Results in Control and Optimization最新文献_第3页

Challenges and opportunities in the industrial usage controller synthesis tools: A review of LTL-based opensource tools for automated control design

Results in Control and Optimization Pub Date : 2025-01-06 DOI: 10.1016/j.rico.2024.100511

Amar Banerjee, Venkatesh Choppella

引用次数: 0

Non-linear PID control of AC current and DC voltage for a photovoltaic system operating on a microgrid

Results in Control and Optimization Pub Date : 2025-01-01 DOI: 10.1016/j.rico.2024.100514

Pablo Proaño , Marcelo Pozo , Carlos Gallardo , Oscar Camacho

{"title":"Non-linear PID control of AC current and DC voltage for a photovoltaic system operating on a microgrid","authors":"Pablo Proaño , Marcelo Pozo , Carlos Gallardo , 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}

引用次数: 0

Understanding issues and challenges posed by LDoS, FRC attacks on cloud environment

Results in Control and Optimization Pub Date : 2024-12-25 DOI: 10.1016/j.rico.2024.100512

Deepali D. Ahir , Nuzhat F. Shaikh

{"title":"Understanding issues and challenges posed by LDoS, FRC attacks on cloud environment","authors":"Deepali D. Ahir , 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}

引用次数: 0

New class width rule for continuous frequency tables

Results in Control and Optimization Pub Date : 2024-12-21 DOI: 10.1016/j.rico.2024.100506

Mohammed Bappah Mohammed , Ishaq Abdullahi Baba , Hauwa Danjuma Salihu , Isah Abubakar Ibrahim

{"title":"New class width rule for continuous frequency tables","authors":"Mohammed Bappah Mohammed , Ishaq Abdullahi Baba , Hauwa Danjuma Salihu , 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}

引用次数: 0

Divided opposition strategy in particle swarm framework for constrained optimization problem

Results in Control and Optimization Pub Date : 2024-12-06 DOI: 10.1016/j.rico.2024.100508

Sarika Jain , Rekha Rani , Pradeep Jangir , Seyed Jalaleddin Mousavirad , Ali Wagdy Mohamed

{"title":"Divided opposition strategy in particle swarm framework for constrained optimization problem","authors":"Sarika Jain , Rekha Rani , Pradeep Jangir , Seyed Jalaleddin Mousavirad , 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}

引用次数: 0

Optimal control governed impulsive neutral differential equations

Results in Control and Optimization Pub Date : 2024-12-01 DOI: 10.1016/j.rico.2024.100505

Oscar Camacho , René Erlin Castillo , Hugo Leiva

引用次数: 0

TSP solution using an exact model based on the branch flow formulation and automatic cases generation via the Julia software

Results in Control and Optimization Pub Date : 2024-12-01 DOI: 10.1016/j.rico.2024.100507

Oscar Danilo Montoya , Walter Gil-González , Luis Fernando Grisales-Noreña , Rubén Iván Bolaños , Jorge Ardila-Rey

{"title":"TSP solution using an exact model based on the branch flow formulation and automatic cases generation via the Julia software","authors":"Oscar Danilo Montoya , Walter Gil-González , Luis Fernando Grisales-Noreña , Rubén Iván Bolaños , Jorge Ardila-Rey","doi":"10.1016/j.rico.2024.100507","DOIUrl":"10.1016/j.rico.2024.100507","url":null,"abstract":"<div><div>The traveling salesman problem (TSP) is a classical optimization problem with practical applications in logistics, transportation, and network design. This research proposes an efficient mixed-integer linear programming (MILP) model based on the branch flow formulation which prevents the formation of sub-tours during the solution process and guarantees valid optimal routes. Implemented in Julia with the JuMP optimization package and the HiGHS solver, the model achieves high computational efficiency. Unlike classical models, the branch flow formulation ensures a quadratic constraint growth, rather than an exponential one, significantly enhancing scalability. Benchmark tests on various instances (Eil51, Eil76, KroA100) demonstrate results comparable to state-of-the-art combinatorial optimizers, and six new TSP instances, ranging from 50 to 300 cities, validate the model’s performance. This scalable and robust approach is well-suited for real-world applications in supply chain management, network optimization, and urban planning, and it shows potential for future extensions to dynamic or multi-objective TSP variants.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"17 ","pages":"Article 100507"},"PeriodicalIF":0.0,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143128241","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}

引用次数: 0

Optimal fuzzy robust state feedback control for a five DOF active suspension system 五自由度主动悬架系统的最优模糊鲁棒状态反馈控制

