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Optimal PID controller for the DC-DC buck converter using the improved sine cosine algorithm

RESULTS IN CONTROL AND OPTIMIZATION 2024年 14卷

作者： Nanyan, Norsyahidatul Farah Ahmad, Mohd Ashraf Hekimoglu, Baran Univ Malaysia Pahang Al Sultan Abdullah Fac Elect & Elect Engn Technol Pekan 26600 Pahang Malaysia Batman Univ Dept Elect & Elect Engn TR-72100 Batman Turkiye

This paper presents an improved sine cosine algorithm (ISCA) towards optimization of a DC-DC buck converter with employment of the proportional-integral-derivative (PID) controller. Limitations of the conventional sine cosine algorithm (SCA) was hereby overcome through two separate alterations which pioneered a synergized employment of nonlinear equation to instrumental mechanism in revising the average location. Primary alteration tackled the issue of local optima by proposed instrumental function towards revision of average location. Secondary alteration then coordinated disproportional exploration and exploitation phases of the conventional SCA by application of a nonlinear equation against the algorithm's decreasing position- updated mechanism. Robustness of the proposed ISCA-PID approach was studied against preceding algorithm-based PID for DC-DC buck converter with respect to their step response, statistics regarding the analyzed objective function, time-domain integral-error performance, reaction to frequency, and resistance to disturbance and parametric uncertainties. Generated findings subsequently uncovered overshadowing efficacy of the proposed method over its algorithmic predecessors towards exceptionally enhanced transitory response of the DC-DC buck converter.

关键词： sine cosine algorithm Improved sine cosine algorithm (ISCA) algorithm-based PID controller DC-DC buck converter

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A novel oppositional learning-based chaotic sine cosine algorithm for the dynamic thermal-wind economic dispatch problem

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ENGINEERING OPTIMIZATION 2022年第12期54卷 2104-2122页

作者： Dasgupta, Koustav Roy, Provas Kumar Mukherjee, V. Techno India Univ Dept Elect Engn Salt Lake India Kalyani Govt Engn Coll Dept Elect Engn Kalyani W Bengal India Indian Inst Technol Dept Elect Engn Dhanbad Bihar India

Wind power generation is efficiently utilized with traditional thermal power generation in the dynamic economic emission dispatch (DEED) problem to achieve the demand power of scheduled periods with minimum generation cost and emission of pollutants. This study uses a novel oppositional learning-based chaotic sine cosine algorithm (SCA) (OL-CSCA) to solve a new model of wind energy-based DEED, called dynamic thermal-wind economic emission dispatch (DTWEED). The concepts of oppositional learning and chaos are introduced into the SCA to strengthen its optimization performance. The effectiveness of the proposed model is tested by solving four cases (generation cost, spinning reserve based generation cost, emission and combined cost-emission) using OL-CSCA. The novelty of DTWEED is shown by comparing the results of different cases with the traditional DEED model. Comparison of the results of OL-CSCA for different cases of DEED and DTWEED with the results of SCA and other algorithms demonstrated its robustness and proficiency.

关键词： Chaos dynamic economic emission dispatch oppositional learning strategy sine cosine algorithm wind energy

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State of charge estimation for lithium-ion batteries using dynamic neural network based on sine cosine algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2022年第2-3期236卷 241-252页

作者： Wei, Meng Ye, Min Li, Jia Bo Wang, Qiao Xu, Xin Xin Changan Univ Natl Engn Lab Highway Maintenance Equipment Xian Shaanxi Peoples R China

