Results in Control and Optimization最新文献_第2页

Optimizing photovoltaic performance: Data-driven maximum power point prediction via advanced regression models 优化光伏性能：基于先进回归模型的数据驱动最大功率点预测

Results in Control and Optimization Pub Date : 2025-06-19 DOI: 10.1016/j.rico.2025.100586

Maissa Farhat , Azzeddine Dekhane , Abdelhak Djellad , Maen Takruri , Aws Al-Qaisi , Oscar Barambones

{"title":"Optimizing photovoltaic performance: Data-driven maximum power point prediction via advanced regression models","authors":"Maissa Farhat , Azzeddine Dekhane , Abdelhak Djellad , Maen Takruri , Aws Al-Qaisi , Oscar Barambones","doi":"10.1016/j.rico.2025.100586","DOIUrl":"10.1016/j.rico.2025.100586","url":null,"abstract":"<div><div>The accurate prediction of the Maximum Power Point (PMPP) in photovoltaic (PV) systems is critical for optimizing energy yield and enhancing solar energy harvesting efficiency. This study explores the application of data-driven methods to improve PMPP prediction, utilizing advanced regression techniques such as Ridge Regression, Lasso Regression, Decision Tree Regression, and Random Forest Regression. By analyzing a dataset of irradiance, temperature, and PMPP measurements, the research compares the performance of these models in capturing complex nonlinear relationships between key variables. Results indicate that tree-based models, particularly Random Forest Regression, outperform linear models, demonstrating superior predictive accuracy and robustness. Feature importance analysis further highlights the dominant influence of irradiance (GPOA) on PMPP, emphasizing the value of precise irradiance data. These findings underscore the potential of machine learning techniques in optimizing PV system performance. Future research should focus on integrating additional features, such as atmospheric conditions and panel characteristics, and exploring deep learning methods to enhance prediction accuracy further.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"20 ","pages":"Article 100586"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The impact of climate change on flowering plants-bees-Vespa orientalis model 气候变化对开花植物-蜜蜂-东方黄蜂模型的影响

Results in Control and Optimization Pub Date : 2025-06-19 DOI: 10.1016/j.rico.2025.100583

Shireen Jawad , Ashraf Adnan Thirthar , Kottakkaran Sooppy Nisar

{"title":"The impact of climate change on flowering plants-bees-Vespa orientalis model","authors":"Shireen Jawad , Ashraf Adnan Thirthar , Kottakkaran Sooppy Nisar","doi":"10.1016/j.rico.2025.100583","DOIUrl":"10.1016/j.rico.2025.100583","url":null,"abstract":"<div><div>There is a dearth of mathematical models that combine climatic stress, mutualism (plant-bee), and antagonism (Vespa predation on bees) in a single ecological system, despite the fact that numerous research look at how climate change impacts particular species or paired interactions. Our capacity to forecast the cascade impacts of warming on pollination services and plant reproduction is hampered by this gap. The densities of the flowering plant depend on the behavior of the pollinators. We describe a novel pollinator model consisting of flowering plants and two pollinator species (honey bees and Vespa orientalis). It assumed that flowering plants’ densities depend on flower visitation rates by honey bees and Vespa orientalis. Also, the global warming phenomenon is assumed to harm the growth of flowering plants and honey bees. The Vespa orientalis hinders the expansion of bees, as they kill them and take the honey inside their stomachs. After presenting the model, the system’s positivity and boundedness, which are crucial for ensuring well-posedness in any dynamical model, are confirmed. The conditions under which the possible equilibrium points exist are established. Furthermore, discussed are the conditions for obtaining local stability around each equilibrium point. Uniform persistence, which ensures the simultaneous existence of all species, is executed. The required conditions for the occurrence of Hopf bifurcations are performed. Analytical confirmation is obtained by the use of numerical simulation. By manipulating the parametric values, the system displays phenomena such as stability, periodic attracts, and the eradication of some species. Therefore, the present study can assist ecologists in determining the parameters necessary to investigate and acquire significant data regarding flowering plant-pollinator systems.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"20 ","pages":"Article 100583"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing computational efficiency of iLQR and DDP via the parametric representation of control inputs 通过控制输入的参数化表示，提高了iLQR和DDP的计算效率

Results in Control and Optimization Pub Date : 2025-06-19 DOI: 10.1016/j.rico.2025.100587