Results in Control and Optimization Pub Date : 2024-12-01 DOI: 10.1016/j.rico.2024.100504

M.J. Mahmoodabadi , N. Nejadkourki , M. Yousef Ibrahim

引用次数: 0

A pursuit-evasion game robot controller design based on a neural network with an improved optimization algorithm 基于神经网络和改进优化算法的追逐-逃避游戏机器人控制器设计

Results in Control and Optimization Pub Date : 2024-11-23 DOI: 10.1016/j.rico.2024.100503

Mustafa Wassef Hasan, Luay G. Ibrahim

{"title":"A pursuit-evasion game robot controller design based on a neural network with an improved optimization algorithm","authors":"Mustafa Wassef Hasan, Luay G. Ibrahim","doi":"10.1016/j.rico.2024.100503","DOIUrl":"10.1016/j.rico.2024.100503","url":null,"abstract":"<div><div>A pursuit-evasion game (PEG) is a type of game that utilizes one or several cooperative pursuers to capture one or several evaders. The PEG game concept has been used in different multi-robot applications such as transportation or navigation applications, search and rescue, surveillance applications such as collision avoidance and air traffic control systems, multi-defense applications such as missile guidance systems, and medical applications such as analyzing biological behaviors. Regardless of the benefits of PEG, one of the main drawbacks of such systems is the computational burden and the immense time required to learn such systems. For this reason, this work proposes a neural network game based on the pursuit-evasion game, where the leader (evader) robot tries to eat several particles/apples distributed inside a closed game environment with boundary and inner obstacles. In contrast, a follower (pursuer) robot tries to capture the leader robot and stop the particle-eating process. The leader and follower robots were designed based on a differential two-wheel robot (DTWR). The neural network is presented to control and learn the leader and follower robot directions with respect to the boundary and inside obstacles in the game environment. The neural network weights are learned using an improved sine cosine algorithm based on chaotic theory (ISCACT). The ISCACT is proposed to solve and avoid the proposed game of being trapped in the local minimum problem. The ISCACT is tested based on five multimodal benchmark functions. The ISCACT has been used in two cases, the first case arises when ISCACT is used in the follower robot’s learning process. In the second case, the ISCACT has been used in the leader robot’s learning process. The results for the first and second cases prove the superiority of the ISCACT compared with other existing works in enhancing the PEG performance time and reducing the computational burden for multi-robot applications.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"17 ","pages":"Article 100503"},"PeriodicalIF":0.0,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142720549","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}

引用次数: 0

Prediction of seam strength of cotton canvas fabric using fuzzy logic 利用模糊逻辑预测棉帆布的接缝强力

Results in Control and Optimization Pub Date : 2024-11-22 DOI: 10.1016/j.rico.2024.100502

Elias Khalil , Mahmuda Akter

{"title":"Prediction of seam strength of cotton canvas fabric using fuzzy logic","authors":"Elias Khalil , Mahmuda Akter","doi":"10.1016/j.rico.2024.100502","DOIUrl":"10.1016/j.rico.2024.100502","url":null,"abstract":"<div><div>This study investigates the application of fuzzy logic in predicting seam strength in cotton plain canvas fabric, focusing on both warp and weft directions. The precise prediction of seam strength is crucial for manufacturers to uphold quality standards, enhance production efficiency, and minimize waste. The fuzzy logic model in this study uses thread linear density and stitch per inch as input parameters and warp and weft seam strength as output variables. The modeling was conducted using MATLAB, specifically utilizing the Mamdani fuzzy inference system with triangle membership functions. The fuzzy logic model was found to be very accurate, as shown by coefficients of determination (R<sup>2</sup>) of 0.9841 for the warp way and 0.9888 for the weft way, along with correlation coefficients (R) of 0.992 and 0.9944. The mean absolute percentage error (MAPE) was calculated to be 4.8719 % for the warp way and 4.7561 % for the weft way, each below 5 %, underscoring the model's reliability and robustness in seam strength prediction. This research provides findings with substantial implications for the textile industry, where the application of predictive models is on the rise to enhance production efficiency and product quality. Manufacturers can improve their ability to forecast regarding fabric properties and adjust production processes through the implementation of fuzzy logic models. This approach is consistent with current industry trends emphasizing automation and digitalization, wherein predictive models are essential for facilitating smart manufacturing and quality control.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"17 ","pages":"Article 100502"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142705806","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}

引用次数: 0