State of charge (SOC) of the lithium-ion batteries is one of the key parameters of the battery management system, which the performance of SOC estimation guarantees energy management efficiency and endurance mileage of electric vehicles. However, accurate SOC estimation is a difficult problem owing to complex chemical reactions and nonlinear battery characteristics. In this paper, the method of the dynamic neural network is used to estimate the SOC of the lithium-ion batteries, which is improved based on the classic close-loop nonlinear auto-regressive models with exogenous input neural network (NARXNN) model, and the open-loop NARXNN model considering expected output is proposed. Since the input delay, feedback delay, and hidden layer of the dynamic neural network are usually selected by empirically, which affects the estimation performance of the dynamic neural network. To cover this weakness, sine cosine algorithm (SCA) is used for global optimal dynamic neural network parameters. Then, the experimental results are verified to obtain the effectiveness and robustness of the proposed method under different conditions. Finally, the dynamic neural network based on SCA is compared with unscented Kalman filter (UKF), back propagation neural network based on particle swarm optimization (BPNN-PSO), least-squares support vector machine (LS-SVM), and Gaussian process regression (GPR), the results show that the proposed dynamic neural network based on SCA is superior to other methods.

关键词： Electric vehicles state of charge lithium-ion batteries dynamic neural network sine cosine algorithm

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Improved Chaotic sine cosine algorithm (ICSCA) for global optima

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International Journal of Information Technology (Singapore) 2024年第1期16卷 245-260页

作者： Shinde, Vikas Jha, Rahul Mishra, Dilip Kumar Department of Mathematics and Computing Madhav Institute of Technology and Science Gwalior India

This paper deals with sine cosine algorithm to make a balance between exploration and exploitation of the search space and find best convergence rate for global optima, that are used the two trigonometric function sine and cosine for modification of solution. We present the improved version of sine cosine algorithm which provide the better exploration mechanism for search space and ten chaotic maps have merged with improved sine cosine algorithm to determine the better outcomes with efficacies as well as proposed work as compared to others algorithms and incorporate four engineering problems. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Chaotic maps Constrained benchmark optimization Engineering design optimization sine cosine algorithm

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sine cosine algorithm with communication and quality enhancement: Performance design for engineering problems

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JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 2023年第4期10卷 1868-1891页

作者： Yu, Helong Zhao, Zisong Zhou, Jing Heidari, Ali Asghar Chen, Huiling Jilin Agr Univ Coll Informat Technol Changchun 130118 Peoples R China Univ Tehran Coll Engn Sch Surveying & Geospatial Engn Tehran *** Iran Wenzhou Univ Key Lab Intelligent Informat Safety & Emergency Zh Wenzhou 325035 Peoples R China

In recent years, the sine cosine algorithm (SCA) has become one of the popular swarm intelligence algorithms due to its simple and convenient structure. However, the standard SCA tends to fall into the local optimum when solving complex multimodal tasks, leading to unsatisfactory results. Therefore, this study presents the SCA with communication and quality enhancement, called CCEQSCA. The proposed algorithm includes two enhancement strategies: the communication and collaboration strategy (CC) and the quality enhancement strategy (EQ). In the proposed algorithm, CC strengthens the connection of SCA populations by guiding the search agents closer to the range of optimal solutions. EQ improves the quality of candidate solutions to enhance the exploitation of the algorithm. Furthermore, EQ can explore potential candidate solutions in other scopes, thus strengthening the ability of the algorithm to prevent trapping in the local optimum. To verify the capability of CCEQSCA, 30 functions from the IEEE CEC2017 are analyzed. The proposed algorithm is compared with 5 advanced original algorithms and 10 advanced variants. The outcomes indicate that it is dominant over other comparison algorithms in global optimization tasks. The work in this paper is also utilized to tackle three typical engineering design problems with excellent optimization capabilities. It has been experimentally demonstrated that CCEQSCA works as an effective tool to tackle real issues with constraints and complex search space. Graphical Abstract

关键词： sine cosine algorithm communication and collaboration quality enhancement engineering design

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Optimizing energy consumption patterns of smart home based on sine cosine algorithm

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第5期16卷 984-999页

作者： Youssef, Heba Kamel, Salah Hassan, Mohamed H. Khan, Baseem Aswan Univ Fac Engn Dept Elect Engn Aswan Egypt Hawassa Univ Dept Elect Engn Awasa Ethiopia

