نشریه مهندسی مخابرات جنوب
پیاپی 46 (زمستان 1401)

Immediate monitoring of the patient has always been very important. Achieving this knowledge, which can be integrated to monitor damaged tissue, is very important. In previous methods, the tissue was monitored using a sensor. In this article, not only is a tissue monitored using a sensor, but also the monitoring and evaluation of the effect of other tissues on tumor tissue is evaluated. The smart grid discussed in this article is designed to monitor the condition of a patient with a breast tumor. The structure of the smart grid, given the weight of the communication paths between the nodes and the ability of the nodes, shows us a strong network to assess the patient's condition. As the patient's condition changes, the nodes and weights of the communication pathways change, indicating that there is important information in the network and helping specialists to better assess the condition of the disease. Network monitoring is such that the evaluator node continuously evaluates the tumor node, by changing the status of the tumor node, the status of other nodes and communication paths between them changes, the result of changes in the network by the node The evaluator is evaluated. The simulation results show that this network has the necessary intelligence to assess the patient's condition in adverse conditions.

In this paper particle swarm optimasation algorithm (PSO) based sliding mode controller(SMC) introduced to control invrters of Uniefied power quality Controllers(UPQC) to control and improve the power quality in microgrids through controlling the output power of the distributed generation source. In the proposed control scheme, the standard sliding mode controller (SMC) is used as a robust nonlinear controller, with the addition of the particle swarm optimization (PSO) algorithm - to determine the optimal parameters of the SMC controller. Using PSO added extra advantages like reducing chattering problems and increasing accuracy and tracking capability to the commonly knowns SMC benefits. To confirm the accuracy of the proposed controller's performance, computer simulation is performed under different system load conditions in the MATLAB/Simulink software environment. The obtained results show the effectiveness of the proposed control compared to the standard sliding mode controller in reducing harmonics, reducing voltage imbalance and improving other power quality indicators.

In this paper, a robust dynamic slip mode controller for an electrical robot manipulator is presented. The control law calculates the motor voltage based on the voltage control strategy. Uncertainties are estimated using the Fourier series expansion and the cutting error is compensated. Fourier coefficients are adjusted based on stability analysis. Also in this paper is the design of a robust controller using a new adaptive Fourier series extension. Compared to previous related works based on the Fourier series expansion, the advantage of this paper is that it provides a matching law for the main frequency of the Fourier series expansion and thus eliminates the need for trial and error in its regulation. A case study of a Scara robot powered by DC magnet electric motors. The effect of uncertainty estimation based on the Fourier series expansion is studied instead of using the sign function. The proposed method is also compared with Legendre polynomials. The simulation results confirm the robust and satisfactory performance of the proposed controller.