Periodica Polytechnica Electrical Engineering and Computer Science

Optimizing Multiple Beam Patterns for 5G mmWave Phased Array Applications

2023-04-20T06:55:09+00:00

In this paper, a new technique for shaping multiple beam patterns antenna arrays for 5G and beyond wireless massive MIMO communication systems is introduced. The technique aims to concentrate the radio energy in specific coverage areas with a desired shape by optimizing the excitation amplitudes and phases of the array elements. To assess the proposed technique, both genetic algorithm and particle swarm optimization are utilized to optimize the excitation amplitudes and phases of the array elements such that the required number of the beams, their shapes, their directions, their power magnitudes, and the desired sidelobe pattern can be achieved. Simulation results fully confirm the effectiveness of the proposed technique in generating optimized shaped patterns that can be suitably used for distributing the radiation powers over the coverage areas in the mobile communication base stations.

A Hybrid Spatial Adaptive Modulation and Frequency Stochastic Approach for MU-MIMO-OFDM Systems in the Context of Underlay Cognitive Radios

2023-04-06T08:01:47+00:00

In this paper, low complexity rate and power optimization schemes operating in the spatial and frequency domains are proposed in a cognitive radio (CR) setting involving multi-user multiple-input-multiple-output-orthogonal frequency division multiplexing (MU-MIMO-OFDM). Under the assumption of a perfect secondary channel state information (CSI) at the receiver, the presented architectures encompass two main stages. In the first one, spatial power waterfilling-like method is performed per each MIMO subchannel pertaining to each subcarrier of each secondary user (SU). The resulting allocated power per each eigen-channel is considered as the power budget in the second stage. In this latter, stochastic algorithm-based approach wherein the transmit parameters per each subcarrier of each SU are adapted such that to maximize the achievable sum-rate capacity of the SUs. Three different schemes are introduced in this work. First, the derivation of the continuous rate MU-MIMO-OFDM-CR version, referred to as C-MU-MIMO-OFDM-CR is presented. Obviously, this proposition is theoretical and is taken as a benchmark for the two remaining counterparts. The second proposition we called discrete-rate MU-MIMO-OFDM-CR, and briefly designated as D-MU-MIMO-OFDM-CR which is to round the provided allocated rate. Finally, the third modified solution, denoted as P-D-MU-MIMO-OFDM-CR proceeds in a similar way as the D-MU-MIMO-OFDM-CR alternative, but superimposes the non/over-used amount of power to the power budget in next iteration. The simulation results show that, compared to the discrete rate D-MU-MIMO-OFDM-CR solution, the P-D-MU-MIMO-OFDM-CR approach exhibits an approximate power gain of 1 dB when the SNR level is low, and of 5 dB at high SNR range.

Exploring the Use of Particle and Kalman Filters for Obstacle Detection in Mobile Robots

2023-04-04T05:53:05+00:00

The present study aims to explore the adaptation of estimation methodologies, specifically Particle filters and Kalman filters, for the purpose of determining the position and velocity vector of obstacles within the operational workspace of mobile robots. These algorithms are commonly employed in the motion planning tasks of mobile robots for the estimation of their own position. The proposed methodology utilizes LiDAR sensor data to estimate the position vectors and calculate the velocity vectors of obstacles. Additionally, an uncertainty parameter can be determined using the introduced perception method. The performance of the newly adapted algorithms is evaluated through comparison of the absolute error in position and velocity vector estimations.

Robust Aerodynamic Parameter Estimation of Unmanned Aircraft Based on Two-step Identification

2023-05-02T10:50:42+00:00

This paper presents the estimation of stability and control derivatives of an unmanned aircraft. The aerodynamics are described using regressors composed of velocity, angular rates, flow angles and control surface deflections. The flight data is generated from numerical simulation of postulated equations of motion describing the aerodynamics model. Least squares based on the equation error method is used to estimate the parameters representing the different force and moment aerodynamic coefficients. Statistical analysis is done on the estimates to determine the accuracy and adequacy of the estimates to describe the aerodynamic model. A dynamic simulation based on the identified aerodynamic model is used to improve the parameter estimates through regression of the errors between the flight data and the model response. The aircraft under consideration is a scaled Yak-54 fixed wing unmanned aerial vehicle.

A Collaborative Graph-based SLAM Framework Using a Computationally Effective Measurement Algebra

2023-01-31T09:57:54+00:00

Simultaneous localization and mapping (SLAM) is an essential task for autonomous rover navigation in an unknown environment, especially if no absolute location information is available. This paper presents a computationally lightweight framework to enable agents with limited processing power to carry out the SLAM cooperatively and without absolute onboard localization sensors in a 2D environment. The proposed solution is built on a graph-based map representation, where nodes (resp. edges) represent landmarks (resp. odometry-based relative measurements), a measurement algebra with embedded uncertainty, and a compact database format that could be stored on a server in a centralized manner. The operations required by the agents to insert a new landmark in the graph, update landmark positions and combine measurements as a loop is closed in the graph are detailed. The resulting framework was tested in a laboratory environment and on a public dataset with encouraging results; hence our method can be used for cost-effective indoor mobile agents with limited computational resources and onboard sensors to achieve a mapping while keeping track of the agent's position. The method can also be easily generalized for a 3D scenario.

