In this research, intelligent adaptive backstepping control is presented as robust control for continuum robot. The first objective in this research is design a Proportional-Derivative (PD) fuzzy system to compensate the system model uncertainties. The second objective is focused on the design tuning gain adaptive methodology according to high quality partly nonlinear methodology. Conventional backstepping controller is one of the important robust controllers especially to control of continuum robot manipulator. The fuzzy controller is used in this method to system compensation. In real time to increase the system robust fuzzy logic theory is applied to backstepping controller. To approximate a time-varying nonlinear dynamic system, a fuzzy system requires a large amount of fuzzy rule base. The adaptive laws in this algorithm are designed based on the Lyapunov stability theorem. This method is applied to continuum robot manipulator to have the best performance.

The Proportional Integral Derivative (PID) Fuzzy Sliding Mode Controller (FSMC) is the most widely used control strategy in the Industry (control of robotic arm). The popularity of PID FSMC controllers can be attributed to their robust performance in a wide range of operating conditions and partly to their functional simplicity. The process of setting of PID FSMC controller can be determined as an optimization task. Over the years, use of intelligent strategies for tuning of these controllers has been growing. Biologically inspired evolutionary strategies have gained importance over other strategies because of their consistent performance over wide range of process models and their flexibility. This paper analyses the modified PID FSMC controllers based on minimum rule base for flexible robot manipulator system and test the quality of process control in the simulation environment of MATLAB/SIMULINK Simulator.