Noor Mjeed
Papers
3
Total Citations
11
H-Index
2
About
Noor Mjeed is a control systems researcher whose work focuses on the stabilization and trajectory tracking of highly nonlinear, unstable dynamic systems—specifically, the Two-Wheeled Self-Balancing Robot (TWSBR). Mjeed’s major contributions lie in the design of robust controllers that combine advanced sliding mode control with intelligent optimization and neural network techniques. In their most cited work (2018, 6 citations), Mjeed developed a Modified Integral Sliding Mode Controller enhanced by neural networks and optimization algorithms, effectively addressing balancing and tracking under external disturbances. Another key paper (2018, 3 citations) introduced an Adaptive Backstepping Sliding Mode Controller using a Cuckoo Search algorithm and Radial Basis Function networks, achieving robust attitude stabilization despite uncertainties. Most recently (2020, 2 citations), Mjeed proposed a Sliding Mode Controller based on optimized state feedback, offering a novel approach to solving the inherent instability of TWSBR systems. Though early in their career, Mjeed’s work demonstrates a systematic progression toward more adaptive, intelligent, and robust control strategies—paving the way for practical applications in mobile robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
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