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In this paper, an intelligent robust controller is proposed for a class of nonlinear systems in presence of uncertainties and bounded external disturbances. The proposed method is based on a combination of terminal sliding mode control and adaptive neuro-fuzzy inference system with bee’s algorithm training. For this purpose, a sliding surface is firstly designed based on terminal sliding control method. This sliding surface is considered as input for the intelligent controller which is an adaptive neuro-fuzzy inference system and using it, terminal sliding mode control law without the switching part is approximated. In the proposed method, an intelligent bee’s algorithm is also used for updating the weights of the adaptive neuro-fuzzy inference system. Compared with fast terminal sliding mode control, the proposed controller provides advantages such as robustness against uncertainty and disturbance, simplicity of controller structure, higher convergence speed compared with similar conventional methods and chattering-free control effort. The method is applied to an atomic force microscope for nano manipulation. The simulation results show the robustness and effectiveness of the proposed method.

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A dc-dc buck converter is an electronic circuit with wide application in power electronics. This converter acts as a nonlinear system then, it is necessary to use a robust controller to control and regulate the output voltage under load changes, circuit elements and other disturbances. In this paper, a new fast terminal sliding mode control (FTSMC) using the property of the terminal attraction as a function of the inverse tangent for buck DC-DC converter is provided. The performance of this new controller is compared with FTSMC common type in terms of output voltage convergence time and input control function structure. The superior property of this controller is low singular effect on the control function. Also, the controller has fast rate of convergence in different situations for output voltage stability in order to use in power electronic device of mechanical motion control systems such as types of robots and electric vehicle are pretty good. Simulation results confirm the proper performance of the new proposed fast terminal sliding mode control method compared to traditional fast terminal sliding mode converter for buck converter.

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The anti-lock braking system is one of the main factors to make safety in designing vehicles. The brake pressure control and desired slip tracking through severe braking cause safety in vehicles. Because of uncertainty in parameters and sever nonlinear factors, robust controller designing is suitable for this system. In this paper the types of sliding mode controller have been used to achieve a vehicle desired slip and its stop. Sliding surface and terminal attractions will be analyzed in all of the designed controllers. Also a new structure with high terminal attraction have been for the fast terminal sliding mode controller (FTSMC). The proposed method has reduced tracking error as well. In this paper, the performance of this controller is compared with normal terminal sliding mode controller and fast terminal sliding mode. Also all design parameters are determined to decrease error ratio using particle swarm optimization (PSO) algorithm. This method is suitable for solving complex optimized solution based on certain cost function. Simulation results with using MATLAB software, present better performance of the suggested controller in comparison with normal and fast terminal sliding mode controller.

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In this paper, we used a non-singular backstepping terminal sliding mode control approach to the unmanned aerial vehicle (quadrotor). In the first step, the governing dynamical equations were obtained based on the quadrotor considering all the effective parameters. The controller objective is limited to obtaining proper tracking of the desired positions (x, y, z) and the yaw angle (ψ), as well as maintaining the stability of the roll and pitch angles despite the presence of external disturbances. Controlling methods require complete information about system states that may be limited in practice. Even if all system conditions are available, it is interfered by noise, and also large number of applier sensors to measure states, makes the entire system more complex and costly. For this purpose, the Extended Kalman Filter (EKF) has been used as an observer. The extended Kalman filter is used as a speed observer and estimator of external disturbances such as wind force. Therefore, the use of a controller-observer is suggested to estimate the effects of external disturbances in order to compensate for them. The design method is based on the stability of Lyapunov. Simulation results show the promising performance and suitability of the observer-controller.

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In this paper, a sliding mode predictive control method is proposed for function improvement of affine discrete-time nonlinear systems using integral terminal sliding mode method (ITSMC). The proposed method is based on the integration of terminal integral sliding mode method and model predictive controller which leads to using the advantages of both methods. Indeed, in the proposed method, integral and terminal characteristics of terminal integral sliding mode method are used to design the sliding surface in order to reduce the error (in reaching phase) and to converge to the origin (in sliding phase). Moreover, the chattering phenomenon which usually exists in sliding mode based methods will be decreased using the model predictive controller. The proposed control method has the capability to eliminate the effect of external disturbances and uncertainties. In this paper, it is shown that the model predictive method decreases the chattering phenomenon more than using the saturation function in the control law of the sliding mode method. In addition, using numerical and functional examples, the performance of the proposed method in improving the quality of the system response in the presence of external disturbances and uncertainties is illustrated.

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