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Abstract In recent years many researches have been focused on active magnetic bearing (AMB) systems. AMB offers advantages such as, contact less and friction free operation, excellent performance over a wide range of temperature, no need for lubricant and longer life. Technology of magnetic bearings can be considered as a new field of research in Iran. This paper presents design, manufacturing and control of a magnetically levitation system with successful operation. This research concluded with documentation of the AMB technology which is prerequisite for earning the technology of active magnetic systems (AMS) and paves the way to develop it.

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This paper introduces an indirect adaptive fuzzy sliding mode controller as a power system stabilizer for damping local and inter-area modes of oscillations of multi-machine power systems. This controller is designed based on the combination of sliding mode controller and the fuzzy logic systems. The fuzzy systems are used to approximate the unknown functions of power system model. Generator speed deviation and accelerator power are selected as fuzzy logic system inputs. A new sliding mode control law achieved by changing the sliding condition and the undesirable chattering has been removed by using of a continuous function. Based on the Lyapunov synthesis, adaptation laws are developed. Performance of the proposed stabilizer is studied for a two-area four-machine power system. Simulation results show the effectiveness of the proposed controller in comparison with multi-band power system stabilizer (MB-PSS), classical adaptive fuzzy sliding mode stabilizer and adaptive fuzzy sliding mode stabilizer with a proportional integral function (PI).

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In this paper, an optimal adaptive fuzzy integral sliding mode control is presented to control the robot manipulator position tracking in the presence of uncertainties and permanent magnet DC motor. In the proposed control, sliding surface of the sliding mode control is defined according to the information of position tracking error, derivatives, and error integral. In order to estimate bounds of the existing structured and unstructured uncertainties in the dynamics of the robot manipulator and the permanent magnet DC motor, a MIMO fuzzy adaptive approximator is designed. This helps to overcome the undesired chattering phenomenon in the control input by using fuzzy logic. Mathematical proof shows that the closed-loop system with the adaptive fuzzy integral sliding mode control in the presence of all the uncertainties has the global asymptotic stability. Furthermore, modified harmony search optimization algorithm is used to define the input coefficients of the proposed control and also to reduce the control input amplitude. In order to validate performance of the proposed controller, a case study on the SCARA robot manipulator is conducted in the presence of permanent magnet DC motor. Results of the Simulation show desired performance of the proposed controller.

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Friction is an inevitable issue in most of mechanical servo systems. Friction has a counter-effect on the dynamic performance of servo mechanisms and needs to be considered in the design process. Particularly, in high-performance motion systems, friction can severely deteriorate performance and can cause tracking errors, longer settling time and limit cycles. In this paper, a new method is presented based on the adaptive fuzzy sliding mode control strategy for position control of mechanical systems. The first order dynamic LuGre model is used for the design of friction observer. Unlike previous papers, the control input and friction are applied to the system with non-equal gains. An adaptive law is employed for the estimation of the ratio between the gains of input and friction terms. Various uncertainties on parameters of friction also are considered and an appropriate control strategy is designed to tackle these uncertainties.

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Tractor-trailer wheeled mobile robot (TTWMR) is a robotic system that consists of a tractor module towing a trailer. Trajectory tracking is one of the challenging problems which is focused in the context of wheeled mobile robots (WMRs) that has been discussed in this paper. First, kinematic equations of TTWMR are obtained. Then, reference trajectories for tracking problem are produced. Subsequently, an output feedback kinematic control law and a dynamic Fuzzy Sliding Mode Control (FSMC) are designed for the TTWMR. The proposed controller steer the TTWMR asymptotically follow reference trajectories. Finally, experimental results of the designed controller on an experimental setup and comparison results are presented. Obtained results show the effectiveness of the proposed controller.

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Nonlinear factors such as air compressibility, leakage and friction make the control of pneumatic systems complex. Model-based robust control strategies are appropriate candidates for pneumatic systems, however in such controllers the measurement of state variables of the system are needed. In a pneumatic system the state variables are position and velocity of the actuator, and pressure in both sides of the cylinder. Pressure measurement is usually obtained by means of costly and low response sensors. A better way to deal with the measurement problem is to use observers to reconstruct the missing velocity and pressure signals. However the problem in a pneumatic system is that the system is not observable and pressure signals could not be observed by means of position signals only. To deal with this problem, in this paper, the pneumatic actuator is modeled as two separate chambers and the resulting subsystems are observable independently. High gain observers are designed for mentioned subsystems and for each chamber the pressure of the other chamber is considered as a disturbance. The input signal for each observer is the actuator position signal only. Finally a sliding-mode control strategy is designed for position tracking and experimental results verify that both controller and observer objectives are satisfied.

