Design New Artificial Intelligence Base Modified PID Hybrid Controller for Highly Nonlinear System

Design a nonlinear controller for second order nonlinear uncertain dynamical systems is one of the most important challenging works. This research focuses on the design, implementation and analysis of a new modified proportional-integral-derivative (PID) hybrid fuzzy controller for highly nonlinear dynamic continuum robot manipulator, in presence of uncertainties. In order to provide high performance nonlinear methodology, modified PID controller in presence of boundary derivative part, computed torque controller (CTC) and fuzzy inference system are selected. Linear PID controller can be used to control of partly known nonlinear dynamic parameters of robot manipulator. Pure CTC is used to estimate highly nonlinear parameters, this controller has an important drawback; nonlinear equivalent dynamic formulation in uncertain dynamic parameter. In order to solve the uncertain nonlinear dynamic parameters, implement easily and avoid mathematical model base controller, Mamdani’s performance/error-based fuzzy logic methodology with one input and one output and 7 rules is applied to proposed methodology. The results demonstrate that the proposed method is a partly model-free controller which works well in certain and partly uncertain system.