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In this paper, an adaptive robust tracking control system for an unmanned quadrotor is designed .Quadrotor placed in category of rotary wing aerial vehicle, and it is an under actuated and inherently unstable system. Also the dynamic model of system is nonlinear and along with the Uncertainty, therefore it is required to design a robust control system for stabilization and tracking the desired path. This system must be capable to retain the quadrotor balance in the presence of the disturbance, undesired aerodynamical forces and Measurement error of constant parameters. The suggested controller in this paper consists of two inner and outer control loops. Inner loop controls the Euler angles and outer loop is for control the quadrotor position and translational motion, and calculating the desired angles for trajectory tracking. In this paper by utilizing the adaptive sliding mode, the controller has been designed which is no need to be given the uncertainty range and the upper bound of it will be estimated as a scalar number. In order to prevent from diverging adaptive parameters, the sigma-modification is used in adaption laws and also to achieve suitable performance in various load, the total mass is estimated adaptively. The control design is based on the Lyapunov theory and the robust stability of system in the presence of the disturbance have been shown.

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Cell injection system in medicine used to inject the materials into the cells. The injection system consists of Injector and rotating plate. The controller sets height, position and orientation of the rotating plate. The proposal of this article is to replace SCARA robot injection tool and it included ability in desired position tracking and applied to time-varying force. In recent articles the control system applies to the rotating plate of Cells and this method can cause the damaging risk. The proposed method is fixed plate and to increase the success rate, the robot had been controlled. The parameters of environmental models are estimated by nonlinear proposed models and by using the recursive method, the minimum of squares errors will be optimal. The voltage strategy can control robot actuators. This method is simpler and free from the manipulator dynamics. In all recent studies, the impedance control is based on the torque control method and the proposed method of this article is applying the impedance control using voltage control. The robust adaptive impedance controller is designed in the presence of uncertainties. The simulation's results demonstrate desired performance of the proposed method

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In this paper, a novel dynamical model is proposed for the multi-input multi-output electrically driven robot manipulators, by an observer-based robust adaptive fuzzy controller. The proposed control scheme utilizes current control effort, which is more efficient than the torque control approach. The proposed method is very simple, accurate and robust. Based on the adaptive fuzzy system an observer-based estimator is presented that uses feedback error function as the input of fuzzy system to approximate and adaptively compensate the unknown uncertainties and external disturbance of the system under control. Although the proposed controller scheme requires the uncertainties to be bounded, it does not require this bound to be known. An H_∞ robust controller is employed to an attenuate the residual error to the desired level and recompenses the both fuzzy approximation errors and observer errors. The proposed method guarantees the stability of the closed-loop system based on the Strictly Positive Real (SPR) condition and Lyapunov theory. The proposed control scheme is not limited only for controlling of robotics vehicles, it can be applied for a class of nonlinear MIMO systems. Finally, in simulation study, to demonstrate the usefulness and effectiveness of the proposed technique, a two-link robot manipulator system is employed.