Adaptive Control of Antilock Braking System Using Grey Multilayer Feedforward Neural Networks

In this paper, a grey neuro-adaptive control algorithm is suggested for Antilock Braking Systems (ABS). The concept of grey system theory, which has a certain prediction capability, offers an alternative approach to conventional control methods. A multilayer neural network and a grey predictor, GM(1,1) model, are combined in the approach proposed in the paper. The grey neural network controller is examined under several different operating conditions and it is shown that the proposed control algorithm anticipates the upcoming values of wheel slip and optimal wheel slip, and takes the necessary action to keep the wheel slip at the desired value. The simulation results indicate that the proposed controller has the ability to control the nonlinear system accurately with little oscillations and with no steady-state error.

• Type: Conference
• Year: 2008
• Where: ICMLA
• Authors: Erdal Kayacan, Yesim Oniz, Okyay Kaynak, Andon V. Topalov
• Keywords: Control Algorithm, Grey Neuro-adaptive Control, ICMLA 2008, Machine Learning, Wheel Slip