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The forward kinematic problem of parallel robots is always considered as a challenge in the field of parallel robots due to the obtained nonlinear system of equations. In this paper, the forward kinematic problem of planar parallel robots in their workspace is investigated using a neural network based approach. In order to increase the accuracy of this method, the workspace of the parallel robot is divided into a number of smaller subspaces using the classifier and the boundary overlap method. After estimating the corresponding subspace, two separate neural networks are used in each subspace to determine the position and orientation of the moving platform. This approach is implemented on a 3-PRR planar parallel robot and its results are compared with the results obtained from the MLP, WaveNet, GMDH, Dual and Independent neural networks. Moreover, in order to evaluate the efficiency of the proposed method, a circular motion path is simulated using this approach and its performance is compared with the five mentioned methods. The results obtained from the implementation of this approach and comparison with the conventional methods indicates that the proposed method analyzes the forward kinematic problem of planar parallel robot with proper accuracy.

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In this paper, a new output feedback control method was used based on a linear matrix inequality to control the angular position of AC servo motor shaft. The proposed control method does not need to measure all of the AC servo motor statuses; it only uses the output feedback and is robust against the uncertain servo motor parameters and the disturbances applied to it. The proposed control method was compared in several scenarios with a Standard Internal Model Control-Sliding Mode Control (SIMC-SMC) method, 2-Degree-of-Freedom Internal Model Control-Sliding Mode Controller (2DOF-IMC-SMC) method, 2-Degree-of-Freedom Internal Model Control-Proportional-Integral-Derivative (2DOF-IMC-PID) method, Standard Internal Model Control-Proportional-Derivatives (SIMC-PD) method, and Internal Model Control-Proportional-Integral-Derivative-Extended State Observer (IMC-PID-ESO) method. The simulation results show that the proposed controller has desirable performance against disturbances and uncertain parameters of the AC servo motor compared with other mentioned controllers. This method relative to other controllers decreased the error of tracking the angular position of the servo motor to 30% .The simulation was performed in the Matlab Software. 

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In an islanded microgrid, power electronic converters are used to exchange power, and these converters have very low inertia, thus compromising the frequency stability of the microgrid. Virtual inertia control is used to improve the frequency stability of an islanded microgrid. The derivative control technique is usually used to implement virtual inertia control in the microgrid. Factors such as disturbance and uncertainty of parameters of the islanded microgrid compromise the performance of virtual inertia control and may cause system frequency instability. Therefore, the virtual inertia control structure, a complementary controller is needed that can weaken the effect of disturbance on the microgrid as much as possible and be resistant to the uncertainty of parameters of the microgrid. In this paper, a robust control method is used in a virtual inertia control structure that uses system output feedback. The proposed method is expressed based on linear matrix inequality and is proved based on the Lyapunov criterion. Among the advantages of the proposed method is the attenuation of disturbance, resistance to the uncertainty of parameters of the microgrid, and increasing the degree of freedom to control the system in this method. The results of the proposed method to improve the performance of virtual inertia control in several different scenarios by considering the uncertainty of parameters of the two-zone microgrid and disturbances on the microgrid are compared with several methods and the effectiveness of the proposed method in terms of improving frequency stability is shown.

 

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The issue of frequency control is very important in the power system. The presence of wind turbine in the power system makes frequency control challenging. In order to improve the frequency control of the power system in the presence of wind turbine, in this paper, a new control method is designed. In this method, the coordinated control of load-frequency control (LFC) system and superconducting magnetic energy storage (SMES) has been discussed using PD-FOPID cascade controller. The PD member in this type of controller responds to the frequency changes of the power system faster and also the FOPID member has a favorable performance against the uncertainty of the system parameters and disturbances. In this paper, the problem of owl search algorithm is solved. Considering that the owl search algorithm may get stuck in the local optimum. In this paper, solutions are presented to solve this problem of the owl search algorithm, which is called the developed owl search algorithm, and in order to improve the performance of the PD-FOPID controller, the developed owl search algorithm is used to optimally adjust its parameters. . The proposed control method with several methods including: Load frequency control (LFC) and superconducting magnetic energy storage (SMES) based on the robust controller, LFC and SMES based on the MSA-PID controller, LFC based on the MSA-PID controller with SMES and LFC based on the MSA-PID controller without SMES has been compared in four scenarios and the results show the superiority of the proposed method over the other mentioned methods. Is. The proposed method is resistant to load disturbances, disturbances caused by wind turbines, and uncertainty related to system parameters.