Sensors Fault Diagnosis and Active Fault-Tolerant Control for PMSM Drive Systems Based on a Composite Sliding Mode Observer

Zhu, Qiuguo; Li, Zhaoyang; Tan, Xitang; Xie, Dabo; Dai, Wei

doi:10.3390/en12091695

Cited by 17 publications

(12 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is multivariable and nonlinear, has strong coupling and interference sensitivity, and is a multirotor unmanned aerial vehicle with strong maneuverability and simple structure. The micro-multirotor drone has the following advantages: small size and lightweight, low requirements for the working platform and space environment, even the requirements for take-off and landing space are not high [2]. It can be in a relatively small and enclosed space; in order to complete the specified tasks, the flight altitude requirements are low; it can work close to the ground; and the requirements for the working environ-ment are also low-even if it is complex and harsh, it can work [3].…”

Section: Introductionmentioning

confidence: 99%

Sensor Fault Diagnosis and Fault Tolerant Control of Quadrotor UAV Based on Genetic Algorithm

Hua

Zhang

et al. 2022

Journal of Sensors

View full text Add to dashboard Cite

The quadrotor drone is small in size and light in weight, the mechanical structure is simple, and the requirements for the working environment are low. The development of a quadrotor UAV technology is also the focus of the current technical personnel. The author proposes a four-rotor UAV sensor fault diagnosis and fault-tolerant control based on genetic algorithm and introduces common sensor failures, and based on the improved BP neural network of the GA algorithm, the genetic algorithm is improved. This paper uses a classical BP algorithm, a classical GA-BP algorithm, and an improved GA-BP algorithm for training. Using a total of 150 sets of training data and training function using LevenbregMarquardt (trainlm), MeanSquaredError (performance function using mse), in the same noise background, the improved GA-BP algorithm has the highest detection rate, the classical GA-BP algorithm followed, and classical BP algorithm is the worst. Therefore, using the improved GA-BP algorithm, various errors of the sensor can be detected quickly and accurately.

show abstract

Section: Introductionmentioning

confidence: 99%

Sensor Fault Diagnosis and Fault Tolerant Control of Quadrotor UAV Based on Genetic Algorithm

Hua

Zhang

et al. 2022

Journal of Sensors

View full text Add to dashboard Cite

show abstract

“…A selection on switching surface and the existing of QSMC is also considered in this reference. A composite sliding mode observer is proposed in [20] to study multi-sensor fault diagnosis and active fault-tolerant control in a PMSM drive system. For the FDI of a class of uncertain Lipschitz nonlinear systems, an adaptive robust sliding mode observer (SMO) is proposed in [21], where both external disturbance and faults are considered.…”

Section: Introductionmentioning

confidence: 99%

Generalized Sliding Mode Observers for Simultaneous Fault Reconstruction in the Presence of Uncertainty and Disturbance

et al. 2022

View full text Add to dashboard Cite

In this paper, a generalized sliding mode observer design method is proposed for the robust reconstruction of sensors and actuators faults in the presence of both unknown disturbances and uncertainties. For this purpose, the effect of uncertainty and disturbance on the system has been considered in generalized state-space form, and the LMI tool is combined with the concept of an equivalent output error injection method to reduce the effects of them on the reconstruction process. The upper bound of the disturbance and uncertainty are minimized in the design of the sliding motion so that the reconstruction of the faults will be minimized. The design method is applied for actuator faults in the generalized state-space form, and then with some suitable filtering, the method extends as sensors and actuators coincidentally faults. Since in the proposed approach, the state trajectories do not leave the sliding manifold even in simultaneous sensors and actuators faults, then the faults are reconstructed based upon information retrieved from the equivalent output error injection signal. Due to the importance of the robust fault reconstruction in the wind energy conversion system (WECS), the proposed approach is successfully applied to a 5 MW wind turbine system. The simulation results verify the robust performances of the proposed approach in the presence of unknown perturbations and uncertainties.

show abstract

“…The second type uses the motor speed parameters (such as the back-EMF) in the motor fundamental excitation mathematical model to estimate the rotor position and speed, which has significant dynamic performance but is only suitable for the operation range of medium and high-speed. The commonly used fundamental back-EMF observation algorithms include SMO [6][7][8][9], model reference adaptive [10][11], and extended Kalman filter [12]. SMO has been widely studied because of its simple implementation, insensitivity to parameter changes, and external interference [13].…”

Section: Introductionmentioning

confidence: 99%

Speed Sensor‐Less Control System of Surface‐Mounted Permanent Magnet Synchronous Motor Based on Adaptive Feedback Gain Supertwisting Sliding Mode Observer

Zhang

Bai

2021

Journal of Sensors

View full text Add to dashboard Cite

Aiming at the problems of severe chattering and difficulty in low-speed operation of the surface-mounted permanent magnet synchronous motor (SPMSM) sensor-less speed control system based on the traditional sliding mode observer (SMO), this paper proposes a sensor-less control strategy of supertwisting sliding mode observer based on adaptive feedback gain (AFG-STA-SMO). This strategy combines the supertwisting algorithm (STA) with the equivalent feedback principle and designs an adaptive law to compensate for the rotor position error by adjusting the feedback gain coefficient online. Secondly, considering the ripple component in the back electromotive force (back-EMF), the Kalman filter gets a smoother back-EMF signal, further improving the rotor position estimation accuracy. The stability of the system is proved by using the Lyapunov function. Finally, the feasibility and effectiveness of the proposed control strategy are verified by MATLAB/Simulink simulation.

show abstract

Sensors Fault Diagnosis and Active Fault-Tolerant Control for PMSM Drive Systems Based on a Composite Sliding Mode Observer

Cited by 17 publications

References 25 publications

Sensor Fault Diagnosis and Fault Tolerant Control of Quadrotor UAV Based on Genetic Algorithm

Sensor Fault Diagnosis and Fault Tolerant Control of Quadrotor UAV Based on Genetic Algorithm

Generalized Sliding Mode Observers for Simultaneous Fault Reconstruction in the Presence of Uncertainty and Disturbance

Speed Sensor‐Less Control System of Surface‐Mounted Permanent Magnet Synchronous Motor Based on Adaptive Feedback Gain Supertwisting Sliding Mode Observer

Contact Info

Product

Resources

About