Vehicle lateral dynamics estimation using unknown input observer

Youssfi, Naoufal El; Oudghiri, Mohammed; Bachtiri, Rachid El

doi:10.1016/j.procs.2019.01.063

Cited by 12 publications

(11 citation statements)

References 13 publications

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“…In fact, this technique allows obtaining an exact T-S representation without information loss on a compact set of the state space. By using identification and linearization of the cornering forces on the vehicle which can be approximated as in [20,27], they are given by the following expressions:…”

Section: T-s Fuzzy Representation For Vehicle Lateral Dynamicsmentioning

confidence: 99%

“…Theorem 2. For given positive scalars λ k , the states and faults of system (15) are estimated asymptotically with observer (20) Unknown input observer Vehicle lateral dynamics if there exist the matrices N i , G i , L i , H, R, Y, and Q i and positive symmetric matrix P i such that (33)-( 35) hold.…”

Section: Stability Analysis and Design Of A Relaxed Unknown Input Observermentioning

confidence: 99%

“…Generally, these unknown inputs come from sensor faults, modeling errors, disturbances, or noise [19]. To overcome these limits, the Unknown Input Observer (UIO) is widely studied in the literature [20][21][22], and it makes it possible to reconstruct system states even in the presence of unknown inputs and often intervenes in diagnosis, for fault detection, sensor monitoring, and estimation of disturbances affecting the system.…”

Section: Introductionmentioning

confidence: 99%

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Relaxed State and Fault Estimation for Vehicle Lateral Dynamics Represented by T–S Fuzzy Systems

Youssfi

Bachtiri

Zoulagh

et al. 2020

Journal of Control Science and Engineering

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This paper deals with the problem of observer design of the vehicle model which is represented by Takagi–Sugeno (T–S) fuzzy systems with the presence of uncertainties. A relaxed observer design is presented to estimate the unmeasurable states and the faults of the vehicle lateral dynamics model, simultaneously. The vehicle model is transformed into a system with unknown inputs. Then, it is rebuilt by adding the default to the system state equation. Based on the Lyapunov function approach and the introduction of some slack variables, sufficient conditions of unknown input observer design are formulated as Linear Matrix Inequalities (LMIs). Finally, the simulation section clearly shows the importance and effectiveness of the proposed strategy.

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Section: T-s Fuzzy Representation For Vehicle Lateral Dynamicsmentioning

confidence: 99%

Section: Stability Analysis and Design Of A Relaxed Unknown Input Observermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Relaxed State and Fault Estimation for Vehicle Lateral Dynamics Represented by T–S Fuzzy Systems

Youssfi

Bachtiri

Zoulagh

et al. 2020

Journal of Control Science and Engineering

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“…However, a nonlinear model must be considered in the case of an increasing slip. To solve this problem, Recent studies such as [12,20], suggest that a model with two T-S fuzzy rules represent the nonlinear behavior of lateral forces. We introduce in this analysis, an approach to describing the behavior of these forces via a T-S fuzzy fourruler model.…”

Section: T-s Fuzzy Vehicle Model and Problem Formulationmentioning

confidence: 99%

“…The H ∞ Control For Vehicle Active Suspension Systems In Finite Frequency Domain is studied in [11]. The authors propose a technique to estimate the vehicle states and the crosswind in [10,12], In order to improve the stability of the vehicle as well as its safety despite the presence of parametric/modeling disturbances.…”

Section: Introductionmentioning

confidence: 99%

Static output-feedback $$H_\infty$$ control for T–S fuzzy vehicle lateral dynamics

et al. 2019

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This paper deals with static output-feedback H ∞ control for a system of the vehicle lateral dynamics, represented by Takagi-Sugeno (T-S) fuzzy models. Sufficient conditions of the existence of H ∞ control based on the static output-feedback are presented. The bilinear matrix inequalities are converted to a set of linear matrix inequalities, with the aid of some special derivations. Simulation results demonstrate the effectiveness of the proposed method.

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Estimation and fault diagnosis for non‐linear system with time‐varying faults and measurement noises: Application on two CSTRs in series

Bzioui

Channa

2022

Can J Chem Eng

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A continuously stirred tank reactor (CSTR) is largely used in water treatment and in chemical and biological processes. It is characterized by a complex non‐linear behaviour. Operating large reactors in industry can be expensive, so a common trick used to reduce costs is to operate multiple CSTRs in series. Consequently, the CSTR is usually exposed to faults and noises. This paper addresses the design of a robust observer for estimation and fault diagnosis strategy on two CSTRs in series. The considered system is affected simultaneously by time‐varying actuator and sensor faults with measurement noises. The Takagi‐Sugeno multimodel approach is proposed to transform the non‐linear model into an interpolation of several linear sub‐models with non‐measurable premise variables. The purpose of this brief is to provide the state and the fault estimation for the considered system using a proportional multiple integral (PMI) unknown input observer. The exponential stability conditions are studied with the Lyapunov theory and L2 optimization and formulated in terms of linear matrix inequalities. In addition, a comparative study with a PMI observer is conducted. Finally, the proposed observer is used for time‐varying fault detection and isolation.

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Vehicle lateral dynamics estimation using unknown input observer

Cited by 12 publications

References 13 publications

Relaxed State and Fault Estimation for Vehicle Lateral Dynamics Represented by T–S Fuzzy Systems

Relaxed State and Fault Estimation for Vehicle Lateral Dynamics Represented by T–S Fuzzy Systems

Static output-feedback $$H_\infty$$ control for T–S fuzzy vehicle lateral dynamics

Estimation and fault diagnosis for non‐linear system with time‐varying faults and measurement noises: Application on two CSTRs in series

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