Luenberger observer-based sensor fault detection: online application to DC motor

Abstract

Abstract:The integration of a capacitor-commutated converter (CCC) high-voltage direct current (HVDC) (CCC-HVDC) and voltage source converter (VSC) HVDC (VSC-HVDC) is proposed in this paper to supply entirely passive AC networks. The key point of this integration is the flat characteristic of the DC voltage of the CCC-HVDC, which provides the condition for the VSC to connect to the CCC DC link via a current regulator. The advantages of the proposed combined infeeding system are the requirement of only one DC line, and better dynamic responses. The structure of the proposed infeeding system, as well as its control system, is studied. Simulation results are provided to validate the effectiveness of the proposed system and its control strategy. Two other schemes for infeeding AC passive networks are studied to demonstrate the advantages of the proposed system.

Design of Observer-Based Fault Detection Structure for Unknown Systems using Input–Output Measurements: Practical Application to BLDC Drive

“…The results show that the estimated error of the proposed observer is less than the estimated error of the traditional observers. Finally, all experimental results are presented in this article; in addition, the results that were published in (Alkaya and Eker, 2014;Tarantino et al, 2000) have advocated that the proposed observer's work is a good estimator for FD purposes.…”

“…7-11). Alternatively, any change result from other sources (noise, disturbers) will be considered as a fault, and the false fault alarm will be increased (Alkaya and Eker, 2014;Eissa et al, 2015a,b;Isermann, 2006) Four faults have been detected using the proposed observer, namely abrupt fault, incipient fault, intermittent fault and the sensor faultier fault. In normal cases, the proposed observer's estimation error has been compared with the classical Luenberger, as shown in Table 1.…”

“…In Yang et al (1999), Kalman filter has been established to diagnose faults, whereas a hybrid genetic adaptive neuro-fuzzy inference system has been implemented for fault classification. A failure prediction method of preventing maintenance on a DC motor using state estimation through Kalman filtering has been introduced by Alkaya and Eker (2014). The sensor faults were detected using a Luenberger observer for DC motor by Tarantino et al (2000) and BLDC motor by Eissa et al (2015a,b).…”

Real Time Implementation of an Improved Hybrid Fuzzy Sliding Mode Observer Estimator

“…L represents an appropriate designed linear gain matrix, similar to Luenberger Observer gain matrix for linear systems [11], [13] [18] and M is an appropriate designed nonlinear gain matrix that multiplies the common sign function, as in [1] and [16], [18]. In reality they represent two key tuning parameters to control the SMO performance.…”

Speed Sensor Faults Diagnosis in an Induction Motor Vector Controlled Drive

“… Gain fault where the encoder signal is amplified [13].  Intermittent or total loss of feedback information [14][15][16][17][18][19][20][21][22][23][24]. In tachometric sensors, either DC generators or alternators, the intermittent fault is usually due to rotor eccentricity [15,25] or attrition of the brushes or bearings.…”