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Research Papers

Sliding Mode Observer and State-Machine-Based Fault Diagnosis With Application in a Vehicle Chassis Steering System

[+] Author and Article Information
Xian Zhang

International Center of Automotive Research,
Department of Automotive Engineering,
Clemson University,
Clemson, SC 29631
e-mail: xianz@g.clemson.edu

Pierluigi Pisu

International Center of Automotive Research,
Department of Automotive Engineering,
Clemson University,
Campbell Graduate Engineering
Center Research Drive,
Greenville, SC 29607-5257
e-mail: pisup@clemson.edu

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received September 7, 2011; final manuscript received October 27, 2012; published online May 8, 2014. Assoc. Editor: Xubin Song.

J. Dyn. Sys., Meas., Control 136(4), 041026 (May 08, 2014) (12 pages) Paper No: DS-11-1281; doi: 10.1115/1.4026956 History: Received September 07, 2011; Revised October 27, 2012

A novel fault detection and identification (FDI) scheme based on sliding mode observer (SMO) residual generator and state machine residual evaluator is presented in this paper. The FDI scheme is applied to actuator and sensor faults in a vehicle chassis steering system described by a nonlinear bicycle model with three degrees of freedom. Primary residual is generated by an expanded SMO designed for linear time varying (LTV) systems. To cope with the multiple faults isolation problem, the state machine records and utilizes the previous fault information to determine the current fault state. Simulation results show that multiple fault detection and isolation can be successfully achieved by the proposed SMO and state-machine-based FDI scheme.

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References

Figures

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Fig. 1

System layout of an ESP system [3]

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Fig. 3

Comparison of linear and nonlinear model with changing vehicle speed

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Fig. 4

SMO-based FDI scheme

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Fig. 5

The residual evaluator scheme

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Fig. 6

State transition after fault 2 being detected

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Fig. 7

Command input of front steering angle and longitudinal speed of the vehicle

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Fig. 8

Simulation I results: residuals (absolute value) and corresponding thresholds

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Fig. 9

Simulation I results: fault types

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Fig. 10

Simulation II results: residuals (absolute value) and corresponding thresholds

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Fig. 11

Simulation II results: fault types

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Fig. 12

Simulation III results: residuals (absolute value) and corresponding thresholds

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Fig. 13

Simulation III results: fault types

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Fig. 14

Simulation results comparison: when tire cornering stiffness changes −35%

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