Unknown input observer design for fault sensor estimation applied to induction machine

Amrane, A.; Larabi, Abdelkader; Aïtouche, Abdel

doi:10.1016/j.matcom.2018.09.018

Cited by 18 publications

(16 citation statements)

References 23 publications

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“…In [15] two observers namely: interval observer and unknown input observer used to estimate the sensor fault estimation of the railway traction motor. Design of unknown inputs observer for sensor faults of induction machine introduced in [16].…”

Section: Iiliterature Surveymentioning

confidence: 99%

Observer-Based Fault Detection Approach Using Fuzzy Adaptive Poles Placement System With Real-Time Implementation

et al. 2021

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The conventional methods of observer poles placement in sensor fault detection usually adopt the trial-and-error methods. These methods cannot achieve global optimal performance because of their fixed poles placement and it leads to an observer with constant parameters, which could be reducing the system performance. Therefore, this paper proposes a fuzzy-based observer tuning method to optimize and adapt the selection of poles locations to determine the optimal gains of the observer, and it is experimentally applied to a composite sensor fault detection. Fuzzy logic is a promising method that could overcome the trial-and-error method challenges by introducing better adaptation and system robustness. The proposed observer structure includes adaptive tuning corresponding to an unknown input. Utilizing self-tuning for the observer correction stage, the gain is going to be updated online using the proposed fuzzy adaptive poles placement (FAPP) system. This paper validated the system simulation by implementing fault detection algorithms by using a real-time embedded observer-based system. The experimental results demonstrate the effectiveness of the proposed fuzzy-based observer schemes at detecting sensor faults in the Brushless DC (BLDC) motors, with significantly better performance than conventional counterparts' methodologies. The experiments indicate that the average estimation error is 0.146, which less by 43.8% than was obtained for high levels of noise and disturbances compared with the traditional Luenberger observer approach.

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Section: Iiliterature Surveymentioning

confidence: 99%

Observer-Based Fault Detection Approach Using Fuzzy Adaptive Poles Placement System With Real-Time Implementation

et al. 2021

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“…Equations (1)-(4) correspond to the equivalent circuit of an induction motor as presented in Figure 2. Because the angular speed ω changes much slower than the electromagnetic variables u, i and ψ, it is treated as a parameter [1,33,35,37]. Because the angular speed ω changes much slower than the electromagnetic variables u, i and ψ, it is treated as a parameter [1,33,35,37].…”

Section: Mathematical Model Of the Motormentioning

confidence: 99%

Developing Induction Motor State Observers with Increased Robustness

Białoń¹,

Pasko²,

Niestrój³

2020

Energies

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This paper presents the results of recently conducted research on Luenberger observers with non-proportional feedbacks. The observers are applied for the reconstruction of magnetic fluxes of an induction motor. Structures of the observers known from the control theory are presented. These are a proportional observer, a proportional-integral observer, a modified integral observer, and an observer with additional integrators. The practical application of some of these observers requires modifications to their structures. In the paper, the simulation results for all mentioned types of observers are presented. The simulations are performed with a Scilab-Xcos model which is attached to this paper. The problem of gains selection of the observers is discussed. Gains are selected with the described optimization method based on a genetic algorithm. A Scilab file launching the genetic algorithm also is attached to this paper.

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“…Thence, several actuator and sensor failure estimation algorithms have been developed. Actuator fault estimation is performed based on the UIO model, which is designed using the Lyapunov analysis and the linear matrix inequality (LMI) optimization algorithm to determine observer gain [28][29][30][31][32][33][34][35][36][37][38]. In [29], a UIO model is implemented utilizing Bayesian filter equations and estimates the states in two steps: time update and measurement update.…”

Section: Introductionmentioning

confidence: 99%

“…Here, the FE and FTC schemes are integrated to ensure the stability of the closed-loop system affected by gain factors. In [32], the authors focused on the estimation of the sensor faults and the state variables, in which an induction machine-based UIO model was obtained from linear parameter varying (LPV) systems and the rotation speed was considered as a variable parameter. The Lyapunov theory is a promising solution to ensure the stability of the proposed approach.…”

Section: Introductionmentioning

confidence: 99%

Robust Control Optimization Based on Actuator Fault and Sensor Fault Compensation for Mini Motion Package Electro-Hydraulic Actuator

2021

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In recent years, electro-hydraulic systems have been widely used in many industries and have attracted research attention because of their outstanding characteristics such as power, accuracy, efficiency, and ease of maintenance. However, such systems face serious problems caused simultaneously by disturbances, internal leakage fault, sensor fault, and dynamic uncertain equation components, which make the system unstable and unsafe. Therefore, in this paper, we focus on the estimation of system fault and uncertainties with the aid of advanced fault compensation techniques. First, we design a sliding mode observer using the Lyapunov algorithm to estimate actuator faults that produce not only internal leakage fault but also disturbances or unknown input uncertainties. These faults occur under the effect of payload variations and unknown friction nonlinearities. Second, Lyapunov analysis-based unknown input observer model is designed to estimate sensor faults arising from sensor noises and faults. Third, to minimize the estimated faults, a combination of actuator and sensor compensation fault is proposed, in which the compensation process is performed due to the difference between the output signal and its estimation. Finally, the numerical simulations are performed to demonstrate the effectiveness of the proposed method obtained under various faulty scenarios. The simulation results show that the efficiency of the proposed solution is better than the traditional PID controller and the sensor fault compensation method, despite the influence of noises.

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Unknown input observer design for fault sensor estimation applied to induction machine

Cited by 18 publications

References 23 publications

Observer-Based Fault Detection Approach Using Fuzzy Adaptive Poles Placement System With Real-Time Implementation

Observer-Based Fault Detection Approach Using Fuzzy Adaptive Poles Placement System With Real-Time Implementation

Developing Induction Motor State Observers with Increased Robustness

Robust Control Optimization Based on Actuator Fault and Sensor Fault Compensation for Mini Motion Package Electro-Hydraulic Actuator

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