Department of S c h o o l o f E n g i n e e r i n g
Design of Aging-Aware SNN Architecture for Extreme Learning Machine
This project aims to design a Spiking Neural Network (SNN) architecture within the Extreme Learning Machine framework to mitigate computational complexity. It analyses ageing effects on long-term performance, offering insights into neuromorphic hardware robustness and identifying optimisation strategies to enhance resilience and scalability for real-world applications.
A novel cost effective reconfiguration scheme to mitigate power losses in partially shaded PV array
This research introduces a cost-effective Solar Panel Relocation Technique (SPRT) to reduce shading losses in PV arrays. By optimising panel placement during installation, SPRT boosts power output by 4.28% to 27.59%, as observed on the experimental platform. Simulations across 2000 scenarios confirm its superior efficiency and revenue potential over traditional configurations.
Nanomaterial Doped Meta-Materials
Lattice-Based Piezocapacitive Soft
Sensors for Human Motion Monitoring
This work proposes nanomaterial-doped soft piezocapacitive sensors for wearable devices to monitor human motion in neurodegenerative diseases. These sensors enable real-time, remote tracking of gait impairments, supporting personalised care. The research integrates material science, flexible electronics, and healthcare, benefiting India's growing medical and manufacturing ecosystem.
Fast-Terminal Super-Twisting Control for Quadrotor UAVs Landing on Moving Ship
The research presents a fast-terminal super-twisting control (FTSTC) scheme for shipboard quadrotor UAV landing, comprising relative position and altitude-attitude control stages. The FTSTC compensates for underactuated dynamics, ensuring finite-time convergence of tracking and attitude errors. Lyapunov-based analysis guarantees stability, with all errors confined to small neighbourhoods around zero.