Meng Joo Er

About

Meng Joo Er is a distinguished researcher whose work sits at the dynamic intersection of fuzzy logic, neural networks, and intelligent control systems, with particular emphasis on robotics and autonomous systems. His landmark 2001 paper on generalized dynamic fuzzy neural networks (GD-FNNs), which has accumulated nearly 400 citations, established a highly efficient framework for automatically generating fuzzy rules using ellipsoidal basis functions — a contribution that fundamentally advanced the field of neuro-fuzzy computing. This foundational work laid the groundwork for subsequent influential contributions, including his dynamic fuzzy Q-learning method for online tuning of fuzzy inference systems (144 citations) and robust adaptive control strategies for robot manipulators (125 citations). Er's research consistently addresses real-world engineering challenges, spanning exoskeleton rehabilitation systems, mobile robotics, ship-borne manipulators, and UAV-enabled secure communications for Industry 5.0 environments. His early work on neural network-based control of SCARA robots signals a career-long commitment to bridging theoretical intelligence frameworks with practical mechatronic applications. With a body of work spanning over two decades and hundreds of citations across multiple domains, Er has made enduring contributions to intelligent control engineering that continue to inspire researchers worldwide.

Research Focus

Key Achievements

Top Papers

1. 1
   A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks

   391 citations · 2001
2. 2
   Reduced Adaptive Fuzzy Decoupling Control for Lower Limb Exoskeleton

   168 citations · 2020
3. 3
   Online Tuning of Fuzzy Inference Systems Using Dynamic Fuzzy Q-Learning

   144 citations · 2004
4. 4
   Robust adaptive control of robot manipulators using generalized fuzzy neural networks

   125 citations · 2003
5. 5
   Hybrid Fuzzy Control of Robotics Systems

   92 citations · 2004
6. 6
   Enabling Unmanned Aerial Vehicle Borne Secure Communication With Classification Framework for Industry 5.0

   49 citations · 2021
7. 7
   Control of a mobile robot using generalized dynamic fuzzy neural networks

   35 citations · 2004
8. 8
   Composite trajectory tracking of a ship-borne manipulator system based on full-order terminal sliding mode control under external disturbances and model uncertainties

   33 citations · 2022
9. 9
   Hybrid adaptive fuzzy controllers of robot manipulators with bounds estimation

   33 citations · 2000
10. 10
    Control of Adept One SCARA robot using neural networks

    32 citations · 1997

Key Collaborators

Contact & Links