Control of a Muscle Actuated Manipulator using the NeuraBASE Network Model

Robert Hercus, Kit-Yee Wong, Kim-Fong Ho
2014 Journal of Automation and Control Engineering  
This paper presents an alternative approach for the control of an antagonistic muscle actuated manipulator. The proposed method uses a neuronal network called NeuraBase to learn the sensor events obtained via a rotary encoder and to control the motor events of two DC motors, to rotate the manipulator. A neuron layer called the controller network links the sensor neuron events to the motor neurons. The proposed NeuraBase network model (NNM) has demonstrated its ability to successfully control
more » ... essfully control the antagonistic muscle manipulator, in the absence of a dynamic model and theoretical control methods. The controller also demonstrated its robustness in the adaptive learning of control with imposed system changes.  Index Terms-neural network, antagonistic muscle, muscle actuator, control. ; revised 0, November 2
doi:10.12720/joace.2.3.302-309 fatcat:gf2zrycv5rg5njdxtnktmtuo3i