Yoshihiro Iwanaga , Yasutaka Fujimoto

{"title":"Enhancing computational efficiency of iLQR and DDP via the parametric representation of control inputs","authors":"Yoshihiro Iwanaga , Yasutaka Fujimoto","doi":"10.1016/j.rico.2025.100587","DOIUrl":"10.1016/j.rico.2025.100587","url":null,"abstract":"<div><div>Efficiently solving nonlinear optimal control problems is crucial in trajectory planning and model predictive control. This can be achieved by utilizing differential dynamic programming (DDP) and iterative linear quadratic regulator (iLQR), which have recently gained attention. As these algorithms partition the problem into subproblems at each time step, they exhibit linear complexity of one iteration in the length of the prediction horizon. While these methodologies are computationally efficient, industrial applications demand further improvements in computational efficiency, primarily due to the limitations of embedded CPUs. The parametric representation of control inputs has been widely adopted to reduce the dimensionality of decision variables in optimal control problems. However, the subproblem partitioning inherent in DDP and iLQR presents challenges for directly incorporating this representation. In this study, we present a computationally efficient algorithm that integrates a parametric representation of control inputs into DDP- or iLQR-like algorithms. We exemplified a scenario in which parametric representation was introduced by considering interior-point DDP and iLQR, which could handle nonlinear inequality constraints. The effectiveness of this approach for practical applications was demonstrated through a series of numerical experiments. In particular, these numerical experiments mainly focused on key real-world problems, such as trajectory planning for forklifts and optimal excavation trajectory planning for an excavator. Regarding trajectory planning for forklifts and excavators, we achieved a maximum reduction of about 70% in the total computation time.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"20 ","pages":"Article 100587"},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm 不平衡配电网中导线优化选择与相位平衡：基于涡流搜索算法的经济优化

Results in Control and Optimization Pub Date : 2025-06-16 DOI: 10.1016/j.rico.2025.100578

Brandon Cortés-Caicedo , Jhony Andrés Guzmán-Henao , Oscar Danilo Montoya , Luis Fernando Grisales-Noreña , Rubén Iván Bolaños

{"title":"Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm","authors":"Brandon Cortés-Caicedo , Jhony Andrés Guzmán-Henao , Oscar Danilo Montoya , Luis Fernando Grisales-Noreña , Rubén Iván Bolaños","doi":"10.1016/j.rico.2025.100578","DOIUrl":"10.1016/j.rico.2025.100578","url":null,"abstract":"<div><div>The inherent characteristics of unbalanced three-phase distribution networks can have negative technical and financial effects. In this vein, optimal conductor size selection and phase balancing are among the most common strategies for improving these indicators, which involves dealing with complex optimization problems. This article presents a mixed-integer nonlinear programming model to address conductor selection and phase balancing in distribution systems. Given the complexity of the model, a leader–follower methodology based on the vortex search algorithm (VSA) is employed to determine the conductor caliber and load phase configuration, in conjunction with the three-phase successive approximations power flow method to compute the objective function. This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. Simulation results demonstrate that the proposed methodology provides the best solution for unbalanced distribution systems comprising eight and 25 nodes. The VSA yielded the best response, with values of 125,348.4870 USD and 94,475.1477 USD in the two test feeders, respectively, as well as the lowest standard deviation (0.1948% and 0.2147%) while requiring reasonable computational times, within the average for the 8-node system and the best time for the 25-node system. The VSA demonstrated superior performance in terms of cost minimization and solution consistency with a reasonable computational effort, which makes it a valuable tool for optimizing unbalanced distribution systems and enhancing their overall efficiency.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"20 ","pages":"Article 100578"},"PeriodicalIF":0.0,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144306407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal control-based quantum genetic algorithm for a six jointed articulated robotic arm 基于最优控制的六关节机械臂量子遗传算法

Results in Control and Optimization Pub Date : 2025-06-06 DOI: 10.1016/j.rico.2025.100584

