Nooritawati Md Tahir
Papers
3
Total Citations
78
H-Index
2
About
Nooritawati Md Tahir is a leading researcher in nonlinear system identification and intelligent control, with a particular focus on modeling complex dynamical systems. Her major contributions lie in developing advanced metaheuristic optimization algorithms for structure selection in Nonlinear Autoregressive Moving Average with Exogenous Inputs (NARMAX) models. Her most cited work, "Binary Particle Swarm Optimization Structure Selection of NARMAX Model of a Flexible Robot Arm" (2016, 57 citations), pioneered the use of binary swarm intelligence for simultaneously selecting model structure and estimating parameters, significantly improving the efficiency of nonlinear system modeling. She further advanced this field by introducing the Binary Artificial Bee Colony (BABC) algorithm for feature selection in polynomial NARX and NARMAX models, demonstrating its comparative advantages over particle swarm optimization. Her research has direct applications in robotics, as evidenced by her work on differential drive wheel mobile robots, where she developed practical self-driving algorithms using sensor fusion techniques. Through her innovative integration of computational intelligence with nonlinear system identification, Tahir has established herself as a key contributor to intelligent control systems, with her work serving as a foundation for researchers working on flexible manipulators, mobile robotics, and advanced modeling techniques.
Research Focus
Key Achievements
Top Papers
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