ANN Based Controller for Anti-locking Braking System
Kommabathula Prakash Babu
Kommabathula Prakash Babu, Andhra University, Visakhapatnam, Andhra Pradesh, India.
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 26 July 2019 | PP: 442-445 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F10910486S419/19©BEIESP | DOI: 10.35940/ijitee.F1091.0486S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Braking has great impact on the stability of a moving vehicle, as it has to dissipate all the energy that has been stored (kinematic energy) through brake pads (in another forms i.e. heat and sound energy). Stability of the system is more likely to flop as it has to transform and deplete the energy in flash of time, leads to loss in control over desired path followed by drift. Slip (µ) is the key factor to measure stability of this system explicitly, which is defined in terms of vehicle speed (Vs) and wheel speed (Ws). Using Artificial Neural Network (ANN) as a tool to control Anti-lock braking system (ABS) to attain optimal brake pressure thereby minimizing the stopping distance, jerk’s and ultimately system stability. Validation of result were carried out by using MAT-LAB and compared with Hysteresis controller. Simulated results proved that the system performance is improved.
Keywords: Anti-lock Braking System (ABS), Artificial Neural Network (ANN), Slip, Vehicle Stability.
Scope of the Article: Artificial Intelligence Approaches to Software Engineering