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In this paper, a new approach for controller designing of robust output feedback model reference adaptive control with a function of tracking error for a class of continuous linear systems with multiple uncertain time varying state delays is introduced. Proposed controller is not only robust versus of multiple uncertain time delays and external disturbance with uncertain bound but also improve performance of transient and steady state of closed loop system. The stability of closed loop system and error convergence is shown with an appropriate Lyapunov-Krasovskii function. Simulation results show good performance of proposed controller.

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This paper proposes an adaptive control method based on the feedback linearization technique and a proposed neural network,  for tracking and position control of an industrial manipulator. At first, it is assumed that the dynamics of the system are known and the control signal is constructed  by the feedback linearization method. Then to eliminate the effects of the uncertainties and external disturbances, the parameters of the proposed neural network are learned based on the Lyapunov method such that the sliding condition to be satisfied. The performance of the proposed method is compared with the sliding mode technique in presence of external disturbance, delay and uncertainties. The simulation results verify that the proposed method is effective and can be used in many applications.

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In this paper, a fractional-order robust adaptive intelligent controller (FRAIC) is designed for a class of chaotic fractional order systems with uncertainty, external disturbances and unknown time-varying input time delay. The time delay is considered both constant and time varying. Due to changes in the equilibrium point, adaptive control is used to update the system's momentary information and the intelligent controller is used to estimate the uncertainties and disturbances and non-linearities of the system according to the momentary information obtained. The sliding mode control, which provides closed loop asymptotic stability in the system despite the uncertainties and disturbances, is used as a robust controller. Using the Lyapunov theorem and Barbalat's Lemma, the asymptotic stability of a chaotic fractional order system with input delay and uncertainty as well as external disturbance is proved by designed controller. Finally, using the simulation results of financial as well as supply and demand systems, the performance of designed controller would be examined.