Adaptive Fuzzy Control of Uncertain Nonlinear System using RLSE Compared to Feedback Linearization method

This paper presents an Adaptive Fuzzy Logic modeling and control (AFLC) of the nonlinear system associated with uncertainty, and also the Feedback Linearization method, to control proposed dynamic. In fuzzy method to estimate the uncertain part of the system, fuzzy logic systems are used. To speed up the learning of fuzzy systems with in-line or off-line of proposed algorithm, and also for reducing the error of the system against the unwanted changes and variation of the inputs parameters, Recursive Least Square Estimation (RLSE) method is used. To comparing the robustness of the system against the changing of the parameter the Feedback Linearization (FBL) method is also used for controlling the proposed dynamic.The effectiveness of our approach in recursive least square method and also the feedback linearization strategy of control are surveys on Prismatic-Revolute (P-R) manipulator, with uncertainty in its inputs