Intelligent Gain Scheduling (igs) Using Neural Networks For Robotic Manipulators

Existing industrial robotic manipulators have proven to be limited in many applications, especially in their payloads and manipulation speeds. This paper presents an Intelligent Gain Scheduling control scheme using neural networks. It advances the idea of mapping the non-linear relationship between robot working conditions (e.g. payload, speed, etc.) and its controller’s gains. The aim of this research is to try to propose an applied robot controller, which is not too expensive, is acceptable to industry and can largely improve the pe~omance of existing robot manipulators. Simulation has shown promising results.