Majid Mokhtari

Shahid Beheshti University

Papers

1

Total Citations

11

H-Index

1

About

Majid Mokhtari is a leading researcher in the field of rehabilitation robotics and nonlinear control systems, with a particular focus on lower-limb exoskeletons and human-robot interaction. His most influential work centers on developing adaptive, fault-tolerant control strategies that ensure safe and precise trajectory tracking for assistive devices. In his highly cited 2022 paper, Mokhtari introduced an innovative approach that combines second-order sliding mode control with a Central Pattern Generator (CPG) algorithm, enabling exoskeletons to adapt to disturbances and actuator faults while maintaining natural, biomimetic motion. This contribution is critical for advancing the reliability of wearable robots in clinical and daily-use settings. With over 11 citations on this work alone, his research has already shaped how engineers design robust controllers for rehabilitation systems. Mokhtari’s broader impact lies in bridging theoretical control theory with practical, human-centered robotics—offering solutions that enhance mobility for individuals with lower-limb impairments. His work is essential reading for students and researchers interested in fault-tolerant control, exoskeleton design, and the integration of bio-inspired algorithms into assistive technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
11
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive second-order sliding model-based fault-tolerant control of a lower-limb exoskeleton subject to tracking the desired trajectories augmented by CPG algorithm
11 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Shahid Beheshti University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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