Detection and diagnosis of incipient faults in sensors of an LTI system using a modified GLR-based approach

Kiasi, Fariborz; Prakash, J.; Shah, Sirish L.

doi:10.1016/j.jprocont.2015.03.007

Cited by 13 publications

(17 citation statements)

References 12 publications

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“…Different types of faults such as sensor/actuator bias, faults changing system dynamics, stuck sensor and stuck actuator (controller failure), ramp-type and truncated ramp-type additive faults in sensor and actuator might be occurred in processes. [26][27][28]32,47 In this work, 2 types of the most common faults in the process industries, which are sensor bias and ramp-type additive fault in sensor, are considered. Nonetheless, the applied fault-tolerant framework can easily include other types of fault such as actuator bias and stuck actuator.…”

Section: Level 2: Ftc Proceduresmentioning

confidence: 99%

“…To make a more accurate estimation of the time of fault occurrence as well as identification of the fault (estimating the type of fault and its magnitude), M extra samples is intended and the generalized-likelihood ratio (GLR) approach is applied. Assuming occurrence of a bias with magnitude b i or a ramp-type additive fault with slope m i , the GLR test can be performed as follows [26][27][28][29] :…”

Section: Level 2: Ftc Proceduresmentioning

confidence: 99%

“…The same maximization procedure should be repeated for all hypothesized faults (all values of i). Finally, the maximum value of T i among all hypothesized faults determines the maximum likelihood estimate of the location of the fault (î) and the time of fault occurrence (t) as follows 27,28 :…”

Section: Level 2: Ftc Proceduresmentioning

confidence: 99%

“…32 Furthermore, it is assumed that ΔM(t) is a zero-mean Gaussian white noise with variance 0.01M L . 32 Paying attention to the DC motor dynamics (27), the sampling time ΔT = 0.1 seconds is selected to discretize the continuous-time model (27). By applying the zero-order-hold discretization method and considering a noise sequence for the system output, the following discrete-time model is obtained: The purpose is to design a fault-tolerant PID controller with the following structure in the fault-free case:…”

Section: Fault-tolerant Pid Control For a DC Motormentioning

confidence: 99%

“…16,25 For the aim of fault diagnosis, there are some methods based on residual generation using state observers or Kalman filters. [26][27][28][29][30] Paying attention to the importance of the fixed-order controllers in industrial applications and due to the potential threats of faults, there are several methods available in the literature for designing fault-tolerant fixed-order controllers 31,32 and fault-tolerant PID controllers. 16,17 Some of these methods rely on transforming the considered problem into a static output feedback problem.…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

Karimi

Batmani

Khosrowjerdi

2018

Optim Control Appl Methods

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In this paper, a multiobjective fault-tolerant fixed-order output feedback controller design technique is proposed for multivariable discrete-time linear systems with unmeasured disturbances. Initially, a multiobjective fixed-order controller is designed for the system by transforming the problem of tuning the parameters of the controller into a static output feedback problem and solving a mixed H 2 ∕H ∞ optimization problem with bilinear matrix inequalities.Subsequently, the fixed-order controller is used to construct the closed-loop system and an active fault-tolerant control scheme is applied using the input/output data collected from the controlled system. Motivated by its popularity in industry, the proposed method is also used to tune the parameters of proportional-integral-derivative controllers as a special case of structured controllers with the fixed order. Two numerical simulations are provided to demonstrate the design procedure and the flexibility of the proposed technique.

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Section: Level 2: Ftc Proceduresmentioning

confidence: 99%

Section: Level 2: Ftc Proceduresmentioning

confidence: 99%

Section: Level 2: Ftc Proceduresmentioning

confidence: 99%

Section: Fault-tolerant Pid Control For a DC Motormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

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Batmani

Khosrowjerdi

2018

Optim Control Appl Methods

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Decentralized active sensor fault tolerance in attitude control of satellite formation flying

Nasrolahi

Abdollahi

Rezaee

2020

Intl J Robust & Nonlinear

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This article presents a decentralized framework of active fault tolerant control for attitude synchronization in satellite formation flying. By employing a nonlinear observer and a static approximator, the fault in both the angular velocity and orientation sensors can be diagnosed whether the sensor belongs to the satellite or its neighbors. The convergence of the observer is guaranteed by utilizing Lyapunov's direct method and Barbalat's lemma. The proposed approach is based on unknown input and requires only the angular velocity and orientation of the states in a decentralized architecture. Moreover, by designing a sensor fault tolerant controller, the tracking synchronization among the satellites' attitudes with individual set-points is guaranteed and the uniformly ultimate boundedness of the synchronization/tracking errors is provided. The simulation results are presented to illustrate the performance of the developed algorithm. K E Y W O R D S attitude synchronization tracking control, nonlinear observer, satellite formation flying, sensor fault tolerance 1 INTRODUCTION Satellite formation flying (SFF) missions have been increasingly attracted in the last two decades as a promising technology in aerospace fields. 1 Its advantages include maintenance enhancement and redundancy capability. In addition, by employing SFF a large payload in a massive satellite could be replaced with multidivided microsatellites. These payloads involve with interferometry, synthetic aperture radar missions. 2 To perform these missions, some technical requirements such as attitude synchronization should b e guaranteed. 3 A main challenge to synchronize attitude in SFF is designing a reliable control system to perform attitude maneuvers among multiple satellites. Obviously, decentralized attitude control approach is a fundamental step to enhance the decision-making ability for each agent thus improving the whole reliability system. 4 In addition, it avoids any redesign process and guarantees the system stability when new system/agent is added/subtracted. 5 Additional decentralized approaches for attitude synchronization are addressed in References 6,7. However, they utilize relative angular velocity communication among satellites to design the control signal. In order to improve the SFF reliability in attitude synchronization, fault diagnosis approaches are usually employed to detect, isolate, and identify the faults. There are plenty of fault diagnosis and tolerant control approaches for single or centralized multiagent systems in the literature. However, in a decentralized control strategy, the component Abbreviations: SFF, satellite formation flying; UUB, uniform ultimate boundedness 8340

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A Data-Driven Robust Fault Detection Method for Linear Systems with Full-Order Sensors

Liu

et al. 2022

Circuits Syst Signal Process

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Detection and diagnosis of incipient faults in sensors of an LTI system using a modified GLR-based approach

Cited by 13 publications

References 12 publications

Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

Multiobjective fault‐tolerant fixed‐order/PID control of multivariable discrete‐time linear systems with unmeasured disturbances

Decentralized active sensor fault tolerance in attitude control of satellite formation flying

A Data-Driven Robust Fault Detection Method for Linear Systems with Full-Order Sensors

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