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The present study aims to implement an approach for trajectory control of a 3-RPR parallel manipulator over a path with obstacles in the workspace. For this purpose, using the spline curves approach and based on the cuckoo optimization algorithm, a smooth reference trajectory with minimum length is generated in the workspace to avoid robot collision with obstacles. The performance and accuracy of the cuckoo optimization algorithm in converging to the optimal solution is then compared with the Genetic algorithm. In the next step, the robust sliding mode control technique is adopted for trajectory control of the robot in the presence of some uncertainties. These uncertainties usually include the links length and links mass of the robot. The obtained results confirm the demanded level of performance and accuracy of the cuckoo optimization algorithm. It is also observed that the optimal trajectory with minimum length is generated using the spline curves approach. In addition, it is concluded that based on the sliding mode control technique, the robot can follow the desired trajectory very precisely in spite of the presence of the uncertainties in length and mass of the robot's links.

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High-precision three-axis attitude control scheme is vitally important to deal with the overactuated spacecraft, as long as the overall performance through rapid response can be in general acquired. Due to the fact that the rigid-flexible spacecraft is somehow applicable, in so many academic and real environments, there is a consensus among experts of this field that the new insights in developing the present complicated systems modeling and control are highly recommended with respect to state-of-the-art. The new hybrid control scheme presented here is organized in line with the linear approach, which includes the proportional derivative based quadratic regulator and the nonlinear approach, which includes finite-time sliding mode control, as well. It should be noted that the three-axis angular rates of spacecraft under control are all dealt with in inner closed loop control and the corresponding rotation angles are also dealt with in outer closed loop control, synchronously. 

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The problem of two wheeled self-balancing robot is an interesting and challenging problem in control and dynamic systems. This complexity is due to the inherent instability, nonholonomic constraints, and under-actuated mechanism. Dynamical model of two wheeled self-balancing robot can be presented by a set of highly coupled nonlinear differential equations. Authors, previously, developed the modified dynamical equations of the robot. The governed equations have some differences with the commonly used equations. The main difference is due to the existence of a nonlinear coupling term which is neglected before. In this paper we used an adaptive sliding-mode controller based on the zero dynamics theory. The controller objective is to drive the two wheeled self balancing robot to the desired path as well as to make the robot stable. By some simulations the behavior of the robot with the proposed controller is discussed. It is shown that if the nonlinear coupling term is ignored in designing the controller, the controller cannot compensate its effect. Using Lyapunov theorem and the invariant set theorem, it is proved that the errors are globally asymptotically stable.

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Performance increasing of robot-aided training in stroke elbow rehabilitation is the goal of this paper. Therapist holds on the arm of patient and guides the center of mass along a desired trajectory. In robotic rehabilitation, when the arm of patient rotate within the desired boundaries, (s)he should ideally not feel the robot. The robot needs to actively compensate for the weight of the exoskeleton and reflected mass of the motors. A nonlinear torsion spring can be used and also a counter-torque as a function of arm angle is applied by the motor. Applying the springs affords more convenience, it allows smaller motors to be used, the size of required brakes can be reduced and inherent safety is introduced in rehabilitation robots. Furthermore, the robust controller design can be used to compensator the modeling errors and gravitational force. A novel elbow rehabilitation robot is designed based on the cable actuation. The strategy is not just anti-gravitational forces because there should be joint-stiffness control. The uncertainty in the patients arm dynamic is effectively approximated. The motion of closed-loop control system in the presence of parametric uncertainties is investigated. The sliding mode controller with proportional-derivative controller is compared through computer simulation and improvement is observed.

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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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In this paper, a new approach has been presented for dynamic control of active suspension vehicle system subject to the road disturbances. The active suspension system (ASS) which has been considered in this paper is operated by a hydraulic actuator. The input of this hydraulic actuator is a servo valve. In the other word, both mechanical equation of system (related to hydraulic actuator) and its electrical equation (related to servo valve) are considered. Therefore, the equations are complicated and only the input current of servo valve is accessible as the input control signal. The proposed approach is based on dynamic sliding mode control (DSMC).In DSMC chattering is removed due to the integrator which is placed before the input control signal of the plant. However, in DSMC the augmented system (the system plus the integrator) is one dimension bigger than the actual system and then, control of the plant is more complicated. But, its advantage is that the input control signal is obtained from a dynamic system or a low pass filter, while the robust performance (invariance property) of the system is reserved even in the presence of disturbance. Another advantage of proposed approach is that the desired output force of the hydraulic actuator is obtained by the controller.

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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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In this article, trajectory generation, control and hardware development of a knee exoskeleton robot is provided. The robot aims to help the individuals with lower extremity weakness or disability during the sit-to-stand movement. In the trajectory generation phase, a new method is proposed which uses a library of sample trajectories to predict the sit-to-stand movement trajectory based on the initial sitting conditions of the user. This method utilizes the theory of "dynamic movement primitives" to estimate the sit-to-stand trajectory. The trajectory generation method is tested on a library of human motion data which has been obtained in a laboratory of motion analysis. In the next step, an exponential sliding mode controller is used to guide the robot along the predicted trajectory. The controller and the trajectory generator are implemented on the exoskeleton robot. For the hardware development, the xPC Target toolbox of MATLAB software and a data acquisition card was used. Finally, the robot was tested on a male adult. The subjects were asked to wear the robot while doing several sit-to-stand movements from various sitting positions. According to the results, the average power which is required to be applied by the user’s knee, is less when the exoskeletons assists him.

