Reliable Fuzzy Sampled-Data Control for Nonlinear Suspension Systems Against Actuator Faults

This article investigates the reliable fuzzy sampled-data control issue of nonlinear vehicle suspension systems subject to actuator faults. Considering the high nonlinear characteristics in the springs and the shock absorbers, the Takagi-Sugeno fuzzy method is utilized to describe the nonlinear susp...

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Published inIEEE/ASME transactions on mechatronics Vol. 27; no. 6; pp. 5518 - 5528
Main Authors Zhao, Jing, Wong, Pak Kin, Li, Wenfeng, Ghadikolaeia, Meisam Ahmadi, Xie, Zhengchao
Format Journal Article
LanguageEnglish
Published New York IEEE 01.12.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Actuator faults
Actuators
Algorithms
Continuous time systems
Control systems design
Delays
Fuzzy control
Nonlinear control
Nonlinear dynamical systems
nonlinear dynamics
Nonlinear systems
Optimization
Output feedback
Passenger comfort
Roads
sampled-data control
Shock absorbers
Suspension systems
Suspensions (mechanical systems)
Systems stability
Tires
Vehicle dynamics
vehicle suspension control
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Abstract This article investigates the reliable fuzzy sampled-data control issue of nonlinear vehicle suspension systems subject to actuator faults. Considering the high nonlinear characteristics in the springs and the shock absorbers, the Takagi-Sugeno fuzzy method is utilized to describe the nonlinear suspension system. To deal with the discrete phenomenon of nonuniform sampling, an input-delay is employed to convert the continuous-discrete suspension system into a continuous-time form. Motivated by the above system model, a Lyapunov functional candidate is employed to obtain sufficient conditions that can meet system stability and performance requirements simultaneously. Furthermore, a novel two-step optimization algorithm is proposed for the sampled-data controller design in the structure of output feedback. Finally, experimental tests are implemented via an active suspension test rig, and the test results illustrate that the proposed method contributes greatly to improve the ride comfort, handling performance, and road holding capability simultaneously.
AbstractList This article investigates the reliable fuzzy sampled-data control issue of nonlinear vehicle suspension systems subject to actuator faults. Considering the high nonlinear characteristics in the springs and the shock absorbers, the Takagi-Sugeno fuzzy method is utilized to describe the nonlinear suspension system. To deal with the discrete phenomenon of nonuniform sampling, an input-delay is employed to convert the continuous-discrete suspension system into a continuous-time form. Motivated by the above system model, a Lyapunov functional candidate is employed to obtain sufficient conditions that can meet system stability and performance requirements simultaneously. Furthermore, a novel two-step optimization algorithm is proposed for the sampled-data controller design in the structure of output feedback. Finally, experimental tests are implemented via an active suspension test rig, and the test results illustrate that the proposed method contributes greatly to improve the ride comfort, handling performance, and road holding capability simultaneously.
Author Xie, Zhengchao
Wong, Pak Kin
Li, Wenfeng
Ghadikolaeia, Meisam Ahmadi
Zhao, Jing
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Snippet This article investigates the reliable fuzzy sampled-data control issue of nonlinear vehicle suspension systems subject to actuator faults. Considering the...
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SubjectTerms Actuator faults
Actuators
Algorithms
Continuous time systems
Control systems design
Delays
Fuzzy control
Nonlinear control
Nonlinear dynamical systems
nonlinear dynamics
Nonlinear systems
Optimization
Output feedback
Passenger comfort
Roads
sampled-data control
Shock absorbers
Suspension systems
Suspensions (mechanical systems)
Systems stability
Tires
Vehicle dynamics
vehicle suspension control
Title Reliable Fuzzy Sampled-Data Control for Nonlinear Suspension Systems Against Actuator Faults
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