Papers
4
Total Citations
37
H-Index
3
About
Mohsin Rizwan’s research focuses on advanced control systems for mechatronic and robotic platforms, with particular emphasis on intelligent, adaptive, and optimal control strategies. His work addresses critical challenges in nonlinear dynamics, parameter uncertainties, and real-world operational constraints such as battery depletion. Rizwan’s major contributions include the development of a fractional transformation-based intelligent H-infinity controller for DC servo motors (21 citations), which significantly improves position tracking accuracy under nonlinearities. He also formulated a model-free self-organizing weight adaptation scheme that enhances the robustness of Linear Quadratic Regulators for under-actuated robotic systems (7 citations), experimentally validated on inverted pendulum platforms. Additionally, his genetically optimized ANFIS-based PID controller (6 citations) provides a novel solution for maintaining posture stability in self-balancing robots as battery power degrades—a practical problem often overlooked. Rizwan’s work bridges theoretical control design with experimental verification, offering tangible improvements in reliability and performance. His research is particularly valuable for students and engineers working on autonomous systems, robotics, and energy-aware control applications.
Research Focus
Key Achievements
Top Papers
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- 3Genetically Optimized ANFIS-based PID Controller Design for Posture-Stabilization of Self-Balancing-Robots under Depleting Battery Conditions6 citations · 2019
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