This paper presents a new application of the sine cosine algorithm (SCA) to obtain optimal home energy management systems (HEMS) that use the load shifting strategy of demand side management (DSM) to optimize the energy consumption patterns of a smart home. It aims to manage the load demand in an efficient way to decrease electricity bills and peak to average ratio (PAR) while maintaining user comfort through coordination among home devices. In order to meet the load demand of electricity consumers, this study schedules the load on a day-ahead and real-time basis. The main objective of the paper is to help balance the load through ON-peak hours and OFF-peak hours. Three price signals, namely: real-time pricing (RTP), time of use (TOU), and critical peak pricing (CPP), are used to evaluate the proposed algorithm. The results show that the electricity bill and PAR are minimized by up to 40% and 50%, respectively. The scheduling using coordination between devices in real-time does not significantly impact the cost of electricity and the peak to average ratio.

关键词： energy management systems electricity consumers RTP electricity bills home devices sine cosine algorithm load demand power markets ON-peak hours critical peak pricing smart home load shifting strategy energy consumption real-time pricing price signals OFF-peak hours pricing optimal home energy management systems real-time basis average ratio home automation energy consumption patterns PAR demand side management building management systems power engineering computing HEMS

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Economic load dispatch using memetic sine cosine algorithm

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JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING 2022年第9期14卷 11685-11713页

作者： Al-Betar, Mohammed Azmi Awadallah, Mohammed A. Abu Zitar, Raed Assaleh, Khaled Ajman Univ Coll Engn & Informat Technol Artificial Intelligence Res Ctr AIRC Ajman U Arab Emirates Al Balqa Appl Univ Al Huson Univ Coll Dept Informat Technol Irbid Jordan Al Aqsa Univ Dept Comp Sci POB 4051 Gaza Palestine Ajman Univ Artificial Intelligence Res Ctr AIRC Ajman U Arab Emirates Sorbonne Univ Abu Dhabi Sorbonne Univ Ctr Artificial Intelligence Abu Dhabi U Arab Emirates

In this paper, the economic load dispatch (ELD) problem which is an important problem in electrical engineering is tackled using a hybrid sine cosine algorithm (SCA) in a form of memetic technique. ELD is tackled by assigning a set of generation units with a minimum fuel costs to generate predefined load demand with accordance to a set of equality and inequality constraints. SCA is a recent population based optimizer turned towards the optimal solution using a mathematical-based model based on sine and cosine trigonometric functions. As other optimization methods, SCA has main shortcoming in exploitation process when a non-linear constraints problem like ELD is tackled. Therefore, beta-hill climbing optimizer, a recent local search algorithm, is hybridized as a new operator in SCA to empower its exploitation capability to tackle ELD. The proposed hybrid algorithm is abbreviated as SCA-beta HC which is evaluated using two sets of real-world generation cases: (i) 3-units, two versions of 13-units, and 40-units, with neglected Ramp Rate Limits and Prohibited Operating Zones constraints. (ii) 6-units and 15-units with Ramp Rate Limits and Prohibited Operating Zones constraints. The sensitivity analysis of the control parameters for SCA-beta HC is initially studied. The results show that the performance of the SCA-beta HC algorithm is increased by tuning its parameters in proper value. The comparative evaluation against several state-of-the-art methods show that the proposed method is able to produce new best results for some tested cases as well as the second-best for others. In a nutshell, hybridizing beta HC optimizer as a new operator for SCA is very powerful algorithm for tackling ELD problems.

关键词： Economic load dispatch Hybrid metaheuristics sine cosine algorithm beta-hill climbing optimizer Power systems

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Image registration of computed tomography of lung infected with COVID-19 using an improved sine cosine algorithm

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MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 2022年第9期60卷 2521-2535页

作者： Dida, Hedifa Charif, Fella Benchabane, Abderrazak Univ Kasdi Merbah Dept Elect & Telecommun Lab Genie Elect LAGE Ouargla Algeria Univ Kasdi Merbah Dept Elect & Telecommun Ouargla Algeria

In recent years, the optimization problem using meta-heuristic algorithms has been widely used in medical image registration and was a solution in diagnosing many diseases and tumors. Given the great success achieved by the sine cosine algorithm (SCA) and particle swarm optimization (PSO) algorithms in many medical images analysis, and the use of the computed tomography (CT) scan images for diagnosing COVID-19 patients, we propose an improved sine cosine algorithm (ISCA) resulting from the hybridization of the SCA and PSO algorithms to register the CT images of the lung of the people infected by COVID-19. Simulation results show that the proposed approach can achieve high accuracy and robust recording compared to the SCA method.

