Robust observer-based fault-tolerant control for vehicle lateral dynamics

Oudghiri, Mohammed; Chadli, Mohammed

doi:10.1504/ijvd.2008.022575

Cited by 77 publications

(44 citation statements)

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“…Using an identification method based on the LevenbenrgMarquadt algorithm [15] combined with the least square method, parameters of the membership functions (ai, bi, and ci) and stiffness coefficient C f i and Cri are obtained so that the T-S model (6) approximates the cornering forces for given vehicle parameters and road conditions. For the vehicle parameters defined in Table 2 and for a dry road, the obtained values are given in Table 3.…”

Section: Parameter Identification Of the Vehicle Modelmentioning

confidence: 99%

“…A model-based roll state estimator is designed in presence of the road bank angle using the H∞ approach and taking into account the unmeasurable premise variables [11,12] . The nonlinear model, as derived from three-degree-of-freedom vehicle lateral dynamics, is represented by a Takagi-Sugeno (T-S) fuzzy model [13] which is very efficient to represent the lateral force nonlinearities [12,14,15] . This representation has been widely used and studied in the past years (see for example [15−22]).…”

Section: Introductionmentioning

confidence: 99%

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Detection of impending vehicle rollover with road bank angle consideration using a robust fuzzy observer

Dahmani

Chadli

Rabhi

2015

Int. J. Autom. Comput.

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Abstract:This article describes a method of vehicle dynamics estimation for impending rollover detection. We estimate vehicle dynamic states in presence of the road bank angle as a disturbance in the vehicle model using a robust observer. The estimated roll angle and roll rate are used to compute the rollover index which is based on the prediction of the lateral load transfer. In order to anticipate rollover detection, a new method is proposed to compute the time to rollover (TTR) using the load transfer ratio (LTR). The nonlinear model, deduced from the vehicle lateral and roll dynamics, is represented by a Takagi-Sugeno (T-S) fuzzy model. This representation is used to account for the nonlinearities of lateral cornering forces. The proposed T-S observer is designed with unmeasurable premise variables to cater for non-availability of the slip angles measurement. The proposed approach is evaluated using CarSim simulator under different driving scenarios. Simulation results show good efficiency of the proposed T-S observer and the rollover detection method.

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Section: Parameter Identification Of the Vehicle Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Detection of impending vehicle rollover with road bank angle consideration using a robust fuzzy observer

Dahmani

Chadli

Rabhi

2015

Int. J. Autom. Comput.

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“…Usually, the fault tolerance could be achieved through several potential solutions, for instance: selecting a new precomputed control law depending on the faults which have been identi¦ed by the FDI system. In this case, hybrid control or switching control structures are commonly encountered in [65]; synthesizing a new control strategy online. Such methods involve the calculation of new controller parameters once a failure has been identi¦ed by an online fault estimation scheme, following the typical design paradigm of adaptive control [66]; and using dynamic control allocation for overactuated systems.…”

Section: Recovery Aspectsmentioning

confidence: 99%

The challenge of advanced model-based fdir techniques for aerospace systems: the 2011 situation

Zolghadri

2013

Progress in Flight Dynamics, Guidance, Navigation, Control, Fault Detection, and Avionics

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For aerospace systems, advanced model-based Fault Detection, Identi¦-cation, and Recovery (FDIR) challenges range from predesign and design stages for upcoming and new programs up to the improvement of the performance of in-service §ying systems. However, today, their application to real aerospace world has remained extremely limited. The paper underlines the reasons for a widening gap between the advanced scienti¦c FDIR methods being developed by the academic community and technological solutions demanded by the aerospace industry.

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“…Notice that in (Oudghiri et al, 2008), a bank of controllers is implemented, each of them is designed separately and generates a control law based on the state estimatex k (t). Based on a residual analysis, a switching strategy is then developed in order to select "the best" control signal (in the sense that the control law relies on a fault free state estimate).…”

Section: Fault Tolerant Controlmentioning

confidence: 99%

“…In the context of fault tolerant control (FTC), state trajectory tracking is proposed in (Ichalal et al, 2010) for actuator faults. Observer bank based controllers with switching mechanism for sensor faults is also presented in (Oudghiri et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Nonlinear observer based sensor fault tolerant control for nonlinear systems

Ichalal

Marx²,

Maquin³

et al. 2012

IFAC Proceedings Volumes

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This paper deals with the problem of sensor fault tolerant control for Takagi-Sugeno nonlinear systems. Firstly, a residual generator is designed in order to detect and isolate sensor faults. Secondly, a nonlinear observer based controller, adopting the so-called parallel distributed compensation structure is designed. This controller is based on a weighted blending of the estimated states provided by different observers. Each observer is constructed to estimate the system state from the inputs and only one output. The blending of the estimates depends on the residual magnitudes in order to minimize the use of faulty estimates in the control law. The stability of the global closed-loop system is studied by Lyapunov theory and the gains of the fault tolerant controller are obtained by solving Linear Matrix Inequalities.

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Robust observer-based fault-tolerant control for vehicle lateral dynamics

Cited by 77 publications

References 0 publications

Detection of impending vehicle rollover with road bank angle consideration using a robust fuzzy observer

Detection of impending vehicle rollover with road bank angle consideration using a robust fuzzy observer

The challenge of advanced model-based fdir techniques for aerospace systems: the 2011 situation

Nonlinear observer based sensor fault tolerant control for nonlinear systems

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