Modeling of Nonlinear 3-RRR Planar Parallel Manipulator: Kinematics and Dynamics Experimental Analysis

Parallel Manipulators (PMs) are gaining increasing importance, due to their superiority over serial manipulators in industry  in  terms  of  smaller  workspace  (WS),  speed  and precision. In this paper, the design, workspace analysis, modeling and  control  of  a  novel  3-RRR  Planar  Parallel  Manipulator (PPM) are proposed. Because the kinematic constraint equations are  complex  due  to the  nonlinear  behavior,  non-conventional methods are used to model the system and control it. The Neuro- Fuzzy Inference System (NFIS) is used for forward kinematics modeling, while the Neural Networks (NN) and Adaptive Neuro- Fuzzy Inference System (ANFIS) are used for inverse kinematics modeling. Two metaheuristic optimization techniques, PSO and GA, were  used for parameter  tuning in  the NFIS model.  The results show that the used techniques were accurate in capturing the system dynamics. Thus, they enable precise and fast control using them, instead of using the coupled kinematical equations