Papers
14
Total Citations
101
H-Index
6
About
Estiko Rijanto is a leading researcher at the intersection of intelligent control systems, robotics, and electric vehicle (EV) technology. His work focuses on developing advanced control algorithms for autonomous systems, including reinforcement learning for self-tuning PID controllers in multi-agent soccer robots and recursive least squares (RLS) with adaptive forgetting factors for accurate battery state-of-charge (SoC) and state-of-health (SoH) estimation in Li-Ion batteries. Rijanto’s contributions have been widely recognized, with his most cited papers accumulating over 90 citations, including foundational work on robotic charging for EVs and coordination control for automatic guided vehicles (AGVs) in container terminal logistics. His research on plugging/unplugging characterization for EV charging connectors and boost/buck converter control for renewable energy systems demonstrates a practical engineering focus. Notable achievements include designing controllers for brushless DC motors in 4-wheel drive robotic platforms and kinematic analysis of 2-DOF mechanisms for satellite communication antennas. Rijanto’s work bridges theoretical control methods with real-world applications in robotics, energy storage, and sustainable transportation, making him a key figure in advancing autonomous and electrified systems.
Research Focus
Key Achievements
Top Papers
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- 3A review of robotic charging for electric vehicles13 citations · 2023
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