Anti-Disturbance Speed Control of Permanent Magnet Synchronous Motor Based on Fractional Order Sliding Mode Load Observer

Lu, En; Li, Wei; Jiang, Song; Liu, Yuanyuan

doi:10.1109/access.2022.3214205

Cited by 3 publications

(4 citation statements)

References 28 publications

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“…This method provides a new option for the establishment of an engine output torque model. (2) In this study, a prediction model of the engine output torque was established, and the RLS algorithm was used to estimate the road rolling resistance coefficients of tracked vehicles under certain driving conditions. The experimental results showed that when the tracked vehicle was driving on a sand road and a cement road, the rolling resistance coefficient of the road could be automatically estimated and had high accuracy when the vehicle driving state satisfied the set driving conditions.…”

Section: Discussionmentioning

confidence: 99%

“…A driving road is complex and changeable, and the demands on the dynamics and safety of tracked vehicles are high [1]. The road parameters affect the acceleration, braking, and steering performance of vehicles, and they are important parameters for risk assessment and active safety control during tracked vehicle driving [2]. Road parameter estimation is of great significance for improving the safety and dynamic performance of vehicles [3].…”

Section: Introductionmentioning

confidence: 99%

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Research on the Prediction Model of Engine Output Torque and Real-Time Estimation of the Road Rolling Resistance Coefficient in Tracked Vehicles

Jia,

Liu,

Jia

et al. 2023

Sensors

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Road parameter identification is of great significance for the active safety control of tracked vehicles and the improvement of vehicle driving safety. In this study, a method for establishing a prediction model of the engine output torques in tracked vehicles based on vehicle driving data was proposed, and the road rolling resistance coefficient f was further estimated using the model. First, the driving data from the tracked vehicle were collected and then screened by setting the driving conditions of the tracked vehicle. Then, the mapping relationship between the engine torque Te, the engine speed ne, and the accelerator pedal position β was obtained by a genetic algorithm–backpropagation (GA–BP) neural network algorithm, and an engine output torque prediction model was established. Finally, based on the vehicle longitudinal dynamics model, the recursive least squares (RLS) algorithm was used to estimate the f. The experimental results showed that when the driving state of the tracked vehicle satisfied the set driving conditions, the engine output torque prediction model could predict the engine output torque T^e in real time based on the changes in the ne and β, and then the RLS algorithm was used to estimate the road rolling resistance coefficient f^. The average coefficient of determination R of the T^e was 0.91, and the estimation accuracy of the f^ was 98.421%. This method could adequately meet the requirements for engine output torque prediction and real-time estimation of the road rolling resistance coefficient during tracked vehicle driving.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on the Prediction Model of Engine Output Torque and Real-Time Estimation of the Road Rolling Resistance Coefficient in Tracked Vehicles

Jia,

Liu,

Jia

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…In the control of motors, it is usually assumed that the magnetic field is sinusoidal distributed, the three-phase windings are symmetrical and the electromagnetic thrust of the motor is proportional to the q-axis current [4]. The three-phase windings are not symmetrical due to end effects.…”

Section: Mathematical Modellingmentioning

confidence: 99%

Vector Control Simulation of Permanent Magnet Synchronous Linear Motor

Dai,

Wang,

Zhao

2024

J. Phys.: Conf. Ser.

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Compared with rotating motor, linear motor can “directly” obtain linear motion, which eliminates the intermediate transformation link and can directly drive the equipment requiring linear motion. It is applicable to rotating motor mature control strategy can be better for linear motor control research. Its development and application of linear motor has great significance. In this thesis, starting from the weakening characteristics of permanent magnet synchronous linear motor, through the MATLAB simulation and comparative analysis of different control signals (SPWM and SVPWM) of vector control strategy, the conclusion that vector control strategy can effectively control ideal linear motor is obtained, which lays a foundation for further improving the control strategy to control non-ideal linear motor.

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“…W ITH the rapid development of power electronics technology, high-frequency high-power switching devices and new control theory, permanent magnet synchronous motors (PMSMs) have been more and more widely used in many fields [1]- [3]. However, in the actual operation, the controlled object of the PMSM servo system is typically nonlinear because of the obvious external disturbances and system delay, and in addition, conventional linear controllers, e.g., proportional integral control (PIC) [4] and active disturbance rejection control (ADRC) [5], are utilized to adjust the tracking performance but cannot maintain the satisfactory control performance when the system is in the operation conditions of time-varying load inertia or load torque.…”

Section: Introductionmentioning

confidence: 99%

Parallel Self-Tuning Controllers for Speed Servo System Based on Predictive Model-Mismatch Compensation

Dan,

He,

et al. 2024

IEEE Access

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When the operating conditions are changed suddenly, the model mismatch for the servo system using model-based methods occurs during the identification convergence, which will lead to the obvious speed spikes and damped oscillations, deteriorating the control performance of the servo system. To solve the problem, a parallel self-tuning scheme based on a generalized predictive control law is proposed in this paper. In the proposed scheme, the controlled model parameters in which an integral-proportional controller (IPC) is considered as the controller of speed loop are first online estimated by a recursive least squares method with a forgetting factor. Then, a model-mismatch compensator (MMC) is designed to obtain the corresponding compensation current, and in addition, the predicted speed is considered as the feedback speed to promote the establishment of an inner loop, which allows for a faster and more thorough model mismatch compensation based on both the excitation torque current and the adaptivity of the MMC. At the same time, through constructing two different quadratic performance indicators, the optimal control laws can be obtained based on a simplified decoupled derivation, thus supplying IPC and MMC with suitable control parameters simultaneously. Simulation and experimental results show that, compared with traditional methods, the proposed scheme can ensure faster convergence speed and better control performance.

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Anti-Disturbance Speed Control of Permanent Magnet Synchronous Motor Based on Fractional Order Sliding Mode Load Observer

Cited by 3 publications

References 28 publications

Research on the Prediction Model of Engine Output Torque and Real-Time Estimation of the Road Rolling Resistance Coefficient in Tracked Vehicles

Research on the Prediction Model of Engine Output Torque and Real-Time Estimation of the Road Rolling Resistance Coefficient in Tracked Vehicles

Vector Control Simulation of Permanent Magnet Synchronous Linear Motor

Parallel Self-Tuning Controllers for Speed Servo System Based on Predictive Model-Mismatch Compensation

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