Image Based Visual Servoing Using Proportional Controller with Compensator

Abstract

The main objective is to design a proportional controller of a robot manipulator using the fuzzy cerebellar model articulation controller based on Takagi -- Sugeno (T -- S) framework with a compensator. The controller and compensator apply in visual servoing, including system identification of image and kinematic Jacobians. The proposed approach is basically as a function of the visual error and extent from the error with respect to desire visual feature. This approach leads to enormous reduction on computational expense compared to the image-based approaches of model inverse kinematics. The design of the controller architecture will make it possible to implement in general case. Proportional control variable are learned offline with the help of FCMAC-T-S model, and online compensator scheme has been proposed for adapting possible uncertainties in the unknown system and environment. Stimulation results have shown that visual servoing for tracking static target can be achieved using the proposed controller with compensator.