Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator | Zendy

Farzin Piltan | Zendy; Ali Badri | Zendy; Javad Meigolinedjad | Zendy; Mohammad Hossein Keshavarz | Zendy

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Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator

Author(s) -

Farzin Piltan,

Ali Badri,

Javad Meigolinedjad,

Mohammad Hossein Keshavarz

Publication year - 2013

Publication title -

international journal of intelligent systems and applications

Language(s) - English

Resource type - Journals

eISSN - 2074-9058

pISSN - 2074-904X

DOI - 10.5815/ijisa.2013.09.12

Subject(s) - computer science , controller (irrigation) , robot , nonlinear system , control theory (sociology) , frame (networking) , torque , metric (unit) , artificial intelligence , simulation , control (management) , engineering , agronomy , biology , telecommunications , operations management , physics , quantum mechanics , thermodynamics

This research involved developing a surgical robot assistant using an articulated PUMA robot running on a linear or nonlinear axis. The research concentrated on studying the artificial intelligence based switching computed torque controller to localization of an endoscopic tool. Results show that the switching artificial nonlinear control algorithm is capable to design a stable controller. For this system, error was used as the performance metric. Positioning of the endoscopic manipulator relative to the world coordinate frame was possible to within 0.05 inch. Error in maintaining a constant point in space is evident during repositioning however this was caused by limitations in the robot arm

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