Radiation pattern reconfigurable fm antenna

In this work, a radiation pattern reconfigurable antenna design using compact printed spiral monopoles that operates at 102 MHz is reported. The proposed antenna changes its radiation behaviour that responds towards a desired direction with the use of RF switches. The antenna is printed on a 76.6mm × 50mm PCB layer providing more than 20MHz bandwidth at -10 dB threshold and is easily fabricated with low manufacturing cost. The antenna was also simulated on 500mm × 500mm ground plane that represents the roof top of a vehicl

Nonlinear finite element analysis of reinforced concrete beams strengthened with textile fine grained mortar

Nowadays, there was an increasing need of repairing and upgrading the reinforced concrete (RC) structure due to the deterioration of the structure. The fibre reinforced polymer (FRP) was commonly used for structural retrofitting purposes. However, owing to the debonding of the FRP from the concrete substrate and high cost of epoxy, it was gradually replaced with textile fine grained mortar (TFGM) nowadays. The TFGM system has been widely used in the construction field nowadays to repair the structure. Our study focus on the strain performances of the concrete surface, steel reinforcement and the textile itself. There were many proven experimental results showing that the TFGM was more effective than the other strengthening method such as FRP plate method. The experimental work done by previous researcher on investigation of strain performances of the concrete surface, steel reinforcement and the textile itself which consists of eleven (11) RC beams with dimension 150 x 200 x 2500 mm. The RC beams were strengthened with FGM and TFGM with 4 layers. The investigation continued with the finite element (FE) strain performance analysis with using Advanced Tool for Engineering Nonlinear Analysis (ATENA) software. The strain of the concrete surface, steel reinforcement and the textile were measured at a mid-point of RC beam. Then, the results of the finite element analysis software ATENA compared against the experimental results. The strain performances of the concrete and steel reinforcement improved noticeably when the number of layers of textile reinforcement used increased

The effect of data preprocessing on the performance of artificial neural networks techniques for classification problems

The artificial neural network (ANN) has recently been applied in many areas, such as medical, biology, financial, economy, engineering and so on. It is known as an excellent classifier of nonlinear input and output numerical data. Improving training efficiency of ANN based algorithm is an active area of research and numerous papers have been reviewed in the literature. The performance of Multi-layer Perceptron (MLP) trained with back-propagation artificial neural network (BP-ANN) method is highly influenced by the size of the data-sets and the data-preprocessing techniques used. This work analyzes the advantages of using pre-processing datasets using different techniques in order to improve the ANN convergence. Specifically Min-Max, Z-Score and Decimal Scaling Normalization preprocessing techniques were evaluated. The simulation results showed that the computational efficiency of ANN training process is highly enhanced when coupled with different preprocessing techniques

Voltage profile Improvement Using Static Synchronous Compensator STATCOM

Static synchronous compensator (STATCOM) is a regulating device used in AC transmission systems as a source or a sink of reactive power. The most widely utilization of the STATCOM is in enhancing the voltage stability of the transmission line. A voltage regulator is a FACTs device used to adjust the voltage disturbance by injecting a controllable voltage into the system. This paper implement Nruro-Fuzzy controller to control the STATCOM to improve the voltage profile of the power network. The controller has been simulated for some kinds of disturbances and the results show improvements in voltage profile of the system. The performance of STATCOM with its controller was very close within 98% of the nominal value of the busbar voltage

Mechanical and shrinkage properties of hybrid steel and polypropylene fibre reinforced concrete composite

An experimental study had been carried out to investigate the mechanical properties, expansion and shrinkage of fibre reinforced concrete composite (FRC). However, instead of using single type fibre of either steel (SF) or polypropylene (PPF), this study also combined the two types in one mix.The mechanical properties investigated in this study include compressive strength, splitting tensile strength and flexural strength. Three different FRC mix proportions and one normal concrete (control) were casted which includes (a) 75% SF, (b) 75% SF + 25% PPF, (c) 25% PPF, and (d) 0% fibre for control (PC). Meanwhile, the volume fraction, Vf for the FRC was fixed at 1.5% and the concrete strength was designed to achieve grade C60 at 28 days. The results show that the use of fibres in concrete decreased the workability of concrete. In addition, concrete mix with both SF and PPF produced the highest splitting tensile and flexural strengths by an increase of 75.9% and 86.5%, respectively as compared with the control. Furthermore, expansion and shrinkage of FRC was found to be less than the control. It can be concluded that the combined SF and PPF in concrete gives the most appropriate combination as regards to the highest flexural and splitting tensile strengths, and also reduced the shrinkage strain

