Neural network based feedback linearisation slip control of an anti-lock braking system

Author

Pedro, J.O. ; Nyandoro, O.T.C. ; John, S.

Author_Institution

Sch. of Mech., Ind. & Aeronaut. Eng., Univ. of the Witwatersrand, Johannesburg, South Africa

fYear

2009

Firstpage

1251

Lastpage

1257

Abstract

This paper presents the design of a neural network-based feedback linearisation (NARMA-L2) slip controller for an anti-lock braking system (ABS). The dynamics of the electro-mechanical based braking system are incorporated in the ABS model and thus a slip controller is developed to minimise the braking distance. The proposed controller is compared with an optimally-tuned PID controller. Simulation results demonstrate the superiority of the NN-based controller over the generic PID-based controller.

Keywords

automobiles; autoregressive moving average processes; braking; control system synthesis; feedback; linearisation techniques; neurocontrollers; nonlinear control systems; optimal control; slip; three-term control; ABS; NARMA-L2; antilock braking system; braking distance minimisation; car model; electro-mechanical based braking system dynamics; neural network based feedback linearisation slip control design; optimally-tuned PID controller; Aerodynamics; Africa; Control systems; Friction; Linear feedback control systems; Neural networks; Neurofeedback; Optimal control; Roads; Robust control;

fLanguage

English

Publisher

ieee

Conference_Titel

Asian Control Conference, 2009. ASCC 2009. 7th

Conference_Location

Hong Kong

Print_ISBN

978-89-956056-2-2

Electronic_ISBN

978-89-956056-9-1

Type

conf

Filename

5276197