Adaptive exponential-reaching sliding-mode control for antilock braking systems

作者：Hsu Chun Fei^*; Kuo Tzu Chun

来源：Nonlinear Dynamics, 2014, 77(3): 993-1010.

DOI：10.1007/s11071-014-1357-6

• Sliding-mode control
• Exponential-reaching law
• Functional-linked neural network
• Wavelet neural network

Most commercial antilock braking system (ABS) is based on a look-up table. The table is calibrated through laboratory experiments and engineering field tests under specified road conditions, but it is not adaptive. To attack this problem, this paper proposes an adaptive exponential-reaching sliding-mode control (AERSMC) system for an ABS. The proposed AERSMC system is composed of an equivalent controller and an exponential compensator. The equivalent controller uses a functional-linked wavelet neural network (FWNN) to online approximate the system uncertainties and the exponential compensator is designed to eliminate the effect of the approximation error introduced by the FWNN uncertain observer with an exponential-reaching law. In addition, the adaptive laws online-tune the controller parameters in the sense of Lyapunov function to guarantee the system stability. Finally, the simulation results verify that the proposed AERSMC system can achieve favorable slip tracking performance and is robust against parameter variations in the plant.

• 出版日期2014-8