Shubhendu Bhasin
Papers
15
Total Citations
237
H-Index
8
About
Shubhendu Bhasin is a researcher specializing in nonlinear control theory, adaptive and intelligent control systems, and human-robot interaction, with significant contributions spanning over fifteen years of prolific scholarship. His work is perhaps best recognized for advancing neural network-based control frameworks, particularly the development of dynamic neural network (DNN) observers for uncertain nonlinear systems, which has garnered substantial scholarly attention with 48 citations. His highly cited 2019 work on switching-based collaborative fractional order fuzzy logic controllers for robotic manipulators (66 citations) demonstrates his expertise in intelligent hybrid control architectures. A recurring theme in Bhasin's research is robot-environment interaction, including pioneering adaptive controllers for noncontact-to-contact transitions and control of robots engaging viscoelastic surfaces under model uncertainty. More recently, his research has expanded into wearable robotics and neural interfaces, including EEG-based neural decoders for predicting limb kinematics and integrated simulation platforms for upper limb exosuits — bridging computational neuroscience with assistive robotics. His work on actuator fault compensation further underscores his commitment to robust, real-world applicable control solutions. Collectively, Bhasin's research offers foundational tools for safer, smarter robotic systems operating in unstructured and human-centered environments.
Research Focus
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Top Papers
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