A Solar PV Model Parameter Estimation Based on the Enhanced Self-Organization Maps

2023-05-26T07:32:25+00:00

Solar photovoltaic (PV) is a commonly utilized renewable energy source, with PV cells often being modeled as electric circuits. The identification of suitable circuit model parameters for PV cells is vital for performance evaluation, efficiency calculations, and the implementation of maximum power point tracking in solar PV systems. However, modeling the solar PV system is a nonlinear problem that requires an efficient algorithm. In this paper, we employ the enhanced self-organization maps (EASOM) to efficiently reduce the search space for parameter estimation in solar PV models. Our algorithm trains the SOM network on a subset of solutions, identifies the top solution's neural unit, generates a population of potential solutions, and selects the best candidate using a cost function, which represents the best PV model parameters obtained. The performance of EASOM is verified by extracting the parameters of the single diode (SDM) and double diode (DDM) models for the STM6-40/36 PV module. EASOM outperformed state-of-the-art algorithms with the lowest RMSE and MSE values of 8.3 mA and 6.87e-05 and achieved the lowest maximum error values of 27.37 mA and 20.52 mA, as well as low power error of 66.04 mW and 62.8 mW for SDM and DDM models.

Design for Integrated Planar Spiral Inductor for MEMS

2023-03-23T08:31:50+00:00

The main aim of this paper is to present the new design of an integrated planar spiral inductor with a new structure of an underpass to obtain a high inductance, high quality factor and minimum losses into winding and magnetic core. The performance of this structure dependent on the geometrical, electrical parameters and material properties. These parameters are calculated at 350 MHz and this is the high frequency used for MEMS applications. Furthermore, thermal analysis in inductor from finite difference method is described. The heat transfer model is based on heat conduction and heat convection. Moreover, the heat source is calculated by different losses. In addition, the simulation results from 3D finite element method using software also been presented in this paper. It is based on both the classical heat equation and certain condition limits. However, a new design of an underpass has been proposed where a via is fabricated with a circular layer. The input and output of the spiral are implanted in the same direction. In addition, the magnetic core is the solution to decrease the temperature. Finally, the results of the finite difference method are compared with simulation results from finite element method. The good agreement between the results is obtained. The proposed via and a core magnetic are responsible for enhancement the thermal behavior in integrated inductor. The result shows that the temperature of the air core inductor and magnetic core inductor could be 53 °C and 33 °C, respectively.

Flying Capacitor Voltage Balancing Control Strategy Based on Logic-equations in Five Level ANPC Inverter

2023-04-04T06:03:29+00:00

This paper proposes a novel voltage balancing control approach for the flying capacitors in a five-level Active-Neutral-Point-Clamped inverter (ANPC). The projected method is based on the control signal of the flying capacitor (FC) voltage. A Staircase reference voltage-based Phase-Shifted PWM (PS-PWM) technique is used to generate the different levels and simple logic-equations. The proposed control can regulate the voltage of the FC at the requested reference value and generate the required five-level output voltage with fast dynamics. It requires fewer and simpler calculations and it has a fast execution time. The Simulations are performed using MATLAB and Simulink. The obtained results demonstrate the good performance of the FC voltage control and the high quality of the output voltages and current spectrum.

Comparative Study of Robust RSC Control of Doubly Fed Induction Generator Based Wind Turbine under Grid Frequency and Voltage Variations

2023-04-27T06:27:25+00:00

The configuration of a grid-connected doubly fed induction generator (DFIG) for wind energy generation systems consists of direct coupling of the generator stator windings with the grid and partial coupling of the rotor through power converters. This structure makes the system sensitive to the fault grid. Thus, robust control techniques are required to deal with the undesirable transient sequences in the network. In this paper, two robust controllers have integrated to regulate the stator active and reactive power of DFIG based wind turbine. Then, they have been tested and compared to verify their performances when abnormal grid networks have occurred. Firstly, we used high order sliding mode (HOSM) based Super Twisting, which keeps the same conventional sliding mode performances, such as fast dynamic response and redundancy to the extern disturbances, with a simple design and chattering reduction. Secondly, we implement the backstepping control approach which is known for its robustness in transient sequences. A number of simulations have carried out to evaluate the ride-through performance of both control strategies in case of low grid voltage dips and grid frequency variations.

Sliding Input Output Control of Squirrel Cage Motor Based NPC Five Level Inverter

2023-03-23T08:24:04+00:00

Speed squirrel cage motor control is an area of research that has been in evidence for some time now. In this paper, a nonlinear controller is presented for the squirrel cage motor drives, based on a combination between input-output feedback linearization control (IOLC) technique and sliding mode control (SMC) to create a new control which is sliding input-output linearization (SIOLC) control of squirrel cage motors which associates by an NPC five levels inverter PWM technical used for the variation of its speed, where the sliding mode control it used for controlling the speed of squirrel cage motor and the input-output linearization control applied for two input witch are flux and current. To test robustness and performance of sliding input-output linearization control (SIOLC) we created a variation of internal parameters of the motor. The simulation results show robustness the sliding input-output linearization control of squirrel cage motor responses.