Results in Control and Optimization最新文献

{"title":"Droop control in grid-forming converters using a fractional-order PI controller: A power system transient analysis","authors":"Luis L. Chiza ,&nbsp;Diego Benítez ,&nbsp;Rommel Aguilar ,&nbsp;Oscar Camacho","doi":"10.1016/j.rico.2025.100517","DOIUrl":"10.1016/j.rico.2025.100517","url":null,"abstract":"<div><div>The integration of renewable energy sources in modern power grids introduces challenges in ensuring stable and efficient operation, especially during transient conditions and disturbances. One of the primary issues is the inadequate transient response of conventional droop control strategies in grid-forming (GFM) converters, which can impair system stability and performance under unbalanced load conditions. This article addresses these issues by introducing a fractional-order PI (FOPI) control strategy for droop control of GFM converters, aimed at improving the transient response and enhancing the overall stability of the system. The FOPI controller’s design allows for more flexible tuning of dynamic behaviors compared to traditional integer-order controllers, making it particularly effective for bolstering stability and fault tolerance. To optimize the parameters of the FOPI controller, continuous Monte Carlo simulation is used, focusing on performance under unbalanced load disturbances. The controller’s effectiveness is assessed using the Integral of Squared Error (ISE) and Integral of Squared Control Output (ISCO) metrics to balance accuracy and control effort. The simulation results under two fault scenarios demonstrate that the FOPI controllers significantly enhance the transient response and fault tolerance. In case 1, replacing the PI controllers with the FOPI controllers reduces error by 65% and improves energy efficiency by 16%. In case 2, FOPI controllers achieve an error reduction of 83% and an improvement in energy efficiency 15%. These findings highlight the effectiveness of FOPI controllers in improving control accuracy and efficiency in fault conditions.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100517"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient task scheduling and computational offloading optimization with federated learning and blockchain in mobile cloud computing","authors":"Matheen Fathima G,&nbsp;Shakkeera L","doi":"10.1016/j.rico.2025.100524","DOIUrl":"10.1016/j.rico.2025.100524","url":null,"abstract":"<div><div>Smartphones and other mobile device users are becoming increasingly susceptible to malicious applications or apps that compromise user privacy. Malicious applications are more invasive than required because they require less authorization to operate them. The Android platform is more vulnerable to attacks since it is open-source, allows third-party app stores and it has extensive app screening. Thus the usage of mobile cloud applications has also expanded due to android platform. The mobile apps are useful for e-transportation, augmented reality, 2D and 3D games, e-health care and education. Consequently, maintaining MCC security and optimization of resources according to the task becomes significant task. Though recent research has been focused in the area of task scheduling, supporting multiple objectives still becomes a significant issue due to the Non-deterministic Polynomial (NP) hard problem. In this paper, Federated Learning with Blockchain Technology (FLBCT) is introduced for Microservice-based Mobile Cloud Computing Applications (MSCMCC). Mobile app permissions dataset has to be offloaded to a mobile cloud and protected using FL and BCT. FL permit mobile users to train models without sending raw data to third-party servers. FL is also used to trains the data across various decentralized devices holding of samples without exchanging them. BCT is introduced for enhancing data traceability, trust, security and transparency among participating companies. Resource matching, task sequencing, and task scheduling are major steps of Optimization Task Scheduling based Computational Offloading (OTSCO) framework. OTSCO framework increases application efficiency and gives the successful resource constraints to increase application-based efficiency, tasks are executed under deadline, and minimize application cost. The proposed system has a lower overhead of 20.14%, lesser boot time of 20.47 ms, lesser CPU usage of 0.45%, failure task ratio of the suggested system is 2.52%. It shows that the proposed system is easily applicable to Task Scheduling, and gives more security on MCC.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100524"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On generation of Julia sets, Mandelbrot sets and biomorphs via a modification of the viscosity approximation method","authors":"Rimsha Babar,&nbsp;Wutiphol Sintunavarat","doi":"10.1016/j.rico.2025.100516","DOIUrl":"10.1016/j.rico.2025.100516","url":null,"abstract":"<div><div>Iterative methodology has been demonstrated to be an achievement in the age of fractals. A novel method based on the viscosity approximation approach, one of the most popular iterative techniques for identifying non-linear operator fixed points, for visualizing Mandelbrot and Julia sets for a complex polynomial <span><math><mrow><mi>G</mi><mrow><mo>(</mo><mi>z</mi><mo>)</mo></mrow><mo>=</mo><msup><mrow><mi>z</mi></mrow><mrow><mi>m</mi></mrow></msup><mo>+</mo><mi>a</mi><mi>z</mi><mo>+</mo><mi>b</mi></mrow></math></span>, where <span><math><mi>z</mi></math></span> is a complex variable, <span><math><mrow><mi>m</mi><mo>∈</mo><mi>N</mi><mo>∖</mo><mrow><mo>{</mo><mn>1</mn><mo>}</mo></mrow></mrow></math></span> and <span><math><mrow><mi>a</mi><mo>,</mo><mspace></mspace><mi>b</mi><mo>∈</mo><mi>ℂ</mi></mrow></math></span> are parameters, is presented in this paper. Using the proposed approximation method, we establish a novel escape criterion for producing Julia and Mandelbrot sets. This method yields biomorphs for any complex function. Additionally, we visualize the sets using the escape time approach and the suggested iteration. Then, using graphical and numerical experiments, we explore how the shape of the resulting sets changes depending on the iteration parameters. The examples show that this transformation can be highly complex, and we can acquire a wide range of shapes.