关键词： COVID-19 sine cosine algorithm Particle swarm optimization Image registration

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Robust 2D and 3D images zero - watermarking using dual Hahn moment invariants and sine cosine algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2022年第18期81卷 25581-25611页

作者： Daoui, Achraf Karmouni, Hicham Sayyouri, Mhamed Qjidaa, Hassan Sidi Mohamed Ben Abdellah Fez Univ Natl Sch Appl Sci Lab Engn Syst & Applicat Fes Morocco Sidi Mohamed Ben Abdellah Fez Univ Fac Sci Lab Elect Signals & Syst Informat Fes Morocco

In this paper, we initially provide significant improvements on the computational aspects of dual Hahn moment invariants (DHMIs) in both 2D and 3D domains. These improvements ensure the numerical stability of DHMIs for large-size images. Then, we propose an efficient method for optimizing the local parameters of dual Hahn polynomials (DHPs) when computing DHMIs using the sine-cosine algorithm (SCA). DHMIs optimized via SCA are used to propose new and robust zero-watermarking scheme applied to both 2D and 3D images. On one hand, the simulation results confirm the efficiency of the proposed computation of 2D and 3D DHMIs regarding the numerical stability and invariability. Indeed, the proposed computation method of 2D DHMIs allows to reach a relative error (RE) of the order approximate to 10(-10) for images of size 1024 x 1024 with an execution time improvement ratio exceeds 70% (ETIR >= 70%), which validates the efficiently of the proposed computation method. On the other hand, the simulation and comparison outcomes clearly demonstrate the robustness of the proposed zero-watermarking scheme against various geometric attacks (translation, rotation, scaling and combined transformations), as well as against other common 2D and 3D image processing attacks (compression, filtering, noise addition, etc.).

关键词： Image reconstruction 2D and 3D image zero-watermarking Discrete orthogonal moments Dual - Hahn moment invariants sine cosine algorithm Numerical stability

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A chaotic sine cosine algorithm with crossover operator for microgrid energy scheduling considering uncertainty

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2022年第5期43卷 6805-6819页

作者： Qiu, Chenye Fang, Huixing Liu, Ning Huangshan Univ Sch Informat Engn 39 Xihai Rd Huangshan 245000 Peoples R China Nanjing Univ Posts & Telecommun Sch Internet Things Nanjing Peoples R China

Microgrid (MG) systems are growing at a rapid pace since they can accommodate the high amount of renewable energy. Since the MG consists of small distributed generators (DG) with volatile characteristics, an efficient energy management system is the main requisite in MG. In this paper, a chaotic sine cosine algorithm with crossover operator (CSCAC) is proposed for the day-ahead MG optimal energy scheduling problem. CSCAC includes a novel non-linear transition parameter based on the chaos system which can help the algorithm escape from local optima. A chaotic search operator is proposed to enhance the local search ability. Furthermore, a crossover operator is devised to combine the advantages of different search strategies and achieve a comparatively better balance of exploration and exploitation. First, the effectiveness of CSCAC is validated on several benchmark functions. Then, it is applied to the day-ahead energy scheduling in a MG with three wind power plants, two photovoltaic power plants and a combined heat and power plant (CHP). Furthermore, it is implemented in two more cases considering the uncertainty and stochastic nature of the renewable power sources. Experimental results demonstrate the superiority of CSCAC over other comparative algorithms in the optimal MG energy management problem.

关键词： sine cosine algorithm microgrid chaotic system energy scheduling uncertainty

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