Wavelet based analysis and control of anti lock braking system with hybrid optimisation techniques

The integration of wavelet-based analysis and hybrid optimisation techniques in the control of anti-lock braking systems (ABS) presents a significant advancement in automotive safety and performance. Wavelet transforms, with their capability for multiresolution analysis and noise reduction, offer enhanced signal processing, enabling precise detection of wheel dynamics and road conditions. This leads to improved fault detection, adaptive control, and efficient brake pressure modulation, ensuring optimal braking performance under diverse and nonlinear conditions. Hybrid optimisation techniques, such as genetic algorithms and particle swarm optimisation, complement wavelet-based methods by optimising ABS performance across multiple objectives, such as safety, comfort, and efficiency. The synergy of these approaches results in a robust and responsive ABS that adapts in real-time to varying driving scenarios, enhancing vehicle stability, reducing stopping distances, and providing superior overall safety. This research underscores the potential of wavelet-based analysis and hybrid optimisation to revolutionise ABS technology, offering significant benefits in both conventional and autonomous vehicles.