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100516"},"PeriodicalIF":0.0,"publicationDate":"2025-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measurement-based characterization of an RF Transmitter to offset the effects of nonlinearities","authors":"Fadia Noori Hummadi ,&nbsp;Ekhlas Kadhum Hamza ,&nbsp;Ali M.J. Zalzala ,&nbsp;Ahmad H. Sabry","doi":"10.1016/j.rico.2025.100521","DOIUrl":"10.1016/j.rico.2025.100521","url":null,"abstract":"<div><div>Power amplifier characterization is an important process that is used to design and optimize PA circuits, and to troubleshoot problems with existing PA circuits. Measured input and output signals are used to determine the key parameters of a PA. However, PA characterization can be challenging due to the nonlinearity of PAs and the high frequencies at which they are often operated. This paper presents a comprehensive characterization of a power amplifier (PA) using measurement-based techniques. The study focuses on comparing the performance of memoryless and polynomial memory models in accurately predicting the PA's behavior. Results demonstrate that the polynomial memory model consistently outperforms the memoryless model, particularly at lower bandwidths. Key findings include the significant impact of memory effects on the PA's nonlinearity and the moderate influence of bandwidth on model accuracy. The proposed methodology provides a valuable framework for characterizing PAs and optimizing their performance in various applications. The results obtained indicated that for the OFDM signals with varying bandwidths, the time-based error as a percentage RMS for the nonlinear memoryless model was approximately 6 %, which is roughly greater than the inaccuracy of the polynomial memory model by three times, which is approximately 2 %.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100521"},"PeriodicalIF":0.0,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenges and opportunities in the industrial usage controller synthesis tools: A review of LTL-based opensource tools for automated control design","authors":"Amar Banerjee,&nbsp;Venkatesh Choppella","doi":"10.1016/j.rico.2024.100511","DOIUrl":"10.1016/j.rico.2024.100511","url":null,"abstract":"<div><div>Controller synthesis is pivotal in automating control system design from formal specifications and enhancing industrial system verification and optimization processes. This paper critically evaluates LTL-based controller synthesis, highlighting significant gaps in tool support that hinder its widespread adoption in the industry. Despite substantial theoretical progress, an apparent disparity persists between academic research outcomes and the robust, practical tools demanded by industry. Through a comprehensive evaluation, this study reveals mismatches between industrial requirements and the capabilities of current open-source tools. The findings emphasize underexplored challenges and propose future research directions and strategies for practical integration. This work aims to bridge the gap by advocating for enhanced tool support, enabling solutions that align with industrial standards and fostering the broader application of controller synthesis across various sectors.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100511"},"PeriodicalIF":0.0,"publicationDate":"2025-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-linear PID control of AC current and DC voltage for a photovoltaic system operating on a microgrid","authors":"Pablo Proaño ,&nbsp;Marcelo Pozo ,&nbsp;Carlos Gallardo ,&nbsp;Oscar Camacho","doi":"10.1016/j.rico.2024.100514","DOIUrl":"10.1016/j.rico.2024.100514","url":null,"abstract":"<div><div>This study introduces a nonlinear control strategy to enhance the energy management of electrical power systems, addressing the inherent limitations of traditional linear PI controllers. The proposed approach incorporates a variable gain that dynamically adjusts based on the system error, amplifying the PI controller’s responsiveness without causing output saturation. By introducing quadratic error terms through the gain adjustment, the controller achieves nonlinear behavior. When the system error is significant, the gain increases to expedite correction; as the error approaches zero, the gain decreases, allowing the PI controller to maintain stability around the reference. This adaptive behavior eliminates the need for a derivative component, effectively circumventing challenges posed by electromagnetic noise and rapid system dynamics. A comparative analysis between the proposed nonlinear PI controller and a conventional PI controller is conducted within a photovoltaic microgrid framework. The results highlight the nonlinear controller’s superior performance in achieving robust and accurate control.