Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
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Aircraft Pitch Control via Filtered Proportional-Integral-Derivative Controller Design Using Sinh Cosh Optimizer
Get PDFAn innovative approach to controlling aircraft pitch is shown in this research. This approach is accomplished by adopting a proportional-integral-derivative with filter (PID-F) mechanism. A novel metaheuristic approach that we propose is called the sinh cosh optimizer (SCHO), and it is intended to further optimize the settings of the PID-F controller that is used in the aircraft pitch control (APC) configuration. An in-depth comparison and contrast of the recommended method is carried out, and statistical and time domain assessments are utilized in order to ascertain the success of the method. When it comes to managing the APC system, the SCHO-based PID-F controller delivers superior performance compared to other modern and efficient PID controllers (salp swarm based PID, Harris hawks optimization based PID, grasshopper algorithm based PID, atom search optimization based PID, sine cosine algorithm based PID, and Henry gas solubility optimization based PID) that have been published in the literature. When compared to alternative approaches of regulating the APC system, the findings demonstrate that the way that was presented is among the most successful as better statistical (minimum of 0.0033, maximum of 0.0034, average of 0.0034 and standard deviation of 5.1151E−05) and transient response (overshoot of 0%, rise time of 0.0141 s, settling time of 0.0230 s, peak time of 0.0333 s and steady-state error of 0 %) values have been achieved
Using Active Filter Controlled by Imperialist Competitive Algorithm ICA for Harmonic Mitigation in Grid-Connected PV Systems
Get PDFSolar energy has been gaining momentum recently, with a focus on maximizing its investment potential due to its reputation as the most sustainable and efficient energy source. This shift towards solar power could potentially reduce the reliance on oil-based fuels in the future. As a result of the integration of photovoltaic (PV) energy sources into the grid, the reliability of power distribution and maintaining its quality in these systems has become increasingly important. The presence of non-linear loads in these grids causes distortion of both voltage and current waves on the grid side, so it is necessary to implement effective reduction techniques to reduce the distortions in these waves. The research contribution is TO introduce the integration of an active filter on the dc side of grid-connected PV systems, along with a control circuit for the filter switches. The control switches were operated using a Sinusoidal Pulse Width Modulation (SPWM) control scheme, while the controller parameters were tuned using the Imperialist Competitive Algorithm (ICA). The proposed system was simulated in the MATLAB/Simulink environment with variations in solar radiation and temperature. The simulation results demonstrated a reduction in the total harmonic distortion factor (THD) for voltage and current waveforms on the grid side, which are within the permissible limits. This confirms the effectiveness of the proposed filter and the efficiency of the control strategy and algorithm for parameter adjustment
Simulation and Arduino Hardware Implementation of ACO, PSO, and FPA Optimization Algorithms for Speed Control of a DC Motor
Get PDFThis article proposes implementing and comparing the effectiveness of three optimization algorithms (ACO, PSO, and FPA) for tuning a proportional-integral-derivative (PID) controller on an Arduino Mega 2560 board. This relatively unexplored approach aims to evaluate these algorithms through practical experiments. The choice of PID control is due to its design simplicity and widespread industrial use. Similarly, the permanent magnet DC motor (PMDC) was selected because of its crucial role in various industrial sectors. Tuning PID parameters using optimization algorithms has garnered increasing interest due to its demonstrated efficiency. Several studies have validated the stability of ACO, PSO, and FPA algorithms, justifying their selection. In this article, simulation results showed that ACO, with a response time of 0.322s and an overshoot of 0.68%, was more effective than PSO, which had a response time of 0.768s and an overshoot of 13%. FPA had a response time of 0.347s, close to ACO, but a higher overshoot of 6%. In practice, several factors come into play, such as speed ripples caused by the speed sensor, and machine saturation, which must be considered to ensure practical implementation. After adjusting the PID parameters and integrating a low-pass filter in the feedback loop, ACO, with a response time of 0.596s and an overshoot of 1.68%, was very close to FPA, which had a response time of 0.644s and an overshoot of 0.81%. This comparison highlighted the advantages of the FPA algorithm, which is simple to use, requires fewer parameters to adjust, and takes less time than ACO. This study suggests the potential for implementing a hybrid FPA-ACO algorithm, leveraging the strengths of both algorithms
Seasonal Electrical Load Forecasting Using Machine Learning Techniques and Meteorological Variables
