Ali Doustmohammadi
Amirkabir University of Technology, National Taiwan University
Papers
9
Total Citations
133
H-Index
5
About
Ali Doustmohammadi is a control systems and robotics researcher whose work spans adaptive control, multi-robot coordination, and rehabilitation robotics. He is perhaps best known for his 2017 paper on robust adaptive model reference impedance control for robotic manipulators — his most cited work with 70 citations — which addressed critical real-world challenges including actuator saturation, parameter uncertainties, and imprecise force sensing using adaptive techniques and prediction error methods. His research into distributed receding horizon coverage control for multiple mobile robots has made notable contributions to the field of autonomous multi-agent systems, developing decentralized schemes that enable robot teams to efficiently detect and respond to probabilistic events in a shared environment, accumulating nearly 30 citations. Doustmohammadi has also advanced safe human-robot interaction in rehabilitation settings, proposing singularity-free, model-free impedance control strategies using max-plus algebra to ensure safe motion near kinematic singularities. His additional contributions include robust adaptive observer design for singular nonlinear uncertain systems and hybrid model predictive control for miniature capsule robots, reflecting a research portfolio characterized by rigorous mathematical foundations applied to practical robotic challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2Distributed Receding Horizon Coverage Control for Multiple Mobile Robots29 citations · 2014
- 3
- 4
- 5
- 6
- 7
- 8Hybrid model predictive control of legless piezo capsubot2 citations · 2011
- 9Distributed Receding Horizon Coverage Control by Multiple Mobile Robots2 citations · 2014