Papers

11

Total Citations

207

H-Index

7

About

Shubhi Purwar is a control systems researcher whose work has substantially advanced the field of intelligent and adaptive control for robotic systems. With a career spanning over two decades, Purwar has focused primarily on robot manipulator control, sliding mode techniques, neural and fuzzy logic systems, and more recently, multi-agent systems and event-triggered control architectures. Purwar's most influential contributions include adaptive output feedback tracking control using position measurements only (2007, 82 citations) and fuzzy logic-based adaptive control under actuator constraints (2004, 62 citations), both of which addressed the critical practical challenge of achieving robust manipulator performance without full state feedback. These works demonstrated that reliable trajectory tracking could be accomplished despite velocity measurement limitations and physical actuator bounds — problems of direct industrial relevance. Further cementing her reputation, Purwar explored neuro-sliding mode control, higher-order sliding mode strategies to reduce chattering, and wavelet network-based controllers for mobile robots. Her more recent research reflects evolving priorities in the field, including event-triggered control for computational efficiency and distributed sliding mode approaches for multi-agent consensus. Collectively, her papers have accumulated nearly 200 citations, reflecting sustained influence on researchers tackling nonlinear, uncertain robotic systems through intelligent control methodologies.

Research Focus

Key Achievements

7
H-Index
11
Papers
207
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
Adaptive output feedback tracking control of robot manipulators using position measurements only
82 citations · 2007
📈 Most Prolific Year: 2007 (3 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Motilal Nehru National Institute of Technology, Indian Institute of Technology Delhi

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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