Get PDFAccurate forecasting of seasonal power consumption is crucial for effective grid management, especially with increasing energy demand and renewable energy integration. Weather patterns significantly influence energy usage, making load prediction a challenging task. This study employs machine learning algorithms, including Random Forest (RF), Artificial Neural Networks (ANN), and Decision Tree (DT) models, to forecast electricity consumption using meteorological variables such as solar irradiance, humidity, and ambient temperature. The impact of weather elements on load prediction accuracy across different seasons is explored using seasonal forecasting techniques. The results demonstrate the superior performance of ANN and RF models in forecasting summer and winter loads compared to the rainy season. This discrepancy is attributed to the abundance of data for the summer and winter seasons, and the ability of the models to capture complex patterns within the data for these particular seasons. The study highlights the potential of machine learning techniques, particularly ANN and RF, in conjunction with meteorological data analysis, for enhancing the accuracy of seasonal electrical load forecasting. This can contribute to more effective power grid management and support the transition towards a more sustainable energy landscape. The findings underscore the importance of data quality, quantity, and appropriate model selection for different seasonal conditions
Artistic negotiation, religious and cultural values: an Islamic dance aesthetic in the perspective of Muhammadiyah tarjih decision
Get PDFThis research aims to show the efforts to build Islamic dance aesthetics through artistic negotiations of dance works with art norms in tarjih decisions and cultural values in Muhammadiyah dance performances. The results of this intersection gave rise to a new value in Islamic dance art that speaks not only to divine oneness as an Islamic principle but also to Indonesian cultural factors in its aesthetic performance. Data was collected for 6 months using interview techniques and audio-visual data analysis of 3 dance works and artists in Muhammadiyah. Interviews with the general chairman policymakers in the field of tarjih and art institutions in Muhammadiyah also support analysis related to religious values in artworks. The analysis shows that the dance works performed result from the artist's religious interpretation of the norms in the Muhammadiyah tarjih decision. There is a negotiation between artists and Muhammadiyah administrators that takes place continuously in Muhammadiyah dance performances. Artists conduct artistic negotiations in the dance works performed to harmonize with Islamic values without eliminating cultural elements. The adaptation process is more on content (variety of dance movements), performance (costumes and dance supporting elements), and ideas (philosophical values within the cultural framework). The theoretical contribution of this research is to understand the relationship between art, culture, and religion, especially in the context of Islamic performing arts. This research also makes an important contribution to building the theory of Islamic dance aesthetics, which talks about artistic beauty and religious meaning in every element of performing arts and shows it through the perspective of dance diversity in Indonesia
Design of A Backstepping Control and Synergetic Control for An Interconnected Twin-Tanks System: A Comparative Study
Get PDFThis paper presents a comparative performance examination between designing backstepping control (BSC) and synergetic control (SC) for an interconnected twin-tanks system. The controller is used to maintain the liquid level in the tank at the desired value by manipulating the input flow rate. The nonlinear dynamics of the twin-tanks system is established first. Then, based on the nonlinear dynamics of the system, the control law of the BSC and the SC are developed. The two controllers cooperate with the grasshopper optimization algorithm (GOA) for further improvement of the control design performance by tuning the design parameters of each controller. GOA has strong searchability for optimal solution and it has been successfully used to solve several optimization problems in numerous ï¬elds. Finally, the performance and the signiï¬cance of each controlled system for two case studies (normal operation and under external disturbance) are examined based on MATLAB software. The simulation data shows that the BSC gives better performance than the SC
Analyzing event relationships in Andersen's Fairy Tales with BERT and Graph Convolutional Network (GCN)
Get PDFThis study explores the narrative structures of Hans Christian Andersen's fairy tales by analyzing event relationships using a combination of BERT (Bidirectional Encoder Representations from Transformers) and Graph Convolutional Networks (GCN). The research begins with the extraction of key events from the tales using BERT, leveraging its advanced contextual understanding to accurately identify and classify events. These events are then modeled as nodes in a graph, with their relationships represented as edges, using GCNs to capture complex interactions and dependencies. The resulting event relationship graph provides a comprehensive visualization of the narrative structure, revealing causal chains, thematic connections, and non-linear relationships. Quantitative metrics, including event extraction accuracy (92.5%), relationship precision (89.3%), and F1 score (90.8%), demonstrate the effectiveness of the proposed methodology. The analysis uncovers recurring patterns in Andersen's storytelling, such as linear event progressions, thematic contrasts, and intricate character interactions. These findings not only enhance our understanding of Andersen's narrative techniques but also showcase the potential of combining BERT and GCN for literary analysis. This research bridges the gap between computational linguistics and literary studies, offering a data-driven approach to narrative analysis. The methodology developed here can be extended to other genres and domains, paving the way for further interdisciplinary research. By integrating state-of-the-art NLP models with graph-based machine learning techniques, this study advances our ability to analyze and interpret complex textual data, providing new insights into the art of storytellin
