A Practical Neuro-fuzzy Mapping and Control for a 2 DOF Robotic Arm System

Ebrahim Mattar
2013 International Journal of Computing and Digital Systems  
Relating an arm Cartesian space to joint space and arm dynamics, is an essential issue in arm control that has been given a substantial attention by number of researches. Arm inverse kinematic, is a nonlinear relation, and a closed form solution is not a straight forward, or does not even always exist. This research is presenting a practical use of Neuro-Fuzzy system to solve inverse kinematics problem that used for a two links robotic arm. The concept here is to learn kinematics relations for
more » ... robotic arm system. This is to learn and map its environment and remembers what it learnt. For learning the inverse kinematics, Neuro-fuzzy needs information about coordinates, joint angles and actuator position. Information flow needed for the training for a Neuro-fuzzy network is slow and difficult to get by measuring the real structure. Desired Cartesian coordinates are given as input to a Neuro-fuzzy that returns actuator positions. Hence to express them as linguistics fuzzy rules. Neuro-fuzzy system is to generalize and produce an appropriate output. The assembled system has been equipped with C ++ interface routines, as being executed from a MATLAB environment, in addition to high-speed low-level communication with the robotic arm sensing devices.
doi:10.12785/ijcds/020302 fatcat:f3x52ecqazef3kru3y2lm52rde