Ismail Boumhidi

About

Ismail Boumhidi is a control systems researcher whose work centers on intelligent control strategies for nonlinear robotic systems and renewable energy applications. His primary contributions lie at the intersection of sliding mode control, fuzzy logic, and neural networks — techniques he has skillfully combined to address one of control engineering's most persistent challenges: eliminating the chattering phenomenon in robust controllers. Boumhidi's most influential work focuses on robot manipulator control, particularly two-link robotic arms. His 2012 papers on fuzzy-sliding mode and neural network sliding mode control, each garnering 22 citations, demonstrated that hybrid intelligent approaches could significantly outperform conventional sliding mode controllers by reducing chattering while maintaining robustness against uncertainties and external disturbances. Subsequent publications in 2014 extended these foundations through adaptive fuzzy implementations, further validating this research direction. More recently, Boumhidi has expanded his expertise toward wind energy systems, applying fractional calculus and enhanced nonlinear control techniques to optimize turbine performance and maximize energy capture — work that has already attracted notable early attention. His continued exploration of PID optimization and Type-2 fuzzy controllers reflects a commitment to advancing practical, deployable intelligent control solutions across multiple engineering domains.

Research Focus

Key Achievements

Top Papers

1. 1
   Combined fuzzy logic and sliding mode approach's for modelling and control of the two link robot

   22 citations · 2012
2. 2
   Adaptive Neural Network Sliding Mode Control For Electrically-Driven Robot Manipulators

   22 citations · 2012
3. 3
   Adaptive fuzzy sliding mode control for the two-link robot

   18 citations · 2014
4. 4
   Fuzzy sliding mode control for the two-link robot

   17 citations · 2014
5. 5
   New design of an intelligent electromagnetic torque controller based on neural network and fractional calculus: Variable-speed wind energy systems application

   7 citations · 2024
6. 6
   Enhanced nonlinear sliding mode control technique for wind power generation systems application: Theoretical design and comparative study

   7 citations · 2025
7. 7
   Comparative Study of Optimal Tuning PID Controller for Manipulator Robot

   5 citations · 2023
8. 8
   Type 2 Fuzzy PID for Robot Manipulator

   4 citations · 2022

Key Collaborators

Contact & Links