Applications of Artificial Intelligence Control for Parallel Discrete-Manipulators

Parallel Discrete-Manipulators are a special kind of force regulated manipulators which can undergo continuous motions despite being commanded through a large but finite number of states only. Real-time control of such systems requires very fast and efficient methods for solving their inverse static analysis. In this paper, artificial intelligence techniques (AI) are investigated for addressing the inverse static analysis of a planar parallel array featuring ten three-state force actuators and two applications using 3D Massively Parallel Robots (MPRs) with one and two layers. In particular, the research method used simulation software and hardware testing with the case of parallel manipulator with two level discrete pneumatic actuators. Simulations with typical desired displacement inputs are presented and a good performance of the results compared to AI is obtained. The comparison showed that the parallel manipulator has the Root Mean Squared Error (RMSE) has less than 10% and can be used for controlling the ternary states of discrete manipulators via AI.