Bhawna Chahar
Papers
1
Total Citations
3
H-Index
1
About
Dr. Bhawna Chahar is a robotics and control systems researcher whose work focuses on intelligent control strategies for industrial robot manipulators. Her primary research areas include adaptive neuro-fuzzy inference systems (ANFIS), hybrid force-position control, and metaheuristic optimization algorithms. In her most cited work, she pioneered the application of the Imperialist Competitive Algorithm to optimize an adaptive neuro-fuzzy controller for hybrid force-position control of industrial robot manipulators. This study, which has garnered 3 citations, addresses the critical challenge of nonlinear dynamics in robot control by proposing a more accurate intelligent method to enhance the performance of traditional PID controllers. Dr. Chahar’s contributions are particularly significant for improving precision and reliability in automated manufacturing and assembly tasks. Her work bridges the gap between classical control theory and modern computational intelligence, offering practical solutions for real-world robotic applications. By integrating optimization techniques with adaptive control, she has advanced the field of intelligent robotics, demonstrating how hybrid approaches can overcome the limitations of conventional control systems in complex industrial environments.
Research Focus
Key Achievements
Top Papers
- 1