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Design New Nonlinear Controller with Parallel Fuzzy Inference System Compensator to Control of Continuum Robot Manipulator

Sliding Mode controller (SMC) is a highly significant nonlinear controller under condition of certain and partly uncertain dynamic parameters of system. This controller is used to control of highly nonlinear systems especially for continuum robot manipulators, because this controller is a robust and stable. In opposition, conventional sliding mode controller is used in many applications; it has two important drawbacks; chattering phenomenon and nonlinear equivalent dynamic formulation in uncertain dynamic parameter. To reduce or eliminate the chattering two methods is used; modified proportional-derivative boundary derivative sliding function and design a nonlinear sliding surface function based on fuzzy inference system and applied to sliding mode controller. The nonlinear equivalent dynamic formulation problem in uncertain system can be solved by applied artificial intelligence theorem (e.g., fuzzy inference system). Based on this research chattering eliminated based on applied modified sliding function and fuzzy inference engine and this controller is more robust than conventional sliding mode controller and simple fuzzy sliding mode controller.