Nonlinear Fuzzy Model-base Technique to Compensate Highly Nonlinear Continuum Robot Manipulator

Refer to this research, a gradient descent optimization methodology for position fuzzy- model based computed torque controller (GDFCTC) is proposed for highly nonlinear continuum robot manipulator. The main problem of the pure computed torque controller (CTC) was equivalent problem in uncertain systems. The simulation results exhibit that the CTC works well in certain system. To eliminate the continuum robot manipulator system’s dynamic; Mamdani fuzzy inference system is design and applied to CTC. This methodology is based on applied fuzzy logic in equivalent nonlinear dynamic part to estimate unknown parameters. This relatively controller is more plausible to implement in an actual real-time when compared to other techniques of nonlinear controller methodology of continuum arms. Based on the gradient descent optimization method, the PD-gain updating factor has been developed in certain and partly uncertain continuum robots. The new techniques proposed and methodologies adopted in this paper supported by MATLAB/SIMULINK results represent a significant contribution to the field of design an optimized nonlinear computed torque controller for continuum robots.