flux when the motor parameters change. To solve this problem, an adaptive full order state observer is designed to observe the motor stator flux, which has stronger parameter robustness. Based on the flux observation, the speed adaptive law is designed to estimate the rotor speed and position angle, and the speed sensorless vector control of variable speed pumped storage unit is accomplished. The simulation results show that compared with the open-loop flux calculation method, the full order state observer can greatly reduce the flux estimation error and accurately estimate the rotor speed and position angle.

Motion control of linear induction motor using self-recurrent wavelet neural network trained by model predictive controller

Due to end effects phenomena that cause a decrease of air-gap flux and thrust force, obtaining a precise velocity for a linear induction motor (LIM) has become a significant challenge. This study suggests implementing a novel controller based on a self-recurrent wavelet neural network (SRWNN) and model predictive controller (MPC) to regulate the velocity and thrust force of LIM. The MPC was used to train the SRWNN in this study. The ultimate goal of employing such a control approach in neural network training is to reduce the degree of uncertainty caused by changes in motor parameters and load disturbance. The indirect field-oriented control (IFOC) approach was used to investigate velocity and flux control under varied loading circumstances. Furthermore, to supply the required LIM stator voltage, a SVPWM dependent voltage source inverter was used in this work. To ensure reliable performance, the suggested system combines the benefits of neural networks with the MPC method, resulting in a versatile controller with a basic construction that is easy to accomplish. The MATLAB package is utilized to simulates and outputs LIM responses. The results confirm that the proposed method, which efficiently controls the velocity and thrust force of the LIM, can cope with changes in load force disruption and motor parameters.

UKF-Based Parameter Estimation and Identification for Permanent Magnet Synchronous Motor

The accuracy of rotor position estimation determines the performance of the sensorless control system of a permanent magnet synchronous motor. In order to realize the accurate control of rotor position and speed, it is necessary to identify the motor parameters. Modeling and simulation of the state estimation are investigated for a permanent magnet synchronous motor with parameter identification based on the unscented Kalman filter (UKF) in this article. Based on the mathematical model of the motor, the unscented Kalman filter is used to identify the rotor flux and quadrature axis inductance simultaneously, and the identified parameters are used to update the motor model in the sensorless vector control algorithm. The simulation results show that the unscented Kalman filter can converge to the real value in a short time with small errors. It can follow the changes of motor parameters well and achieve high-precision speed and position estimation.

Effects of tabata training on health-related fitness components among secondary school students

Physical education curricula in Polish schools should include more tasks to increase physical activity. The Tabata Training Program can help regulate body weight and induce changes in body fat and physical fitness. This study aimed to determine the effects of a 10-week PE curriculum supplemented by a Tabata Training Program on health-related fitness in 16-year-old secondary school students. The study examined 187 students (66 boys and 121 girls) assigned to either a Tabata Training Program intervention or control group. The intervention lasted 14 minutes during one physical education lesson per week. Pre- and post-intervention, anthropometric measurements were taken, and each participant performed physical fitness tests to evaluate muscular strength, flexibility, speed/agility, and cardiovascular efficiency. Boys of the intervention group significantly reduced body fat (by 1.77%, p<.05) and increased cardiovascular efficiency (the physical efficiency index was higher by 3.61 points, p<.05). Girls increased cardiovascular efficiency only (the physical efficiency index increased by 5 points, p<.001). However, slight changes in motor parameters were observed in all the participants. The Tabata Training Program demonstrated partial effectiveness but should be individualized and sex differences should be considered.

Energy efficiency optimization of field-oriented control for PMSM in all electric system

Full electrification is an important change in the energy system of the new generation of aircraft, ships and other platforms. The traditional mechanical, hydraulic and other transmission modes in the system are replaced by the motor transmission mode. Therefore, the optimization of motor energy efficiency is one of the important research directions of motor control. In this paper, the maximum torque current ratio is used as the main strategy of energy efficiency optimization of motor control system, and based on this strategy, an algorithm of energy efficiency optimization control of permanent magnet synchronous motor (PMSM) is proposed, which does not depend on motor parameters, is not affected by the change of motor parameters, has strong universality and robustness. In this paper, the strategy is applied to the control of a 270 V DC permanent magnet synchronous motor in an all-electric system, which effectively improves the energy efficiency of the system.

