A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...

The control of nonlinear chaotic systems with uncertainties is a challenging problem that has attracted the attention researchers in recent years. In this paper, we propose robust adaptive fuzzy fractional strategy for stabilizing uncertainties. proposed combined logic controller fractional-order calculus to accurately model system’s behavior and adapt real-time. was based on supervised sliding...

The remarkable properties of sliding mode control (SMC)—such as robustness, accuracy, and ease implementation—have contributed to its wide adoption by the community. To accurately compensate for parametric uncertainties, switching part SMC controller should have gains that are sufficiently large deal with but small minimize chattering phenomena. Hence, proper adjustment is crucial ensure accura...