Kamal Al‐Haddad

École de Technologie Supérieure, Université du Québec à Montréal, École Normale Supérieure - PSL

Papers

Total Citations

627

H-Index

About

Kamal Al-Haddad is a prominent researcher specializing in advanced robotics control, with deep expertise in sliding-mode control, adaptive control, and neural network-based control systems. His work spans nonlinear system dynamics, trajectory tracking, and intelligent control architectures for robotic manipulators. Al-Haddad's most influential contribution is his 2010 paper on sliding-mode robot control with an exponential reaching law, which has garnered an impressive 531 citations. This landmark work introduced a novel approach to controlling multi-input/multi-output nonlinear systems, elegantly addressing the persistent challenge of chattering reduction while maintaining exceptional steady-state tracking performance — a balance that had long eluded control engineers. His earlier work in the 1990s laid important groundwork in adaptive and neural adaptive control, with studies applying both Lyapunov stability-based direct adaptive techniques and multilayer recurrent neural networks to high-speed direct-drive SCARA robots. A notable 1994 comparative study critically evaluated adaptive versus neural adaptive strategies, offering researchers valuable practical insights into their respective strengths. Later, his 2003 hybrid controller research extended these principles to simultaneous force and position tracking in constrained robotic environments. Collectively, Al-Haddad's body of work has meaningfully shaped modern intelligent robot control theory and continues to inform researchers advancing autonomous and high-performance robotic systems.