АСИНХРОННИЙ ЕЛЕКТРОПРИВОД З КЕРУВАННЯМ ЗА РЕАКТИВНОЮ ПОТУЖНІСТЮ

The method of control of asynchronous electric drive, which based on measuring and control of reactive power of induction motor, is presented. It provides independence of magnetic flow of rotor from changes of induction motor parameters, uninterrupted diapason of regulation of speed including zero and fast regulation.

Speed sensorless control of permanent magnet synchronous motor based on robust adaptive algorithm

In order to solve the problem that the parameters of the regulator and the actual parameters do not match due to the time-varying motor parameters in the operation of PMSM, this paper adopts a robust adaptive control strategy based on linear matrix inequality (LMI) based on the model reference adaptive method (MRAS) to consider the uncertainties of the motor parameters in the state equation of the motor control system, the controller parameters are obtained by solving the LMI. The simulation model of PMSM speed sensorless control system is built in Simulink. The simulation results show that the system can track the given speed well and has strong robustness when the motor parameters change.

PMSM parameter identification based on improved PSO

The results of the standard PSO algorithm are easy to fluctuate and the time-varying error is too large. By introducing the strategy of Gaussian decline and Gaussian disturbance, an improved PSO motor parameter identification method is proposed. When the motor parameters change, the improved PSO method can be used to identify the motor parameters faster, more accurate and more stable. The simulation results show that the improved PSO overcomes the recognition results of the standard PSO and improves its recognition accuracy.

Study the role of dyslipidemia in cases of neuropathy with type 2 diabetes mellitus

Background Diabetic neuropathy is one of the most common neurological diseases. Dyslipidemia is very common in diabetic patients and thought to add to the effect of diabetes on peripheral nerves. Objectives To assess the effect of dyslipidemia on diabetic peripheral neuropathy among patients with type 2 diabetes mellitus. Patients and methods A total of 60 patients with peripheral diabetic polyneuropathy were included and divided into two groups: the first included 30 patients with diabetic neuropathy and dyslipidemia and the other 30 patients had diabetic neuropathy without dyslipidemia. Another 30 healthy volunteers were included as a control group. All were subjected to full history taking, clinical examination, laboratory investigations, and neurophysiological studies. Results Hypertension and smoking were significantly increased in cases when compared with controls. Regarding the severity of neuropathy, it was mild in seven (11.7%) patients, moderate in 34 (56.7%) patients, and severe in 19 (31.7%) patients. Neurophysiological studies of the studied populations revealed significant changes of both motor and sensory parameters in cases when compared with controls and in the group with dyslipidemia when compared with the group without dyslipidemia. In addition, there was a significant correlation between lipid profile and each of glycated hemoglobin, fasting and postprandial blood sugar, and different neurophysiological examinations. Conclusion Dyslipidemia added to the hazardous effect of diabetic neuropathy on neurophysiological studies. In addition, there was a significant correlation between lipid profile and changes in nerve conduction studies.

Neural network inverse system decoupling fuzzy self-tuning proportional–derivative control strategy of a bearingless induction motor

In view of the problems that the analytical inverse system decoupling method of bearingless induction motor is sensitive to the change of motor parameters and is greatly affected by unmodeled dynamics, and that of traditional proportional–derivative controller lacking the self-adaptive regulation ability, a neural network inverse system decoupling fuzzy self-tuning proportional–derivative control strategy is proposed for a bearingless induction motor system. First, under the conditions of considering the stator current dynamic of torque winding, and by neural network inverse system method, the bearingless induction motor system is decoupled into four pseudo-linear integral subsystems. Second, the traditional proportional–derivative controller is improved, and the fuzzy control algorithm is used to adjust the parameters of improved proportional–derivative controller adaptively. Thus, a neural network inverse system decoupling fuzzy self-tuning proportional–derivative control system is constructed for a bearingless induction motor. The simulation experimental results show that the proposed control strategy not only can effectively improve the stability, robustness and steady-state control accuracy of bearingless induction motor system, but also can significantly improve the dynamic response speed and the ability to resist the influences of motor parameter change and load disturbance.

Adaptive position control of a cart moved by a DC motor using integral controller tuned by Jaya optimization with Balloon effect

This study suggests an adaptive linear position control of a car moved by an armature-controlled DC motor. In this study, Jaya optimization algorithm supported by Balloon effect (BE) is used to tune the parameters of the controller of the car position. BE is introduced to improve response of the classical Jaya algorithm in face of the external disturbance and system parameters changes. In the suggested technique, an objective function (OF) of the modified Jaya depends on the updated values of the controller gains and identified value of the motor open loop transfer function. System with the suggested controller has been evaluated in case of step load disturbance and motor parameters changes. Simulation and experimental results supported that suggested adaptive controller using modified Jaya improved the total system performance at moments of load disturbance and uncertainties of system parameters.