Mohamed Salah Dahassa, Nadjet Zioui

{"title":"Optimal control-based quantum genetic algorithm for a six jointed articulated robotic arm","authors":"Mohamed Salah Dahassa, Nadjet Zioui","doi":"10.1016/j.rico.2025.100584","DOIUrl":"10.1016/j.rico.2025.100584","url":null,"abstract":"<div><div>This paper explores the use of a quantum genetic algorithm (QGA) for finding the best control considering a calculated path for a six-jointed robotic arm. Classical genetic algorithms (GAs) are typically used to solve optimization problems in robot manipulators, however, QGAs bring a consistent advantage in terms of solution quality. In fact, this study uses a QGA simulated on classical hardware to create optimal control law based on a fifth-order polynomial path, aiming to minimize the tracking error of the position. Eventually, it compares positional error and energy consumption used by actuators through its cost function with to the classical methods. The simulation demonstrates that the QGA tends to be better than real-coded and binary-coded genetic algorithms (respectively RCGA and BCGA), especially when it comes to tracking accuracy, energy, and maintaining stability in noisy conditions. This indicates its potential use in real-time robotics applications by exploring quantum algorithms' practical benefits over traditional optimization methods for complex tasks with multiple dimensions in robot systems control.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"20 ","pages":"Article 100584"},"PeriodicalIF":0.0,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decision-maker’s behavioral preferences modeling in fuzzy goal programming through linear-nonlinear membership functions 基于线性-非线性隶属函数的模糊目标规划中决策者行为偏好建模

Results in Control and Optimization Pub Date : 2025-06-01 DOI: 10.1016/j.rico.2025.100576

Mohamed Sadok Cherif

{"title":"Decision-maker’s behavioral preferences modeling in fuzzy goal programming through linear-nonlinear membership functions","authors":"Mohamed Sadok Cherif","doi":"10.1016/j.rico.2025.100576","DOIUrl":"10.1016/j.rico.2025.100576","url":null,"abstract":"<div><div>A relevant extension of traditional goal programming (GP), fuzzy goal programming (FGP) can handle uncertainty and imprecision in multi-objective optimization problems. Based on fuzzy set theory, the notion of membership functions has been introduced to consider the fuzziness related to objectives and constraints. These membership functions are mainly intended for fuzziness in the GP rather than modeling the decision-maker’s (DM’s) preferences and his/her attitude toward risk in the decision-making process. In the satisfying philosophy of FGP, little attention has been given to how preferences evolve in terms of the behavior of the decision-maker (DM) and how these preferences may affect decisions in risky scenarios. To address this issue, we suggest novel behavioral-type utility functions for the FGP approach by introducing the concept of behavioral membership functions. This concept offers an innovative procedure for simulating the DM’s behavioral preferences in the FGP approach. First, two main categories of objectives in relation to the DM’s behavioral preferences are distinguished in this work. A risk aversion parameter is integrated into membership functions according to the nature of each objective type, obtaining the so-called behavioral membership functions. A behavioral FGP approach is subsequently formulated. Finally, an illustrative example of venture capital investments, a sensitivity analysis, and comparisons with other FGP approaches are provided to demonstrate the validity and practicality of our proposed approach.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"19 ","pages":"Article 100576"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal control problem for COVID-19 with multiple time-delays in state and control 具有状态和控制多时滞的COVID-19最优控制问题

Results in Control and Optimization Pub Date : 2025-06-01 DOI: 10.1016/j.rico.2025.100579

Mohcine El Baroudi , Hassan Laarabi , Samira Zouhri , Mostafa Rachik , Abdelhadi Abta

{"title":"Optimal control problem for COVID-19 with multiple time-delays in state and control","authors":"Mohcine El Baroudi , Hassan Laarabi , Samira Zouhri , Mostafa Rachik , Abdelhadi Abta","doi":"10.1016/j.rico.2025.100579","DOIUrl":"10.1016/j.rico.2025.100579","url":null,"abstract":"<div><div>The primary motivation of this paper is to identify the most effective implementation of delayed preventive measures, including active screening and testing, mask-wearing, and vaccination for COVID-19, in a way that minimizes the number of infected and exposed individuals, and maximizes the count of recovered individuals. Our goal is to comprehend the impact of delays on the epidemic’s spread and to offer guidance to health authorities on what steps to take if they implement COVID-19 preventive measures too late. We achieve this by employing optimal control theory on a SEIR model that illustrates the dynamics between susceptible, infected, exposed, and recovered individuals within the population. We set up our optimal control problem with multiple time delays in both the state and control variables, then, we used Pontryagin’s Maximum Principle to determine the solution to the delayed optimal control problem with multiple state-control constraints. Our results of simulation show that to control epidemic propagation when preventive measures are delayed, we should take immediate action after delay phase by enforcing mask wear and starting vaccinations to cover a significant portion of the population as quickly as possible. We should then implement active screening and testing measures to further control the spread.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"19 ","pages":"Article 100579"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144184741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

