This work proposes a novel impedance control strategy for a delayed bilateral tele-surgery system to perform a drilling process during spinal surgery. In the new designed control scheme, regarding a desired impedance model for master and slave robot, an especial dynamic characteristic at the surgeon and master as well as slave and vertebra interface is designed. Two desired impedance models are proposed for the master and slave robots such that: (a) the salve robot that holds the drilling device should track the master path but complies with the reaction force of the vertebra, and (b) the surgeon should receive feedback from the slave-vertebra interaction force via the master robot. These main objectives are attained by proper adjustment in the proposed impedance model, which does not require any direct measurement of vertebra reflections. Then, the impedance model is put into a proper sliding mode controller to cope with the modeling uncertainties in the slave side. Consequently, the absolute stability concept is utilized to investigate closed-loop system stability and transparency. Finally, the control scheme is implemented on one degree of freedom robotic manipulators as master and slave robot. Experimental results demonstrate the efficiency of the designed impedance control scheme in the presence of modeling uncertainties.

In this paper, one helicopter model with two degrees of freedom (2-DOF) is controlled by fuzzy sliding mode control with boundary layer (FSMC-BL) while exposed to disturbance. The model is a nonlinear and multi-input multi-output (MIMO) system that requires a MIMO, robust, stable, and nonlinear control to reject the disturbance. These requirements have been satisfied by SMC. In this paper, boundary layer removes the chattering phenomenon and fuzzy logic tunes the switching gains of SMC control law online. The simulation results which are achieved for step and sinusoidal disturbances applied to both pitch and yaw angles, are compared with those of PID control based on linear quadratic regulator algorithm (LQR-PID). Considerable improvement in control signal and yaw angle is observed by using FSMC-BL.

Teleoperation systems have been presented to handle objects in environments in which the presence of operators are impracticable, unsafe or less effective. In this paper, a passive control strategy employing the new outputs to state synchronization of the master and slave robots is developed to attain position coordination during contact tasks. The proposed control scheme includes position signals plus force signals. However, force measurement in such applications is a major limitation. Therefore, a modified force estimation algorithm is proposed to predict external forces applied on the master and slave robots. The closed-loop bilateral teleoperation system is investigated by employing Lyapunov stability criteria. Finally, the experimental results demonstrate the efficiency of the proposed control scheme. It is observed that, in the presence of the estimated external forces in the control scheme, the slave robot follows the master position in both free and contact motion, and force reflecting occurs properly as well. Moreover, it is verified that the external forces are estimated appropriately through the proposed force estimation algorithm.

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Electroencephalography (EEG) is a major clinical tool to diagnose, monitor and manage neurological disorders which is mostly affected by artifacts. Given the importance and the need for an automated method to remove artifacts, in this paper some intelligent automated methods are proposed which are composed of three main parts as extraction of effective input, filtering and filter optimization. Wavelet transform is utilized to extract the effective input, and the wavelet approximation coefficients are used as an effective input signal. In addition, Radial Basis Function Neural Network (RBFNN) has been used for filtering. The appropriate number of RBFs has been selected using extensive simulations, and the optimal value of spread parameter has been achieved by Bees algorithm (BA). Finally, the proposed artifact removal schemes have been evaluated on some real contaminated EEG signals in Mashad Ghaem hospital database. The results show that the proposed artifact removal schemes are able to effectively remove artifacts from EEG signals with little underlying brain signal distortion.

Control of the force exerted on an object is important for boosting system performance in robotics manipulators. Any undesired applied force may leave remarkable effects on the system, with the potential to damage the object. In addition, measuring external force is another challenge associated with such cases. Proposing an appropriate force estimation algorithm is a solution to overcome this deficiency. In this research, a control strategy is proposed to control the external force applied on the n-dof robotics. To eliminate force measurement in the controller, a force estimation strategy based on a disturbance observer is employed. Subsequently, a sliding-mode based control is implemented to cope with the force estimation error. The closed-loop stability of the system in the presence of estimated force is analytically considered. The proposed algorithm was implemented on piezoelectric actuators as the experimental setup. The experimental results confirm that by employing the proposed control scheme, precise force control is achievable. The force estimation algorithm can also suitably estimate external force.

Sub-synchronous oscillation occurs in frequency less than synchronous frequency, in transmission systems compensated by series capacitor and in a state of equilibrium of the system, it imposes great disturbance which brings about tortional modes with varied frequencies in the shaft of the generator which ultimately can result in fatigue in the shaft of the turbine-generator and even might result in fracture in the shaft with irrecoverable damages. To damp and to control the sub-synchronous oscillations, exciter voltage controller was employed in this study. In line with the improvement of this controller, fuzzy control method was used. The results of simulation confirm the effect of fuzzy controller optimization in this system.