Ultra-Local Model-Free Predictive Current Control Based on Nonlinear Disturbance Compensation for Permanent Magnet Synchronous Motor

During motor operation, the motor parameters change, which causes parameter drift. They are also affected by internal and external unknown disturbances, which lead to reduced motor control performance, poor anti-interference performance, and low robustness. A method termed ultra-local model-free predictive current control (MFPCC) has previously been proposed to solve this problem; it uses only the input and output of the system and does not involve any motor parameters, because of which it is free of problems caused by model mismatch. However, the conventional MFPCC method requires adjustment of several control parameters and the estimated value of the total disturbance of the system has a certain deviation and a large pulsation, which result in obvious chattering of the motor output, low stability, reduced anti-interference performance, and low robustness. Therefore, this paper proposes an MFPCC method based on nonlinear disturbance compensation (NDC). This method does not involve any motor parameters, and it can more accurately and stably estimate the total system disturbance, and feedforward compensation, real-time update control information, only need to adjust two control parameters, the workload is small. Simulation results show that the proposed control method has high anti-interference performance, high robustness, small output ripple, and improved dynamic characteristics and that it can estimate the system disturbance accurately and stably.

Modified Rotor Flux Estimators for Stator-Fault-Tolerant Vector Controlled Induction Motor Drives

This paper deals with fault-tolerant control (FTC) of an induction motor (IM) drive. An inter-turn short circuit (ITSC) of the stator windings was taken into consideration, which is one of the most common internal faults of induction machines. The sensitivity of the classic, well-known voltage and current models to the stator winding faults was analyzed. It has been shown that these classical state variable estimators are sensitive to induction motor parameter changes during stator winding failure, which results in unstable operation of the direct field-oriented control (DFOC) drive. From a safety-critical applications point of view, it is vital to guarantee stable operation of the drive even during faults of the machine. Therefore, a new FTC system has been proposed, which consists of new modified rotor flux estimators, robust to stator winding faults. A detailed description of the proposed system is presented herein, as well as the results of simulation and experimental tests. Simulation analyses were performed using MATLAB/Simulink software. Experimental tests were carried out on the experimental test bench with a dSpace DS1103 card. The proposed solution could be applied as an alternative rotor flux estimation technique for the modern FTC drive.

Current closed‐loop control and field orientation analysis of an induction motor in six‐step operation for railway applications

In railway traction drive systems, six-step operation is widely used for motors in a flux-weakening region. Traditional vector control algorithms in six-step operation cannot work effectively due to the limitation of a single degree of freedom. This study analyses the dq current coupling relationship when the voltage amplitude is limited and applies a current closed-loop control strategy in six-step operation. This study proposes a proper switching control strategy to achieve a dual-mode control for induction motors in a full-speed region. The accuracy of field orientation is affected by changes in motor parameters and plays a key role in current control precision. This study analyses the effect of field orientation error on motor six-step operation. It is found that the proposed current closed-loop control strategy can correct the field orientation error and guarantee the motor current to track the reference precisely. A case study of a 5.5 kW experimental platform is presented to validate the control schemes.

Age-dependent changes in cardiac performance, motor function, QoL, and mental status in metoprolol-treated chronic heart failure patients

No previous study reports the effect of age on cardiac performance, motor function and quality of life (QoL) in Chinese chronic heart failure (CHF) patients. This single-center, prospective study enrolled CHF patients with resting heart rate (RHR) > 80 bpm, who were treated with metoprolol and were followed up at 1, 3, 6, and 12 months. Changes in cardiac, motor, and QoL parameters between patients aged ≥60 years and those aged <60 years were compared at all time points. P < 0.05 was considered significant. A total of 154 patients were enrolled (median age: 66.39 years; 116 aged ≥60 years, 38 aged <60 years; 95% New York Heart Association class III-IV). RHR decreased significantly in both patient groups (P < 0.0001 for both groups). Patients aged ≥60 years had a significant improvement in both ejection fraction (EF) at 6 and 12 months and in cardiac index (CI) at 3, 6, and 12 months. However, no major difference was observed in motor function in both groups. Significantly higher SF-8 scores showed greater improvement in QoL in the <60 age group at 12 months (P = 0.0008). Metoprolol demonstrated improvement in cardiac performance, motor function, QoL, and anxiety with increase in depression and burnout in both genders; however, the findings were independent of age.