Behrad Dehghan

Queen's University, University of Tehran

Papers

Total Citations

H-Index

About

Behrad Dehghan’s research focuses on intelligent control systems, particularly adaptive and fuzzy methods for nonlinear dynamical systems. His most cited work, “Comparison of fuzzy and neural network adaptive methods for the position control of a pneumatic system” (15 citations), systematically evaluates the performance of PID controllers enhanced with adaptive neural network compensators against fuzzy adaptive PID controllers, addressing persistent nonlinearities that limit pneumatic system performance. This builds on his earlier foundational study introducing a novel adaptive neural network compensator for pneumatic position control (5 citations), which demonstrated that advanced nonlinear strategies can achieve superior performance without requiring explicit mathematical models. Dehghan has also explored fuzzy control for robotic applications, including one-degree-of-freedom arms and quadrotor UAVs, contributing to the growing field of autonomous aerial vehicle control. His work bridges theoretical control advances with practical implementation challenges, offering valuable insights for researchers working on adaptive control, mechatronics, and robotics. With a cumulative citation count exceeding 20, Dehghan’s contributions continue to inform the development of more robust, model-free control strategies for complex real-world systems.