Observer-Based Fault Detection With Fuzzy Variable Gains and Its Application to Industrial Servo System

Eissa, M. Abdullah; Sali, Aduwati; Hassan, Mohd Khair; Bassiuny, A. M.; Darwish, R. R.

doi:10.1109/access.2020.3010125

Cited by 9 publications

(6 citation statements)

References 40 publications

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“…The work of [19] presents robust observer-based open-circuit faults for industrial permanent-magnet synchronous motor, and then, [20] introduces a new robust observer to detect the faults in an induction motor. In [21,22] Fuzzy logic is used to improve the performance of observer-based fault detection approaches.…”

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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“…In recent years, researchers have used many intelligent methods for tuning PID parameters, such as the Fuzzy method [27] [28][29] [30][31] [32] [33] [34] [35] [36], Neural Network [37] [38] [39][40] [41] [42], the Ant colony method [43] [44], the Genetic Algorithm method and the Particle Swarm Optimization (PSO) method [45] [46][47] [48].…”

Section: Introductionmentioning

confidence: 99%

The Efficiency of an Optimized PID Controller Based on Ant Colony Algorithm (ACO-PID) for the Position Control of a Multi-articulated System

Baghli,

Lakhal,

Kadi

2023

Journal of Robotics and Control

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In this article, a robot manipulator is controlled by the PID controller in a closed loop system with unit feedback. The difficulty of using the controller is parameter tuning, because the tuning parameters still use the trial and error method to find the PID parameter constants, namely Proportional Gain (Kp), Integral Gain (Ki) and Derivative Gain (Kd). In this case the Ant colony Optimization algorithm (ACO) is used to find the best gain parameters of the PID. The Ant algorithm is a method of combinatorial optimization, which utilizes the pattern of ants search for the shortest path from the nest to the place where the food is located, this concept is applied to tuning PID parameters by minimizing the objective function such that the robot manipulator has improved performance characteristics. This work uses the Matlab Simulink environment, First, after obtaining the system model, the ant colony algorithm is used to determine the proper coefficients 𝐾p, 𝐾i, and Kd in order to minimize the trajectory errors of the two joints of the robot manipulator. Then, the parameters will implement in the robot system. According to the results of the computer simulations, the proposed method (ACO-PID) gives a system that has a good performance compared with the classical PID.

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“…Another technique based on a robust fault estimation observer has been introduced for estimating actuator faults for a class of discrete-time singular systems [21]. In [22], a design of an adaptive observer is proposed for detecting sensor faults of an industrial servo system. For the fault diagnosis and reconstruction of the faults affecting the states of the system, in [23] suggested a new augmented linear parameter-varying (LPV) observer for a class of LPV models.…”

Section: Introductionmentioning

confidence: 99%

State and fault estimation based on fuzzy observer for a class of Takagi-Sugeno singular models

Ouarid

Essabre

Assoudi

et al. 2022

IJEECS

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Singular nonlinear systems have received wide attention in recent years, and can be found in various applications of engineering practice. On the basis of the Takagi-Sugeno (T-S) formalism, which represents a powerful tool allowing the study and the treatment of nonlinear systems, many control and diagnostic problems have been treated in the literature. In this work, we aim to present a new approach making it possible to estimate simultaneously both non-measurable states and unknown faults in the actuators and sensors for a class of continuous-time Takagi-Sugeno singular model (CTSSM). Firstly, the considered class of CTSSM is represented in the case of premise variables which are non-measurable, and is subjected to actuator and sensor faults. Secondly, the suggested observer is synthesized based on the decomposition approach. Next, the observer’s gain matrices are determined using the Lyapunov theory and the constraints are defined as linear matrix inequalities (LMIs). Finally, a numerical simulation on an application example is given to demonstrate the usefulness and the good performance of the proposed dynamic system.

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Observer-Based Fault Detection With Fuzzy Variable Gains and Its Application to Industrial Servo System

Cited by 9 publications

References 40 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

The Efficiency of an Optimized PID Controller Based on Ant Colony Algorithm (ACO-PID) for the Position Control of a Multi-articulated System

State and fault estimation based on fuzzy observer for a class of Takagi-Sugeno singular models

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