JP
JINRAJ V PUSHPANGATHAN
Amrita Vishwa Vidyapeetham, Indian Institute of Science, College of Engineering Trivandrum, General Aeronautics, Nair Service Society College of Engineering
About
Jinraj V Pushpangathan received his PhD in
Aerospace Engineering from the Indian Institute
of Science (IISc), India, in 2018. Currently, he
works as an Assistant Professor at the Department
of Aerospace Engineering, Amrita Vishwa
Vidyapeetham, Coimbatore, India. His research interests
include robust control, simultaneous stabilization
and estimation, aerial robots, guidance and control
of unmanned systems, flight dynamics and control,
and reinforcement learning.
Employment
-
Amrita Vishwa Vidyapeetham Assistant Professor2023 - Present
-
Indian Institute of Science Research Fellow2020 - 2021
-
General Aeronautics Senior technician2018 - 2020
-
Indian Institute of Science Research Associate2017 - 2018
-
Federal Institute of Science and Technology Department of Electrical And Electronics Engineering lecturer2007 - 2009
Education
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Indian Institute of Science Ph.D.2012 - 2018
-
College of Engineering Trivandrum MTech2009 - 2011
-
Nair Service Society College of Engineering BTech2003 - 2006
Projects & Funding
Projects & funding information is unavailable.
Publications (19)
- Nonlinear and Linear PID Controllers-Based Hybrid Flight Control Strategy for a Quadcopter With Slung Load Save
- AGVO: Adaptive Geometry-Based Velocity Obstacle for Heterogenous UAVs Collision Avoidance in UTM Save
- Development and calibration of autopilot hardware for small fixed-wing air vehicles with flight test validation of linear output feedback controller Save
- RRT and Velocity Obstacles-based motion planning for Unmanned Aircraft Systems Traffic Management (UTM) Save
- Robust Simultaneously Stabilizing Decoupling Output Feedback Controllers for Unstable Adversely Coupled Nano Air Vehicles Save
- Deep Reinforcement Learning and Simultaneous Stabilization-Based Flight Controller for Nano Aerial Vehicle Save
- Robust consensus of higher-order multi-agent systems with attrition and inclusion of agents and switching topologies Save
- Waypoint Navigation of Quadrotor using Deep Reinforcement Learning Save
- Integrated guidance and control framework for the waypoint navigation of a miniature aircraft with highly coupled longitudinal and lateral dynamics Save
- Gap reduced minimum error robust simultaneous estimation for unstable nano air vehicle Save