Fault Detection and Isolation for Linear Structured Systems

Jia, Jiajia; Trentelman, Harry L.; Camlibel, M. Kanat

doi:10.1109/lcsys.2020.2995239

Cited by 6 publications

(6 citation statements)

References 19 publications

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“…Obviously, tests for structural observability of networks can be obtained by dualizing our results. Other structural properties of interest are, for example, input-state observability and output controllability [25], fault detection and isolation [27], and system invertibility [28] of structured networks.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Scalable controllability analysis of structured networks

Jia¹,

Shali²,

Waarde³

et al. 2020

Preprint

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This paper deals with strong structural controllability of structured networks. A structured network is a family of structured systems (called node systems) that are interconnected by means of a structured interconnection law. The node systems and their structured interconnection law are given by pattern matrices. It is shown that a structured network is strongly structurally controllable if and only if an associated structured system is. This structured system will in general have a very large state space dimension, and therefore existing tests for verifying strong structural controllability are not tractable. The main result of this paper circumvents this problem. We show that controllability can be tested by replacing the original network by a new network in which all original node systems have been replaced by (auxiliary) node systems with state space dimensions either 1 or 2. Hence, controllability of the original network can be verified by testing controllability of a structured system with state space dimension at most twice the number of node systems, regardless of the state space dimensions of the original node systems.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Scalable controllability analysis of structured networks

Jia¹,

Shali²,

Waarde³

et al. 2020

Preprint

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show abstract

“…In [24] adaptive control is implemented on jet engine to compensate the sensor fault. Adaptive method for fault detection and identification in linear time invariant (LTI) systems is proposed in [25]. In the FTC system, faults are identified according to their location of occurrence in a system.…”

Section: Plos Onementioning

confidence: 99%

Fault-tolerant scheme for robotic manipulator—Nonlinear robust back-stepping control with friction compensation

2021

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Emerging applications of autonomous robots requiring stability and reliability cannot afford component failure to achieve operational objectives. Hence, identification and countermeasure of a fault is of utmost importance in mechatronics community. This research proposes a Fault-tolerant control (FTC) for a robot manipulator, which is based on a hybrid control scheme that uses an observer as well as a hardware redundancy strategy to improve the performance and efficiency in the presence of actuator and sensor faults. Considering a five Degree of Freedom (DoF) robotic manipulator, a dynamic LuGre friction model is derived which forms the basis for design of control law. For actuator’s and sensor’s FTC, an adaptive back-stepping methodology is used for fault estimation and the nominal control law is used for the controller reconfiguration and observer is designed. Fault detection is accomplished by comparing the actual and observed states, pursued by fault tolerant method using redundant sensors. The results affirm the effectiveness of the proposed FTC strategy with model-based friction compensation. Improved tracking performance as well robustness in the presence of friction and fault demonstrate the efficiency of the proposed control approach.

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“…In each of the three problems we saw that addition and/or multiplication of pattern matrices plays an important role. We are confident that our results on pattern matrices can also be applied to other system-theoretic properties such as fault detection and isolation [95].…”

Section: Output Controllabilitymentioning

confidence: 72%

“…Such conditions based on the network topology are desirable since they give insight on the types of network structures that allow unique identification, and in addition may aid in the selection of measured nodes. Graph-theoretic methods have also been succesfully applied to assess other system-theoretic properties like structural controllability [30,96,113,142,219] and fault detection [49,95,174].…”

Section: N E T W O R K I D E N T I F I a B I L I T Y A N D G R A P H S I M P L I F I C A T I O Nmentioning

confidence: 99%

From data and structure to models and controllers

Waarde¹

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Fault Detection and Isolation for Linear Structured Systems

Cited by 6 publications

References 19 publications

Scalable controllability analysis of structured networks

Scalable controllability analysis of structured networks

Fault-tolerant scheme for robotic manipulator—Nonlinear robust back-stepping control with friction compensation

From data and structure to models and controllers

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