Papers
6
Total Citations
23
H-Index
3
About
Michael Basin is a control systems researcher whose work spans robust control theory, trajectory tracking, and intelligent control methodologies for complex dynamical systems. His research is principally focused on designing advanced controllers for uncertain multi-input multi-output (MIMO) systems, with particular emphasis on handling parametric uncertainties, external disturbances, and actuator nonlinearities in real-world engineering applications. Among his notable contributions, Basin has developed systematic frameworks for robust proportional-integral and PID-type controllers capable of tracking reference signals under bounded uncertainties — work that has garnered meaningful attention, including his 2020 paper on robust tracking for uncertain MIMO systems earning 10 citations. His 2019 comprehensive approach to mechatronic process control further demonstrates his commitment to unifying controller design methodologies across broad system classes. More recently, his research has extended into robotics, addressing finite-time trajectory tracking for robotic manipulators, and into multi-agent systems, exploring fault detection co-designed with formation control using fuzzy modeling frameworks. His applied work even encompasses intelligent fuzzy-PID control for autonomous cleaning robots. Collectively, Basin's portfolio reflects a researcher who bridges rigorous theoretical control design with practical engineering challenges across robotics, automation, and networked systems.
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