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Shape memory alloys (SMAs) are suitable candidates in various fields of engineering. One advantage of these alloys is their capabilities in developing high strain and force. In addition to these great features, lightweight and super-elastic behavior are other traits of these materials. These specifications are of such an importance that make SMAs to be suitably used in further engineering applications. However, their intrinsic hysteresis non-linear behavior make their usage as position actuators difficult. Despite this challenge, there are various methods proposed in the literatures to model the hysteresis behavior of such materials. In this paper, a generalized Prandtl- Ishlinskii model, because of its simplicity, efficiency and inverse analytical capability, has been used for modeling the SMA behavior. In addition, the hysteresis modeling has been validated via experimental data of one of the articles. In the control section, however, two control systems consisting PID and fuzzy sliding mode controllers have been used. Fuzzy sliding mode control system is a method that can be used in systems without mathematical model and leads to increase in their robustness. It is shown in this paper that by using this method, it is possible to apply a suitable control input to the system in order to vanish the error signal. However, by using PID controllers, the error signal is not acceptable due to the constant controller coefficients. The results indicate the more efficient performance of fuzzy sliding mode controller with respect to the classical PID controller.

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Piezoelectric actuators (PA) are widely used in electromechanical system thank to interesting properties such as: high resolution, fast response, wide bandwidth, mechanical simplicity, high stiffness. Despite these unique desirable properties, they suffer from nonlinear behaviors which adversely affect the positioning accuracy. Among them, hysteresis between applied voltage , actuator position is the most important nonlinearity which can lead to significant error if not compensated. In this study, a sliding mode controller associated with an unknown input observer, which uses the position feedback provided by a selfsensing circuit, is suggested to use in micro positioning applications. The selfsensing technique is based on the linear relation between position , charge, which is measured by an active charge measurement circuit. The advantages of proposed scheme could be summarized as follows. It is a sensorless method which does not need an external position sensor. It does not need any operators to model hysteresis or its inverse. It has improved performance in comparison to traditional controllers like proportional integral (PI) controller. Obtained experimental results demonstrate the effectiveness of proposed method to use in micro-positioning applications.

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In this paper, dynamic modeling and control of a three-degrees-of-freedom parallel robot with pure translational motion is performed. Constraint equations are derived based on the kinematic model of the robot and Lagrange method is applied to derive the dynamic equations. In order to control the robot position on planned reference trajectories, in presence of uncertainties of the dynamic model, a sliding mode controller is designed which is robust against the uncertainties and induced noises. Performance of the designed controller is simulated and evaluated in different conditions including the presence of noise and parameters variation. In this regard, a comparison has been made between the response of the proposed sliding mode controller and response of a feedback linearization controller, indicating their capabilities in noise rejection and compensation of parameters variation. Also, the effect of defining different sliding surfaces on the performance of the sliding mode controller, and using the integral of error instead of the error itself, have been studied and examined. Results show that the proposed sliding mode controller has a desirable performance in tracking the reference trajectories in presence of the model uncertainties and noise for this kind of parallel mechanism.

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One of the most important factors in surveillance systems using robots, is the complexity and unpredictability of the robot trajectories. This becomes more vital in hostile conditions where the robot trajectory is being followed by another agent. Therefore, random or chaotic sequences can be used in motion planning of surveillant robots. However chaotic sequences would be more effective due to their deterministic nature. Moreover the intrinsic robustness and ergodicity of chaotic systems, compared to random functions, would be another advantage to be considered in surveillance systems which require comprehensive coverage. In this paper, a method is proposed for chaotic motion planning for boundary surveillance and implemented to a quadrotor robot. Quadrotor robot is introduced as an appropriate choice for boundary surveillance application due to high maneuverability and aerial functions. The chaotic trajectory is produced using Henon map. Then the dynamics of the system is derived and a sliding mode controller is designed for such chaotic motion. Finally the dynamics of the robot and the proposed controller are simulated to generate the chaotic trajectories for two cases. The performance of the proposed algorithm is discussed according to unpredictability and staying in the allowable region. A circular path and a non-smooth path are considered for simulation examples.

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Nowadays, movement of micro/nano particles has been attracted considerable attention to manufacturing different devices in micro/nano scale and medical and biological applications. Atomic Force Microscope Probe is widely being used for precise small scale movements. During nano-manipulation, micro/nano particles can be moved to a desired destination with high accuracy using Atomic Force Microscope while in contact mode with precise probe control. In this article, by selecting a proper amount of torque applied to the probe tip, deviation from the center and movement of probe have been investigated to assure the contact between the probe and micro/nano particle. Different liquid environments (water, alcohol, and plasma) with different micro/nano particles including biological and non-biological have been used for this investigation. In addition, using sliding mode control, Atomic Force Microscope Probe was used in different environments such as water, alcohol, and plasma. Obtained results showed that the time needed to control different micro/nano particles in plasma was shorter than that of in water; also the time needed in water was shorter than that of in alcohol.

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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.