Gene

Quantum mechanics

Control (management)

Rotor (electric)

Engineering

Fault detection and isolation

Control engineering

Robustness (evolution)

Actuator

Current sensor

Convergence (economics)

Synchronous motor

Economics

Biochemistry

Computer science

Fault (geology)

Seismology

Geology

Current (fluid)

Mechanical engineering

Physics

Nonlinear system

Offset (computer science)

Position (finance)

Artificial intelligence

Position sensor

Observer (physics)

Chemistry

Programming language

Economic growth

Finance

Control theory (sociology)

Electrical engineering

IEEE Transactions on Industrial Electronics

This study proposes an advanced current and position sensor fault diagnosis mechanism for permanent magnet synchronous motor (PMSM) applications. Machine nonlinear dynamics as well as parameter and load uncertainties are addressed. The features of the results of this study are summarized as follows: 1) a proportional-type full-state observer is combined with a disturbance observer to deal with the model uncertainties, 2) a partial optimal process is introduced for determining the observer gain, 3) the concept of normalized residuals is introduced for fault diagnosis criteria, and 4) a closed-loop analysis of the convergence, performance recovery, and offset-free guarantee is provided. The performance recovery property makes the proposed algorithm robust to parameter uncertainties and load variations, and sensitive only to sensor faults. In addition, the location and type of sensor faults can be identified by the fault diagnosis criteria using the normalized residuals. The performance of the sensor fault diagnosis algorithm was experimentally verified under several credible scenarios using a 7.5-kW PMSM.

Current and Position Sensor Fault Diagnosis Algorithm for PMSM Drives Based on Robust State Observer