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\begin{document}

\title{Adaptive Neural \& Fuzzy Controller for Exoskeleton Gait Pattern Control
Based on Musculoskeletal Modeling}



\author[1]{Anjali Gupta}%
\author[1]{Vijay Semwal}%
\affil[1]{Maulana Azad National Institute of Technology}%


\vspace{-1em}



  
  \date{June 17, 2024}


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\begin{abstract}
The paper deals with the development of 2-link lower limb extremity
manipulator for rehabilitation purposes in bio-medical engineering. The
musculoskeletal modeling was performed on the collected human gait data
to obtain the joint angles and driving force values for hip and knee
movement. The results obtained from the proposed controller were
verified using Matlab-Simulink. The robust adaptive RBF neural network
and fuzzy sliding mode controller were developed to track the desired
trajectory. The OpenSim software was utilized to perform inverse
kinematics and inverse dynamics on the musculoskeletal model which is
scaled according to the physical dimensions of the experimental subject.
The simulation results stated that SMC-RBF network has better tracking
rate, less chattering problems and handle unknown uncertainties well.
Finally, the results obtained were compared with the existing method
with the help of performance index parameters to prove their
effectiveness.%
\end{abstract}%



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