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100514"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding issues and challenges posed by LDoS, FRC attacks on cloud environment","authors":"Deepali D. Ahir ,&nbsp;Nuzhat F. Shaikh","doi":"10.1016/j.rico.2024.100512","DOIUrl":"10.1016/j.rico.2024.100512","url":null,"abstract":"<div><div>Cloud computing has taken the world by storm with its numerous benefits like pay-as-you-go pricing, ease of deployment, and an ecosystem of services. Cloud computing has its share of challenges including security, vendor lock-in, cost in the long run, and configuration complexity. Along with the rise of its use, the threats from malicious actors are going up as well. These attackers either want to take down the services of cloud consumers or to hamper the financial viability of these services by inducing unwanted resource usage or by using cloud resources without the victim's consent. Low-rate denial of service attack (LDoS), and fraudulent resource consumption attack (FRC) are the two most important and widespread attacks which take advantage of the cloud provider's utility pricing and cause heavy financial damage to the victim. In LDoS attacks, the attack rate is kept low to remain undetected, which causes the victim's system to use more resources for a longer time or to lower the quality of service (QoS). FRC, like LDoS, is a low-rate attack, but its main motive is to use resources fraudulently. These attacks are difficult to detect and hence it can cause large financial damage to customers over the long run. The fundamental purpose of detecting and addressing FRC and LDoS is to decrease the financial implications of cloud infrastructure. This paper seeks to evaluate and provide a summary of the tools, techniques, and datasets that can be utilized in the research of FRC and LDoS attacks. To achieve its goal, this paper explains cloud computing, its benefits, and challenges and the security issues in the cloud with a focus on LDoS and FRC. It also summarizes the datasets, tools and attack detection techniques for LDoS and FRC, along with the review of research done in the past on LDoS and FRC detection. It concludes with the challenges in detecting FRC and future work.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100512"},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New class width rule for continuous frequency tables","authors":"Mohammed Bappah Mohammed ,&nbsp;Ishaq Abdullahi Baba ,&nbsp;Hauwa Danjuma Salihu ,&nbsp;Isah Abubakar Ibrahim","doi":"10.1016/j.rico.2024.100506","DOIUrl":"10.1016/j.rico.2024.100506","url":null,"abstract":"<div><div>The most significant parameter which must be determined before constructing a frequency table or a histogram is the number of classes or class width. Choosing the appropriate number of classes or class remains a long-lasting problem in statistics. Apart from the rules of thumb several more sophisticated rules were reported in the literature. However, none of them has been proven to be better in all situations. In this research, we proposed a new class width rule which can be used when building a frequency table or a histogram. The new class width rule is compared with nine existing classification rules, Sturges, Scott, Freedman and Diaconis, Doane, Terrel and Scott, Cencov, Cochran, Square root, and Rice rules, using the root mean-squared-error (RMSE). The accuracy of the classification rules is assessed using simulations from normal, uniform, exponential, log-normal, and gamma distributions, and also real data. The findings indicated that the proposed rule outperformed the other binning rules for simulations using normal, exponential, log-normal, and gamma distributions. Meanwhile, the square root rule performed better relative to the other classification rules for simulations from the uniform distribution. Comparison using real data showed that the proposed rule performed better than the other classification rules.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100506"},"PeriodicalIF":0.0,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Divided opposition strategy in particle swarm framework for constrained optimization problem","authors":"Sarika Jain ,&nbsp;Rekha Rani ,&nbsp;Pradeep Jangir ,&nbsp;Seyed Jalaleddin Mousavirad ,&nbsp;Ali Wagdy Mohamed","doi":"10.1016/j.rico.2024.100508","DOIUrl":"10.1016/j.rico.2024.100508","url":null,"abstract":"<div><div>In nature inspired algorithms, population initialization techniques play an important role to find an optimal solution. In this study, we proposed a novel population initialization technique Divided opposition-based learning Particle Swarm Optimization (D-PSO). This technique is inspired by Opposition Based Learning (OBL). D-PSO is a technique in which elements of initial population are uniformly cover the search space so the possibility of obtaining the optimal solution is highest. To validate the results D-PSO is tested on 16 benchmark functions for dimensions 10 and 30 and 12 CEC22 functions along with standard PSO, OBL-PSO, I-PSO. In standard PSO elements of initial population is randomly generated and in OBL-PSO elements of initial population are generated using OBL technique. I-PSO generate initial population elements using improved OBL technique. D-PSO gives better outcomes for all benchmark functions for dimension 10, 30 and 10 CEC22 function out of 12 as compared to other initialization techniques. To measure the significance of results a statistical analysis is also done in this study. Complexity analysis and convergence analysis is also measured for both set of benchmark functions. The convergence behavior of D-PSO for all benchmark function for dimension 10, 30 and 10 CEC22 function is best as compared to other initialization technique.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"18 ","pages":"Article 100508"},"PeriodicalIF":0.0,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143176358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal control governed impulsive neutral differential equations","authors":"Oscar Camacho ,&nbsp;René Erlin Castillo ,&nbsp;Hugo Leiva","doi":"10.1016/j.rico.2024.100505","DOIUrl":"10.1016/j.rico.2024.100505","url":null,"abstract":"<div><div>We derive Pontryagin’s Maximum Principle for optimal control problems characterized by nonlinear impulsive neutral type differential equations. Our method utilizes the Dubovitskii–Milyutin theory, assuming that the linear variational impulsive differential equation along the optimal solution is exactly controllable. This principle offers necessary conditions for identifying optimal solutions.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"17 ","pages":"Article 100505"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}