Prashant J. Gaidhane

Indian Institute of Technology Roorkee

Papers

6

Total Citations

236

H-Index

5

About

Prashant J. Gaidhane is a researcher whose work sits at the dynamic intersection of intelligent control systems, computational optimization, and robotics. His research primarily focuses on advanced controller design for complex nonlinear systems, with particular emphasis on robotic manipulators and the application of bio-inspired optimization algorithms to enhance control performance. Gaidhane's most impactful contribution is his development of a hybrid Grey Wolf Optimizer and Artificial Bee Colony (GWO-ABC) algorithm, which has garnered 112 citations and demonstrated significant promise in optimizing complex engineering systems. Complementing this, his work on interval type-2 fuzzy precompensated PID controllers for two-degree-of-freedom robotic manipulators has attracted 76 citations, reflecting strong community interest in robust, adaptive control strategies. A recurring theme throughout his research is addressing the challenges posed by highly nonlinear, multi-input multi-output robotic systems under uncertain operating conditions. His investigations into fractional-order PID and fuzzy fractional-order controllers for redundant manipulators represent meaningful advances in trajectory tracking precision and disturbance rejection. His continued refinement of these methods, including optimized fractional-order fuzzy controllers, demonstrates a sustained commitment to bridging theoretical control design with practical robotics applications, making his work valuable reading for students and researchers in intelligent automation and control engineering.

Research Focus

Key Achievements

5
H-Index
6
Papers
236
Total Citations
39
Avg Citations/Paper
🏆 Most Cited Paper
A hybrid grey wolf optimizer and artificial bee colony algorithm for enhancing the performance of complex systems
112 citations · 2018
📈 Most Prolific Year: 2018 (3 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Indian Institute of Technology Roorkee

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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