Adaptive Observer and Fault Tolerant Control for Takagi-Sugeno Descriptor Nonlinear Systems with Sensor and Actuator Faults

Kharrat, Dhouha; Gassara, Hamdi; Chaabane, Mohamed

doi:10.1007/s12555-017-0546-8

Cited by 43 publications

(33 citation statements)

References 29 publications

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“…and from the above process of restricted equivalent transformation we can get (20) Combining (19) and (20) we can obtain x…”

Section: Construction Of Augmented Systemmentioning

confidence: 99%

“…Its main idea is to introduce a reference model in which the desired signal is the output of the reference model and the input of the reference model (called the reference input) is often known and then design the controller of the fault system to realize the output tracking for the reference model. In recent years, there have been some achievements in fault-tolerant control of descriptor systems [17][18][19][20][21], but most of them were based on robust fault-tolerant control. At present, the research results of model following control for descriptor systems are relatively few.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Impulse Elimination and Fault‐Tolerant Preview Controller Design for a Class of Descriptor Systems

Jia

Liao

Deng

2019

Mathematical Problems in Engineering

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In this paper, a fault-tolerant preview controller is designed for a class of impulse controllable continuous time descriptor systems with sensor faults. Firstly, the impulse is eliminated by introducing state prefeedback; then an algebraic equation and a normal control system are obtained by restricted equivalent transformation for the descriptor system after impulse elimination. Next, the model following problem in fault-tolerant control is transformed into the optimal regulation problem of the augmented system which is constructed by a general method. And the final augmented system and its corresponding performance index function are obtained by state feedback for the augmented system constructed above. The controller with preview effect for the final augmented system is attained based on the existing conclusions of optimal preview control; then, the fault-tolerant preview controller for the original system is obtained through integral and backstepping. The relationships between the stabilisability and detectability of the final augmented system and the corresponding characteristics of the original descriptor system are also strictly discussed. The effectiveness of the proposed method is verified by numerical simulation.

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“…and from the above process of restricted equivalent transformation we can get (20) Combining (19) and (20) we can obtain x…”

Section: Construction Of Augmented Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Impulse Elimination and Fault‐Tolerant Preview Controller Design for a Class of Descriptor Systems

Jia

Liao

Deng

2019

Mathematical Problems in Engineering

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“…A major advantage is that it provides an efficient design strategy for representing a nonlinear system. As a result, many researchers have become interested in the FTC approach for T-S fuzzy systems (see [10][11][12]).…”

Section: Introductionmentioning

confidence: 99%

“…Remark 1. The calculation of the observer and controller gains is done independently in [11,21], which is restrictive. Therefore, in this study, the resolution of the LMIs is carried out in one step.…”

mentioning

confidence: 99%

T-S Fuzzy Observers to Design Actuator Fault-Tolerant Control for Automotive Vehicle Lateral Dynamics

Youssfi¹,

Bachtiri²

2021

Smart Cities - Their Framework and Applications

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This article presents a fault-tolerant control (FTC) procedure for the automotive vehicle lateral dynamics (AVLD) described by the Takagi-Sugeno (T-S) fuzzy models. This approach focuses on actuator faults, which requires knowledge of the system parameters and the faults that are occurring. For this reason, T-S fuzzy observers are suitable for simultaneously estimating system states and actuator faults. The proposed control makes it possible to maintain vehicle stability even in the presence of faults. The design of fuzzy observers and fuzzy controllers is mainly based on the one-step method of Lyapunov, which is provided in the form of linear matrix inequalities (LMIs). The simulation results clearly illustrate the effectiveness of the applied controller strategy to maintain vehicle stability.

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“…Evolving fuzzy systems (eFS) [18] are universal approximators whose parameters and rule-based structure are updated from never-ending data streams, potentially subject to changes. eFS have been effectively employed in systems identification [5], filtering [22], prediction [8] [16], missing data handling [11], classification [2] [25], image recognition [12], fault detection [14] [19], fault prognostics [6] [7], and robust control [17] [23], to mention some.…”

Section: Introduction 1contextualizationmentioning

confidence: 99%

Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model

Leite¹,

Coutinho²,

Bessa³

et al. 2021

Preprint

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We present a method for incremental modeling and time-varying control of unknown nonlinear systems. The method combines elements of evolving intelligence, granular machine learning, and multi-variable control. We propose a State-Space Fuzzy-set-Based evolving Modeling (SS-FBeM) approach. The resulting fuzzy model is structurally and parametrically developed from a data stream with focus on memory and data coverage. The fuzzy controller also evolves, based on the data instances and fuzzy model parameters. Its local gains are redesigned in real-time -whenever the corresponding local fuzzy models change -from the solution of a linear matrix inequality problem derived from a fuzzy Lyapunov function and bounded input conditions. We have shown one-step prediction and asymptotic stabilization of the Henon chaos.

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Adaptive Observer and Fault Tolerant Control for Takagi-Sugeno Descriptor Nonlinear Systems with Sensor and Actuator Faults

Cited by 43 publications

References 29 publications

Impulse Elimination and Fault‐Tolerant Preview Controller Design for a Class of Descriptor Systems

Impulse Elimination and Fault‐Tolerant Preview Controller Design for a Class of Descriptor Systems

T-S Fuzzy Observers to Design Actuator Fault-Tolerant Control for Automotive Vehicle Lateral Dynamics

Incremental Learning and State-Space Evolving Fuzzy Control of Nonlinear Time-Varying Systems with Unknown Model

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