Mircea‐Bogdan Rădac

About

Mircea‐Bogdan Rădac is a leading researcher in data-driven control and intelligent systems, with a focus on advancing model-free adaptive control (MFAC) and optimization for autonomous robotics. His most impactful work introduces a novel hybrid approach that combines MFAC with Virtual Reference Feedback Tuning (VRFT), enabling automatic, data-driven parameter tuning for nonlinear systems. This mixed MFAC-VRFT framework, detailed in his 2016 paper (39 citations), eliminates the need for explicit system models, significantly improving adaptability and performance in complex control environments. Rădac has also contributed to multi-robot path planning, employing Charged System Search (CSS) algorithms to optimize trajectories for holonomic robots in static settings (6 citations). His research bridges theoretical innovation and practical application, offering scalable solutions for autonomous navigation and real-time control. With a growing citation record and a focus on data-efficient, model-free methodologies, Rădac’s work is shaping the future of intelligent control systems and multi-agent robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Data-driven Model-Free Adaptive Control Tuned by Virtual Reference Feedback Tuning

   39 citations · 2016
2. 2
   Data-driven Model-Free Adaptive Control Tuned by Virtual Reference

   8 citations · 2016
3. 3
   Multi-robot charged system search-based optimal path planning in static environments

   6 citations · 2014

Key Collaborators

Contact & Links