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Continuum robot manipulators are optimized to meet best trajectory requirements. Closed loop control is a key technology that is used to optimize the system output process to achieve this goal. In order to conduct research in the area of closed loop control, a control oriented cycle-to-cycle continuum robot model, containing dynamic model information for each individual continuum robot manipulator, is a necessity. In this research, the continuum robot manipulator is modeled according to information between joint variable and torque, which is represented by the nonlinear dynamic equation. After that, a multi-input-multi-output baseline computed torque control scheme is used to simultaneously control the torque load of system to regulate the joint variables to desired levels. One of the most important challenge in control theory is on-line tuning therefore fuzzy supervised optimization is used to tune the modified baseline and computed torque control coefficient. The performance of the modified baseline computed torque controller is compared with that of a baseline proportional, integral, and derivative (PID) controller.

Design PID Baseline Fuzzy Tuning Proportional- Derivative Coefficient Nonlinear Controller with Application to Continuum Robot