H∞ filtering of uncertain predictive models: Gain computation using LMI and performance evaluation 不确定预测模型的H∞滤波：使用LMI的增益计算和性能评估

Results in Control and Optimization Pub Date : 2025-06-01 DOI: 10.1016/j.rico.2025.100581

Eli G. Pale Ramon, Oscar G. Ibarra-Manzano, José A. Andrade-Lucio, Yuriy S. Shmaliy

{"title":"H∞ filtering of uncertain predictive models: Gain computation using LMI and performance evaluation","authors":"Eli G. Pale Ramon, Oscar G. Ibarra-Manzano, José A. Andrade-Lucio, Yuriy S. Shmaliy","doi":"10.1016/j.rico.2025.100581","DOIUrl":"10.1016/j.rico.2025.100581","url":null,"abstract":"<div><div>Increasing the process informativity and the efficiency of control is achieved using state estimators, which need to be robust under harsh conditions. In this paper, we look at the robust state estimation problem of uncertain models using the transfer function approach through the bias correction gain <span><math><mi>K</mi></math></span> of a recursive <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> filter. The filter is designed for processes represented in discrete time using the forward Euler method, which allows for predictive modeling. Since the error covariance of a state estimator is a quadratic function of <span><math><mi>K</mi></math></span>, a new theorem is proved and a numerical algorithm is developed for computing <span><math><mi>K</mi></math></span> using linear matrix inequality (LMI). An LMI-based algorithm for iterative <span><math><mi>K</mi></math></span> computation is also given. Numerical investigations are provided using two random models with uncertainties. Using the “Box” benchmark of visual object tracking, an experimental comparison of the <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span>, Kalman, and robust unbiased finite impulse response (UFIR) filters is provided in terms of root mean square error, robustness factor, and estimation quality factor. It is shown that <span><math><mi>K</mi></math></span> of the <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> filter is in the range between the Kalman gain and the UFIR filter gain.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"19 ","pages":"Article 100581"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144263175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal control strategies for mitigating drug addiction: A mathematical modeling approach 缓解药物成瘾的最优控制策略：一种数学建模方法

Results in Control and Optimization Pub Date : 2025-06-01 DOI: 10.1016/j.rico.2025.100580

Mostofa Kamal, Mostak Ahmed, Md. Abu Hanif Sarkar

引用次数: 0

The role of amensalism and parasitism on the dynamics of three species ecological system 寄生性和寄生性对三种生态系统动态的影响

Results in Control and Optimization Pub Date : 2025-05-22 DOI: 10.1016/j.rico.2025.100571

Alyaa Raad Saleh Abd Alhadi, Raid Kamel Naji

{"title":"The role of amensalism and parasitism on the dynamics of three species ecological system","authors":"Alyaa Raad Saleh Abd Alhadi, Raid Kamel Naji","doi":"10.1016/j.rico.2025.100571","DOIUrl":"10.1016/j.rico.2025.100571","url":null,"abstract":"<div><div>This paper introduces a novel mathematical model of a three-species ecosystem that includes biological relationships such as amensalism and parasitism. Unlike most previous studies, it assumed that the ecosystem consists of three different kinds of interactions at the same time: two host–parasite interactions, while the third one is amensal–enemy interactions. To do the dynamic analysis of this system, all of the solution’s attributes were examined, and potential equilibrium points were found. The local stability was established using the linearization technique. The global stability was examined using Lyapunov functions. Every prerequisite for perseverance was identified. The effects of varying the parameters were investigated using the bifurcation theory. A computer simulation was applied to bolster our analytical research. It is observed that the proposed model has a globally stable coexistence point, while the periodic dynamics do not exist. The impact of amensalism and parasitism is clearly shown due to the transition of the solution from the coexistence point to the planar equilibrium points once their rates exceed a vital value, and conversely, it is proved that the system <span><span>(3)</span></span> undergoes a transcritical bifurcation near the first axial and the enemy–host-free equilibrium points.</div></div>","PeriodicalId":34733,"journal":{"name":"Results in Control and Optimization","volume":"19 ","pages":"Article 100571"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0