Naresh Patnana
Papers
1
Total Citations
5
H-Index
1
About
Naresh Patnana is a researcher specializing in control systems, robotics, and optimization algorithms, with a particular focus on the modeling and simplification of complex dynamic systems. His work centers on order reduction techniques for controllers, aiming to make high-order systems more computationally efficient without sacrificing performance. In his notable 2022 study, Patnana introduced a novel approach to diminish the order of a self-balanced linear-momentum based bicycle-robot (LMBR) controller. By exploiting time-moments and Markov-parameters, and employing the Jaya algorithm to minimize errors, he successfully developed a reduced-order model that retains critical system behavior. This contribution, which has garnered 5 citations, demonstrates his ability to bridge theoretical optimization with practical robotics applications. Patnana’s research is significant for advancing the design of efficient, real-time controllers for autonomous vehicles and mobile robots, offering a pathway to more streamlined and responsive systems. His work reflects a commitment to solving engineering challenges through intelligent algorithm integration, making him a rising voice in the fields of control theory and robotic system design.
Research Focus
Key Achievements
Top Papers
- 1