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Direct adaptive neural control of antilock braking systems incorporated with passive suspension dynamics

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Abstract

A direct adaptive neural network-based feedback linearization (NNFBL) slip control scheme for an antilock braking system (ABS) is presented. The NNFBL slip controller is developed to minimise the vehicle braking distance and to simultaneously improve its overall ride comfort and road handling. The comprehensive vehicle model incorporates the passive suspension dynamics, the dynamics of the electro-mechanical based braking system and air drag and wheel bearing friction. A feedforward, multilayer perceptron (MLP) neural network (NN) model that is well suited for control by discrete input-output linearization (NNIOL) is selected to represent the ABS with passive suspension. The NN model was trained using Levenberg-Marquardt optimization algorithm. The controlled signal was further boosted using a genetic algorithm generated gain. The effectiveness of the proposed controller is demonstrated by simulation results, in the presence of deterministic road disturbance input to the suspension and varying road conditions. The results are superior with respect to braking distance minimization and also to reference slip tracking, especially on the dry asphalt road.

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Authors and Affiliations

  1. School of Mechanical, Industrial and Aeronautical Engineering, University of the Witwatersrand, Private Bag 03, WITS2050, Johannesburg, South Africa

    Jimoh O. Pedro & Olurotimi A. Dahunsi

  2. School of Electrical and information Engineering, University of the Witwatersrand, Private Bag 03, WITS2050, Johannesburg, South Africa

    Otis T. Nyandoro

Authors
  1. Jimoh O. Pedro
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  2. Olurotimi A. Dahunsi
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  3. Otis T. Nyandoro
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Corresponding author

Correspondence to Olurotimi A. Dahunsi.

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Recommended by Associate Editor Kyongsu Yi

Jimoh Olarewaju Pedro received the M.Sc. and Ph.D degrees in aeronautical engineering from the Warsaw University of Technology, Poland, in 1986 and 1992, respectively. He was a post-doctoral research fellow at the Institute of Aviation in Warsaw (1993–1994). He is currently an associate professor with the School of Mechanical, Industrial and Aeronautical Engineering, University of the Witwatersrand, Johannesburg, South Africa. He is author of more than 50 papers in refereed journals and conference proceedings. His research interests include applications of optimal control, robust control, nonlinear control and computational intelligence to aerospace vehicles and mechatronic systems.

Olurotimi Akintunde Dahunsi received the B.Eng. and M.Eng. degrees in mechanical engineering in 1994 and 2001, respectively. He is presently pursuing his Ph.D degree in mechanical engineering at the University of Witwatersrand, Johannesburg, South Africa. His research interests include intelligent control techniques, vehicle dynamics and vibration analysis.

Otis Tichatonga Nyandoro graduated with a B.Sc. Honours degree in Electrical Engineering, he afterward worked in the industry for two years, performing a number of control, processing and instrumentation projects. After converting his M.Sc. in Electrical Engineering to a Ph.D programme in 2000, he has been researching towards this end in the field of control of real time scheduling systems and has worked on numerous embedded and time-critical control systems. He has also lectured a number of control system related undergraduate and postgraduate courses and supervised M.Sc. researches in control systems.

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Pedro, J.O., Dahunsi, O.A. & Nyandoro, O.T. Direct adaptive neural control of antilock braking systems incorporated with passive suspension dynamics. J Mech Sci Technol 26, 4115–4130 (2012). https://doi.org/10.1007/s12206-012-0878-5

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  • DOI: https://doi.org/10.1007/s12206-012-0878-5

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