Optimized Hidden Markov Model based on Constrained Particle Swarm Optimization

International audienceAs one of Bayesian analysis tools, Hidden Markov Model (HMM) has been used to in extensive applications. Most HMMs are solved by Baum-Welch algorithm (BWHMM) to predict the model parameters, which is difficult to find global optimal solutions. This paper proposes an optimized Hidden Markov Model with Particle Swarm Optimization (PSO) algorithm and so is called PSOHMM. In order to overcome the statistical constraints in HMM, the paper develops re-normalization and re-mapping mechanisms to ensure the constraints in HMM. The experiments have shown that PSOHMM can search better solution than BWHMM, and has faster convergence speed

Active and reactive power flow management in parallel transmission lines using static series compensation (SSC) with energy storage

The power flow controlled in the electric power network is one of the main factors that affected the modern power systems development. The Static Series Compensatior with storage energy, is a FACTS powerful device that can control the active power flow control of multiple transmission lines branches. In this paper, a simulation model of power control using static series compensator with parallel transmission lines is presented.  The control system using adaptive neuro-fuzzy logic is proposed. The results show the ability of static series compensator with storage energy to control the flow of powers components "active and reactive power" in the controlled line and thus the overall power regulated between lines.

Performance investigation of stand-alone induction generator based on STATCOM for wind power application

Self-Excited induction generators (SEIG) display a low voltage and frequency regulation due to variable applied load and input rotation speed. Current work presents a simulation and performance analysis of a three-phase wind-driven, SEIG connect to a three-phase load. In addition, an investigation of the dynamic operation of the induction generator from starting steady state until no-load operation. It is assumed that the input mechanical power is constant where the rotor of the SEIG rotates at a constant speed. The value of the excitation capacitance which is necessary to the operation of the induction generator also computed to ensure a smooth and self-excitation starting. The output voltage of the generator is adjusted by varying the reactive power injected by STATCOM. A 3-phase IGBT voltage source inverter with a fuel cell input supply is connected as STATCOM which is used to compensate for the reduction in the supply voltage and its frequency due to variation occurred in the applied loads. This work includes introducing a neuro-fuzzyy logic controller to enhance the performance of the SEIG by regulation the generated voltage and frequency The dynamic model of SEIG with STATCOM and loads are implemented using MATLAB/SIMULIN

Optimal tuning of proportional integral controller for fixed-speed wind turbine using grey wolf optimizer

The need for tuning the PI controller is to improve its performance metrics such as rise time, settling time and overshoot. This paper proposed the Grey Wolf Optimizer (GWO) tuning method of a Proportional Integral (PI) controller for fixed speed Wind Turbine. The objective is to overcome the limitations in using the PSO and GA tuning methods for tuning the PI controller, such as quick convergence occurring too soon into a local optimum, and the controller step input response. The GWO, the Particle Swarm Optimization (PSO), and the Genetic Algorithm (GA) tuning methods were implemented in the Matlab 2016b to search the optimal gains of the Proportional and Integral controller through minimization of the objective function. A comparison was made between the results obtained from the GWO tuning method against PSO and GA tuning techniques. The GWO computed the smallest value of the objective function minimized. It exhibited faster convergence and better time response specification compared to other methods. These and more performance indicators show the superiority of the GWO tuning method

Power System Stability Improvement via TCSC Controller Employing a Multi-objective Strength Pareto Evolutionary Algorithm Approach

This paper focuses on multi-objective designing of multi-machine Thyristor Controlled Series Compensator (TCSC) using Strength Pareto Evolutionary Algorithm (SPEA). The TCSC parameters designing problem is converted to an optimization problem with the multi-objective function including the desired damping factor and the desired damping ratio of the power system modes, which is solved by a SPEA algorithm. The effectiveness of the proposed controller validates on a multi-machine power system over a wide range of loading conditions. The results of the proposed controller (SPEATCSC) are compared with the Genetic Algorithm (GA) based tuned TCSC through some operating conditions to demonstrate its superior efficiency