Faraz Abed Azad
Papers
5
Total Citations
125
H-Index
5
About
Faraz Abed Azad is a robotics and control systems researcher whose work centers on the dynamics, kinematics, and intelligent control of parallel robotic manipulators — particularly the 3-DOF Delta parallel robot. His research has made meaningful strides in bridging theoretical modeling and real-world implementation, a challenge that has long confronted the robotics community. Azad's most influential contributions address the complex problem of dynamic parameter identification and adaptive control. His 2022 study on offline-online tuning and base inertia parameter identification under insufficient excitations has garnered 39 citations, reflecting its practical significance for calibrating real robotic systems. Complementing this, his back-stepping control framework incorporating smart dynamic model selection for construction applications earned 31 citations, demonstrating his commitment to deploying advanced robotics in demanding industrial environments. A recurring theme in his work is linearizing complex dynamic equations of parallel robots using screw theory and the principle of virtual work — an approach he has shown enables efficient real-time implementation of nonlinear adaptive control schemes. His experimental validation of model reference adaptive control, with 27 citations, further underscores his strength in translating theory into practice. Collectively accumulating over 125 citations, Azad's body of work represents a significant contribution to precision control and modeling of parallel robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5