Design Robust Artificial Intelligence Model-base Variable Structure Controller with Application to Dynamic Uncertainties OCTAM VI Continuum Robot

Design a robust artificial intelligent nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This paper focuses on the design of a robust chattering free mathematical model-base artificial intelligence (fuzzy inference system) variable structure controller (MFVSC) for highly nonlinear dynamic continuum robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, variable structure controller is selected. Pure variable structure controller can be used to control of partly known nonlinear dynamic parameters of continuum robot manipulator. In order to reduce/eliminate the chattering, this research is used the artificial intelligence (fuzzy logic) theory. The results demonstrate that the model base fuzzy variable structure controller with switching function is a model-based controllers which works well in certain and partly uncertain system. Lyapunov stability is proved in mathematical modelbased fuzzy variable structure controller with switching (sign) function. This controller has acceptable performance in presence of uncertainty (e.g., overshoot=1%, rise time=0.9 second, steady state error = 1.6e-8 and RMS error=4.8e-8).