LMI-based Adaptive Observers for Nonlinear Systems

Zhu, Jiang; Khayati, Karim

doi:10.11159/ijmem.2012.006

Cited by 5 publications

(7 citation statements)

References 17 publications

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“…In this context, conventional solutions as proposed in [20–22] have been used to overcome the effect of the presence of disturbances in both the dynamics of the system and measurements. In [21], a sufficient condition for the existence of an adaptive observer for a large class of non‐linear systems has been derived based on Lyapunov stability theory and expressed in terms of LMI. The parameters adaptation law rely on solving a partial differential equation.…”

Section: Introductionmentioning

confidence: 99%

Robust adaptive gain neural observer for a class of non‐linear systems

Abid

Krifa

Liouane

2017

IET Control Theory & Applications

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Section: Introductionmentioning

confidence: 99%

Robust adaptive gain neural observer for a class of non‐linear systems

Abid

Krifa

Liouane

2017

IET Control Theory & Applications

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“…AO in the Kalman filter form is proposed in [20]. Adaptive algorithms for filter parameters tuning are obtained as the solution of linear matrix inequalities problem.…”

confidence: 99%

“…Next, we propose the constraint algorithm for 1 W . Apple (20), (21) and modify the adaptive model (8). Obtain the current estimation for the vector P  :…”

Section: Casementioning

confidence: 99%

Structural-parametrical Design Method of Adaptive Observers for Nonlinear Systems

Karabutov¹

2018

IJISA

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Abstract-The structural-parametrical method for design of adaptive observers (AO) for nonlinear dynamic systems under uncertainty is proposed. The design of AO is consisting of two stages. The structural stage allowed identifying a class of nonlinearity and its structural parameters. The solution of this task is based on an estimation of the system structural identifiability (SI). The method and criteria of the system structural identifiability are proposed. Effect of an input on the SI is showed. We believe that the excitation constancy condition is satisfied for system variables. Requirements to the input at stages of structural and parametrical design of AO differ. The parametrical design stage AO uses the results obtained at the first stage of the adaptive observer construction. Two cases of the structural information application are considered. The main attention is focused on the case of the insufficient structural information. Adaptive algorithms for tuning of parameters AO are proposed. The uncertainty estimation procedure is proposed. Stability of the adaptive system is proved. Simulation results confirmed the performance of the proposed approach.

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“…The main contribution of this work is the proposal of a new adaptation law augmented by a switching leakage term for fault estimation. Unlike adaptation laws in [15] and [24], which relay, respectively, on solving a partial differential equation and a set of algebraic matrix equations, the proposed solution relay on a rank condition similar to the well-known observer matching condition. This makes it possible to use some conventional adaptive observer design tools.…”

Section: Introductionmentioning

confidence: 99%

“…Motivated by the works in [15] and [24], in this paper, an adaptive observer design technique for fault estimation for a class of Lipschitz nonlinear systems that do not satisfy the SPR requirement is proposed. The main contribution of this work is the proposal of a new adaptation law augmented by a switching leakage term for fault estimation.…”

Section: Introductionmentioning

confidence: 99%

Adaptive observer-based fault estimation for a class of Lipschitz nonlinear systems

Oucief

Tadjine

Labiod

2016

Archives of Control Sciences

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Fault input channels represent a major challenge for observer design for fault estimation. Most works in this field assume that faults enter in such a way that the transfer functions between these faults and a number of measured outputs are strictly positive real (SPR), that is, the observer matching condition is satisfied. This paper presents a systematic approach to adaptive observer design for joint estimation of the state and faults when the SPR requirement is not verified. The proposed method deals with a class of Lipschitz nonlinear systems subjected to piecewise constant multiplicative faults. The novelty of the proposed approach is that it uses a rank condition similar to the observer matching condition to construct the adaptation law used to obtain fault estimates. The problem of finding the adaptive observer matrices is formulated as a Linear Matrix Inequality (LMI) optimization problem. The proposed scheme is tested on the nonlinear model of a single link flexible joint robot system.

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LMI-based Adaptive Observers for Nonlinear Systems

Cited by 5 publications

References 17 publications

Robust adaptive gain neural observer for a class of non‐linear systems

Robust adaptive gain neural observer for a class of non‐linear systems

Structural-parametrical Design Method of Adaptive Observers for Nonlinear Systems

Adaptive observer-based fault estimation for a class of Lipschitz nonlinear systems

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