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Barrier Lyapunov Function-Based Adaptive Back-Stepping Control for Electronic Throttle Control System

Author

Listed:
  • Dapeng Wang

    (College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China
    713 Research Institute of China Shipbuilding Industry Corporation, Zhengzhou 450015, China)

  • Shaogang Liu

    (College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China)

  • Youguo He

    (Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

  • Jie Shen

    (Department of Computer and Information Science, University of Michigan-Dearborn, Dearborn, MI 48128, USA)

Abstract

This paper presents an adaptive constraint control approach for Electronic Throttle Control System (ETCS) with asymmetric throttle angle constraints. The adaptive constraint control method, which is based on barrier Lyapunov function (BLF), is designed not only to track the desired throttle angle but also to guarantee no violation on the throttle angle constraints. An ETC mathematic model with complex non-linear system is considered and the asymmetric barrier Lyapunov function (ABLF) is introduced into the design of the controller. Based on Lyapunov stability theory, it can be concluded that the proposed controller can guarantee the stability of the whole system and uniformly converge the state error to track the desired throttle angle. The results of simulations show that the proposed controller can ensure that there is no violation on the throttle angle constraints.

Suggested Citation

  • Dapeng Wang & Shaogang Liu & Youguo He & Jie Shen, 2021. "Barrier Lyapunov Function-Based Adaptive Back-Stepping Control for Electronic Throttle Control System," Mathematics, MDPI, vol. 9(4), pages 1-14, February.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:4:p:326-:d:494879
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    References listed on IDEAS

    as
    1. Seong Ik Han & Jeong Yun Cheong & Jang Myung Lee, 2013. "Barrier Lyapunov Function-Based Sliding Mode Control for Guaranteed Tracking Performance of Robot Manipulator," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-9, November.
    2. Youguo He & Chuandao Lu & Jie Shen & Chaochun Yuan, 2019. "Design and Analysis of Output Feedback Constraint Control for Antilock Braking System with Time-Varying Slip Ratio," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-11, January.
    3. Lei Ma & Dapeng Li, 2018. "Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints," Complexity, Hindawi, vol. 2018, pages 1-9, January.
    4. Fang, Liandi & Ma, Li & Ding, Shihong & Zhao, Dean, 2019. "Finite-time stabilization for a class of high-order stochastic nonlinear systems with an output constraint," Applied Mathematics and Computation, Elsevier, vol. 358(C), pages 63-79.
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    Cited by:

    1. Hazem Issa & József K. Tar, 2022. "Improvement of an Adaptive Robot Control by Particle Swarm Optimization-Based Model Identification," Mathematics, MDPI, vol. 10(19), pages 1-21, October.
    2. Nguyen Xuan-Mung & Mehdi Golestani & Sung-Kyung Hong, 2022. "Tan-Type BLF-Based Attitude Tracking Control Design for Rigid Spacecraft with Arbitrary Disturbances," Mathematics, MDPI, vol. 10(23), pages 1-21, December.

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