Sumatran batik motif design and documentation using turtle graphics algorithm based on local wisdom
Get PDFUsing the Turtle Graphic algorithm to digitize and develop Sumatra batik motifs is an innovative step in preserving local wisdom. This algorithm, which was originally used in graphics programming to educate children about computer concepts, is now being utilized to design and reproduce intricate and detailed batik motifs. The problem is that most existing batik motifs have not been digitally stored. Therefore, the purpose of the research here is to digitize Sumatra batik motifs using the Turtle Graphics algorithm. Turtle graphics utilizes command-based programming principles to draw geometric shapes. As an icon for North Sumatra Province, the basic motif of the existing water tower batik is the focus of this pattern accuracy. It is documented using a Python program that uses the turtle graphics algorithm, and a new Sumatran batik motif design is created from this basic motif. The benefits of research results with this approach are that designers can digitally modify and reproduce traditional batik motifs. This algorithm allows the drawing of patterns with high accuracy, making creating consistent and precise motifs easier. This digitization process also helps document and preserve batik motifs. The use of this technology not only speeds up the design process but also provides wider access to the younger generation and the international community to appreciate and learn about Sumatra batik. By integrating modern technology and local wisdom, the digitization of rare batik motifs has the potential to strengthen cultural identity and increase the economic value of traditional batik products. The specific steps in the motif digitization or pattern-making process are as follows: determine the motif to be digitized, select the starting point of the moving turtle, determine the turtle's direction of motion in relation to the curve to be formed, execute the program, and if the turtle curve does not move in the desired direction, change the program and execute again until the turtle motion curve matches the desired curve. This process is repeated multiple times
Sustainable urban development: a case study on green infrastructure implementation in Kota City India
Get PDFKota City is known as an educational city with increasing urbanization, requiring a sustainable development approach to address environmental and social challenges. One of the solutions implemented is green infrastructure, which integrates natural elements to improve ecological quality, reduce environmental pressure, and improve people's welfare. This study aims to evaluate the effectiveness of green infrastructure in supporting sustainable development in Kota City. The approaches studied include rainwater management, renewable energy (solar, wind, nuclear, hydro), sustainable transportation, and red light-free zone policies to reduce energy consumption and pollution. The study results show that implementing green infrastructure significantly lowers urban temperatures, improves flood management, improves air quality, and improves energy efficiency. These approaches can help for sustainable urban development. This research provides benefits in the form of a greener, more efficient, and sustainable urban development model. With this approach, Kota city can be an example for other cities in creating a healthier, environmentally friendly environment and improving the economic and social welfare of the community
Exploring Indonesia government outbreak response: Misinformation of public officials in handling of Covid-19 Pandemic
Get PDFThe Covid-19 outbreak started in March 2020, and the Indonesian government has taken a long time to respond to it. With different ambiguous statements, public leaders contributed to the disruption of knowledge concerning the Covid-19 pandemic. Therefore, the study aims to investigate the communication strategy of Indonesia’s government in response to the early Covid-19 pandemic in March 2020. This study uses a qualitative method that analyzes news text from online media. The data collection technique in this research is a literature study. The source of this research data comes from statements by four Indonesian ministers regarding the Covid-19 outbreak from online media. The goal of this study is to understand the narrative in online media concerning Indonesian public officials' response to COVID-19 by analyzing the word frequency using NVIVO 12 Plus software. Findings from this study indicate that numerous issues with the utilization and dissemination of information about the COVID-19 pandemic demonstrate a lack of maturity and caution on the part of the government and media. Indonesia’s government could not provide excellent and precise information that followed the community's expectations regarding the pandemic. Indonesian public officials contributed to misinformation regarding the Covid-19 epidemic when dealing with the pandemic by providing ambiguous, incorrect, and misleading information