Neural Network-Based Adaptive Feedback Linearization Control of Antilock Braking System
Safety systems in road vehicles are categorised into two main types: passive and active systems. The antilock braking system (ABS) is an active safety system in road vehicles, which senses the slip value between the tyre and the road and uses these values to determine the optimum braking force. Due to the high non-linearity of the tyre and road interaction, and uncertainties from vehicle dynamics, standard control methods: like PID, sliding mode control and feedback linearization will not suffice. This paper, therefore proposes a neural network-based feedback linearization control design method. The experimental results reveal that slip regulation using neural network-based control scheme is feasible for different slip values (road conditions) and robust to external disturbances.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information. Also: DOI is paid service which provided by a third party. We never mentioned that we go for this for our any journal. However, journal have no objection if author go directly for this paid DOI service.