نشریه مهندسی برق و مهندسی کامپیوتر ایران
سال بیست و چهارم شماره 4 (پیاپی 82، زمستان 1402)

Today, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper introduces a new multi-objective optimization model, which in the first objective, minimizes the total operation cost of the microgrid, and in the second objective, improves the reliability index by reducing the amount of energy not supplied. Due to these two objectives, a multi-objective evolutionary seagull optimization algorithm is used to find the optimal global solutions. In this regard, hybrid electric vehicles and demand response programs are used to smooth out distribution nodal prices and reduce CO2 emissions. The 69-bus distribution network has been used to evaluate the efficiency of the proposed method.

In the present study, drug treatment of HIV infection is investigated using a Data-Driven Sliding Mode Control (DDSMC) combined with a Projection Recurrent Neural Network (PRNN). The major objective is to establish the control law that eliminates the need for HIV infection mathematical formulae and ensures that the physical limits of the actuator are reached. This is accomplished by creating the concepts of model-free adaptive control, in which the relation between input and output is described using local dynamic linearized models based on quasi-partial derivatives. To determine the DDSMC law, a performance index is first defined based on the fulfillment of a discrete-time exponential reaching condition. By turning this index into a quadratic programming problem, the dynamics of the PRNN are extracted based on projection theory. The closed-loop system is explicitly determined using the optimizer output equation and the closed-loop stability analysis is evaluated using the singular value approach. The simulation results reveal that the proposed algorithm has robust performance in conducting the state variables of HIV infection to the healthy equilibrium point in the face of model uncertainty and external disturbances when compared to one of the newest control techniques.

In the drive control of permanent magnet synchronous motors (PMSMs), the control system must be designed to work in different conditions and against of changes in motor parameters and unknown disturbances. In order to enhance the drive performance of PMSM motor, the model-predictive control independent of current and speed model (MFPCSC) is proposed in this article. This method only uses the input and output of the system and does not involve the motor parameters in the drive control, and it is robust to the changes of the motor parameters. The conventional model-independent predictive control method requires setting several control parameters. To improve the performance of the drive system of this motor and make it robust to changes in parameters and disturbances, the proposed MFPCSC method is designed based on the nonlinear disturbance observer (NDO). This observer can estimate system disturbances with more accuracy and stability, and the amount of calculations is small. The simulation and practical test results of the proposed MFPCSC method combined with the NDO show that the proposed control method has high robustness to parameter changes, favorable transient response, small output ripple, and improved transient characteristics, and can accurately and stably estimate system disturbances.

In recent years, Phased-Multiple-Input, Multiple-Output radars (PMRs) have attracted great interest. PMR can combine the advantages of both MIMO radar and phased array radar. Here, PMR transmits orthogonal signals from all subarrays to provide both waveform frequency diversity and high coherent processing gain. In this paper dealt with detector design in the presence of heterogeneous clutter based on the unknown scattering coefficients for PMR. Then, detection probability and false-alarm probability are computed based on the derived optimum detector. At the end, the power allocation problem is investigated analytically. The numerical simulations show that obtained optimal detector is joint spatial-temporal filter, which, the clutters are effectively weakened in PMR. Furthermore, simulation results illustrate that proposed power allocation algorithm improve detection performance of PMR in comparison with PR and equal power PMR.

A step-down converter based on buck and buck-boost converters with a loss reduction technique is proposed in this paper. Utilizing non-electrolytic capacitors in the implementation of the proposed converter has resulted in an increase in circuit life and a reduction in weight and volume. This paper compares the proposed converter to other buck converters. To increase the output efficiency of the converter in comparison to other structures, a new method based on determining the working duty-cycles has been employed to reduce the losses of the converter, resulting in an increase in the converter's output efficiency. In order to demonstrate the differences in efficiency between the proposed method and the conventional method, the efficiency of the converter has been calculated using real-world conditions and the output loss results have been compared. In addition, the proposed converter has a common ground with the input source and has a suitable reduction gain. Finally, this converter has been implemented as a PCB and tested with 100 watts of output power.

In this research, a new intelligent control design using Teaching-Learning-Based-Optimization (TLBO) algorithm to optimize PID controller coefficients is presented. This method has been applied on the twin rotor system which has been constructed in Control Engineering Lab at Arak University. The purpose of controlling the twin rotor system is to stabilize the system in the zero degree horizontal position. After modeling and obtaining the state space description, the PID controller is designed and implemented on the system. In this study, by reviewing meta-heuristic optimization methods such as particle swarm optimization algorithm, genetic algorithm, colonial competition algorithm and differential evolution algorithm, the optimization results were compared with the above-mentioned meta-heuristic methods. With the optimization performed by the teaching and learning algorithm, the stability and faster performance of the system compared to other meta-heuristic methods can be seen. The merit of TLBO is that it does not have control parameters, which makes it convenient to employ. The simulation results of the PID controller for a twin rotor system show the effectiveness of the proposed methods.

This paper presents a new method for Out-of-Step detection in synchronous generators based on Decision Tree theory. For distinguishing between power swing and out-of-step conditions a series of input features are introduced and used for decision tree training. For generating input training samples, a series of measurements are taken under various faults including operational and topological disturbances. The proposed method is simulated over 10 machines 39-bus IEEE test system and the simulation results are prepared as input-output pairs for decision tree induction and deduction. The merit of proposed out-of-step protection scheme lies in adaptivity and robustness of input features under different input scenarios

Due to the increase of processing data, processing systems should be designed to occupy less space. The enlargement of the processing systems has caused the growth of the data size, on the other hand, the problems of miniaturization of metal-oxide semiconductor field effect transistor MOSFET have faced many problems for the designers of processing circuits, the idea of replacing binary processing circuits with multi-valued level processing circuits. It reduces connections between systems and reduces space consumption. Because the implementation of multi-level processing circuits with MOSFET technology is very complicated and problematic, a suitable alternative for MOSFET is carbon nanotube field effect transistor (CNTFET) technology, which has many advantages such as the possibility of making transistors It has a different threshold voltage, which reduces design challenges in the implementation of multi-level systems. In this article, the structure of the transistor level of single-digit quaternary and multi-digit comparators is presented. Transistor level circuits are presented along with circuit techniques. The simulation results also show that the amount of propagation delay and power consumption in the single-digit quaternary comparator is 17.3 picoseconds and 4.59 microwatts, respectively, and the PDP index of this comparator is 79.2 aJ. All simulation results of proposed comparators in this article have been obtained using carbon nanotube field effect transistors and 32 nm technology in HSPICE software.