Unknown Input Observer Design for a Class of Discrete-Time Takagi-Sugeno Implicit Systems

Essabre, Mohamed; Bouatmani, El Mahfoud El; Soulami, Jalal; Assoudi, Abdellatif El; Yaagoubi, El Hassane El

doi:10.1109/cadiag.2018.8751310

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…Similarly, in the case of discrete-time T-S models, various publications published for explicit and implicit structures such as [15]- [20]. Essabre et al [21] suggest a technique for constructing an observer for a class of T-S implicit systems subject to UIs utilizing measurable premise variables that are dependent on the measurable states, input, output, or external parameters. Yoneyama [22], it is confirmed that even if the output of the system is selected as a premise variable and this output is directly impacted by perturbations (which seems to be the case in majority of realistic conditions), the T-S system acquired does not represent an exactly nonlinear system.…”

Section: Introductionmentioning

confidence: 99%

“…Motivated by the above discussions, the purpose of our study is not to compare our technique to previous ones, but rather to generalize our results from the case of T-S implicit models with measurable premise variables [21] to the case of T-S implicit models with unmeasurable premise variables. Using the singular value decomposition technique, the fundamental contribution of this research is to develop a UI observer design for a class of discrete-time Takagi-Sugeno implicit systems (DTSISs) models with unmeasurable premise variables, allowing for the estimate of UIs and unknown states at the same time.…”

Section: Introductionmentioning

confidence: 99%

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Design of unknown input observer for discrete-time Takagi Sugeno implicit systems with unmeasurable premise variables

Essabre

Hmaiddouch²,

Assoudi³

et al. 2023

Bulletin EEI

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In this study, an unknown input observer (UIO) is developed in explicit form to estimate unmeasurable states and unknown inputs (UIs) for nonlinear implicit systems represented by the discrete-time Takagi-Sugeno implicit systems (DTSIS) in the case of unmeasurable premise variables. The method employed is based on singular value decomposition (SVD) and augmenting the state vector, which is formed partly by the system state and partly by the UIs. The convergence of the augmented state estimation error is provided by a Lyapunov function ending with solving the linear matrix inequalities (LMI). An application to a model of the rolling disc is considered to evaluate the effectiveness of the developed approach. It appears that estimated variables converge to the true variables quickly and accurately.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design of unknown input observer for discrete-time Takagi Sugeno implicit systems with unmeasurable premise variables

Essabre

Hmaiddouch²,

Assoudi³

et al. 2023

Bulletin EEI

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show abstract

“…Various studies has investigated the issues related to state and unknown input estimation [21][22][23], as well as state and faults estimation [24,25] and many approaches has been the objective of fuzzy observer design as in [21,24] when authors use the Lipschitz constraints. In other side other approach has been applied by authors in [23,25] based on the separation between dynamic and static relations in T-S singular model.…”

Section: Introductionmentioning

confidence: 99%

Discrete-time Takagi-Sugeno singular systems with unmeasurable decision variables: state and fault fuzzy observer design

2023

Archives of Control Sciences

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The studied problem in this paper, treat the issue of state and fault estimation using a fuzzy observer in the case of unmeasurable decision variable for Discrete-Time Takagi-Sugeno Singular Sytems (DTSSS). First, an augmented system is introduced to gather state and fault into a single vector, then on the basis of Singular Value Decomposition (SVD) approach, this observer is designed in explicit form to estimate both of state and fault of a nonlinear singular system. The exponential stability of this observer is studied using Lyapunov theory and the convergence conditions are solved with Linear Matrix Inequalities (LMIs). Finally a numerical example is simulated, and results are given to validate the offered approach.

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Sensor Fault Diagnosis in T-S Fuzzy Discrete Descriptor Systems using Design a New Unknown Input Observer

Mirshahi,

Shafiee,

Suratgar

2024

2024 32nd International Conference on Electrical Engineering (ICEE)

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Unknown Input Observer Design for a Class of Discrete-Time Takagi-Sugeno Implicit Systems

Cited by 3 publications

References 25 publications

Design of unknown input observer for discrete-time Takagi Sugeno implicit systems with unmeasurable premise variables

Design of unknown input observer for discrete-time Takagi Sugeno implicit systems with unmeasurable premise variables

Discrete-time Takagi-Sugeno singular systems with unmeasurable decision variables: state and fault fuzzy observer design

Sensor Fault Diagnosis in T-S Fuzzy Discrete Descriptor Systems using Design a New Unknown Input Observer

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