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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.

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Brushless direct current motors have been considered by many researchers due to their many advantages over other direct current motors. The upper band is unknown and aims to converge in a limited time. For this purpose, by rewriting the motor model in the presence of modeling uncertainties and limited external perturbations, the terminal slip mode control law is designed to stabilize the system and converge the output speed and motor flow to the desired values ​​in a finite time, using the development theorem. In this control law, the high bandwidth of total uncertainties and external disturbances is estimated online using an adaptive law. Finally, while calculating the system convergence finite time, an idea to reduce the umbrella in using the terminal slip mode control is presented. The results of the numerical simulations performed show the accuracy of the designed controllers.

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This paper presents a new method of the adaptive non-singular Second-order Terminal Sliding Mode (SOTSM) control for the fast and finite time stabilization of Cyber-Physical Systems (CPSs) in the simultaneous presence of parametric uncertainties, unwanted disturbances and actuator cyber-attacks. By utilizing the presented non-linear manifold and sliding surface, the reaching mode is deleted and the entire system’s robust performance is improved. The proposed online adaptive laws deal with parametric uncertainties, unwanted disturbances and cyber-attacks, so that there is no need to identify their upper bounds. The designed adaptive non-singular SOTSM control method guarantees the robust performance of the system in the mentioned conditions along with fast and smooth response, high accuracy and flexibility, without transient fluctuations and chattering, as well as proper convergence in finite time. The numerical simulation results show the effectiveness and success of the adaptive non-singular second-order terminal sliding mode control method in comparison with the results of adaptive integral sliding mode control, traditional sliding mode control and state feedback control.