Systems Science & Control Engineering最新文献_第8页

Optimal dispatching of microgrid based on improved moth-flame optimization algorithm based on sine mapping and Gaussian mutation 基于正弦映射和高斯突变改进蛾焰优化算法的微电网优化调度

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-03-01 DOI: 10.1080/21642583.2022.2042424

Yu Zhang, Peng Wang, Hongwan Yang, Qi Cui

{"title":"Optimal dispatching of microgrid based on improved moth-flame optimization algorithm based on sine mapping and Gaussian mutation","authors":"Yu Zhang, Peng Wang, Hongwan Yang, Qi Cui","doi":"10.1080/21642583.2022.2042424","DOIUrl":"https://doi.org/10.1080/21642583.2022.2042424","url":null,"abstract":"Because the traditional power generation method has caused certain damage to the environment, the microgrid system composed of renewable energy has been widely developed and applied. This paper studies distributed power sources including photovoltaics, wind turbines, energy storage systems, gas turbines, and fuel cells. Under the conditions of microgrid islands and grid-connected operation, the fuel cost, operation and maintenance cost, and the electricity transaction cost between the microgrid and the distribution network, establish the optimal objective function for the operating cost of the microgrid. At the same time, due to the standard moth-flame optimization algorithm having low optimization accuracy and are easy to fall into local optimal solution, an improved moth-flame optimization algorithm based on Sine mapping and Gaussian mutation is proposed. This algorithm is used to obtain the output of each distributed power source and total operating cost in a dispatch period. Finally, an example is used to verify the effectiveness and economy of the proposed model and the improved algorithm.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41310808","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: 6

Application of fuzzy random-based multi-objective linear fractional programming to inventory management problem 基于模糊随机的多目标线性分式规划在库存管理问题中的应用

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-02-28 DOI: 10.1080/21642583.2022.2040060

Hamiden Abd El-Wahed Khalifa, Pavan Kumar, S. Alodhaibi

引用次数: 4

Synthesis analysis for data driven model predictive control* 数据驱动模型预测控制的综合分析*

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-02-28 DOI: 10.1080/21642583.2022.2039321

Hong Jianwang, R. Ramírez-Mendoza

引用次数: 1

A modified method for improving the prediction accuracy of the tunnel shaking table model test based on non-direct similarity technique 基于非直接相似技术提高隧道振动台模型试验预测精度的改进方法

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-02-28 DOI: 10.1080/21642583.2022.2040061

Cheng Wang, Feng Gao, Xukai Tan, Wei Xu

{"title":"A modified method for improving the prediction accuracy of the tunnel shaking table model test based on non-direct similarity technique","authors":"Cheng Wang, Feng Gao, Xukai Tan, Wei Xu","doi":"10.1080/21642583.2022.2040061","DOIUrl":"https://doi.org/10.1080/21642583.2022.2040061","url":null,"abstract":"The tunnel shaking table model test has many influencing factors, and the test parameters are difficult to meet the strict similarity ratio. There are often large errors in predicting prototypes directly using the similarity ratio derived from the classical similarity theory. In order to improve the prediction accuracy of the tunnel shaking table model test, this article proposes a modified method of the traditional similarity theory. Based on the traditional dimensional analysis method, this method uses a non-direct similarity technique to rebuild the dimensional matrix for the main test parameters, derive a new similarity criterion, and then obtain a new similarity ratio. Different from the traditional similarity ratio which is a certain value, the new similarity ratio varies with dynamic parameters, which is more consistent with the actual situation. The tunnel shaking table model test and numerical simulation are carried out to verify the method. Experiments show that the modified method is superior to the traditional similarity theory in numerical prediction accuracy.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45400873","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

A combined backstepping and fractional-order PID controller to trajectory tracking of mobile robots 一种基于反步和分数阶PID的移动机器人轨迹跟踪组合控制器

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-02-27 DOI: 10.1080/21642583.2022.2047125

Lin Xu, Jiaqiang Du, Baoye Song, Maoyong Cao

{"title":"A combined backstepping and fractional-order PID controller to trajectory tracking of mobile robots","authors":"Lin Xu, Jiaqiang Du, Baoye Song, Maoyong Cao","doi":"10.1080/21642583.2022.2047125","DOIUrl":"https://doi.org/10.1080/21642583.2022.2047125","url":null,"abstract":"Trajectory tracking is a critical problem in the field of mobile robotics. In this paper, a control scheme combined with backstepping and fractional-order PID is developed for the trajectory tracking of the differential-drive mobile robot. The kinematic and dynamic models of the mobile robot are described in detail for the trajectory tracking controller design. Then, based on the model of the mobile robot, the design of the trajectory tracking control system is addressed by combining backstepping with fractional-order PID. Moreover, to obtain an optimal control system, an improved beetle swarm optimization algorithm is presented to tune the parameters of the kinematic and dynamic controllers simultaneously. Finally, several simulations are implemented to the trajectory tracking of mobile robots in the cases with and without skidding and sliding, and the results can confirm the effectiveness and superiority of the combined control scheme. Abbreviations: FOPID: fractional-order PID; FOPD: fractional-order PD; DDMR:differential-drive mobile robot; BAS: beetle antennae search; BA: beetle antennae; PSO:particle swarm optimization; BSO: beetle swarm optimization.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43279947","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: 7

A fair dynamic content store-based congestion control strategy for named data networking 一种基于公平动态内容存储的命名数据网络拥塞控制策略

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-02-04 DOI: 10.1080/21642583.2022.2031335

Yan-Hong Liu, Fengling Huang, Hua Yang

引用次数: 5

High-speed vision measurement of vibration based on an improved ZNSSD template matching algorithm 基于改进ZNSSD模板匹配算法的振动高速视觉测量

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-01-12 DOI: 10.1080/21642583.2021.2024099

Jian Luo, Bingyou Liu, Pan Yang, Xuan Fan

引用次数: 2

An intelligent approach of controlled variable selection for constrained process self-optimizing control 约束过程自寻优控制中受控变量选择的智能方法

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-01-12 DOI: 10.1080/21642583.2021.2024916

H. Su, Chenchen Zhou, Yi Cao, Shuang-hua Yang, Zuzhen Ji

{"title":"An intelligent approach of controlled variable selection for constrained process self-optimizing control","authors":"H. Su, Chenchen Zhou, Yi Cao, Shuang-hua Yang, Zuzhen Ji","doi":"10.1080/21642583.2021.2024916","DOIUrl":"https://doi.org/10.1080/21642583.2021.2024916","url":null,"abstract":"ABSTRACT Self-optimizing control (SOC) is a technique for selecting appropriate controlled variables (CVs) and maintaining them constant such that the plant runs at its best. Some tough challenges in this subject, such as how to select CVs when the active constraint set changes remains unsolved since the notion of SOC was presented. Previous work had some drawbacks such as structural complexity and control inaccuracy when dealing with constrained SOC problems due to the elaborate control structures or the limitation of local SOC. In order to overcome the deficiency of previous methods, this paper developed a constrained global SOC (cgSOC) approach to implement self-optimizing controlled variable selection and control structure design. The constrained variables that may change between inactive and active are represented as a nonlinear function of available measurement variables under optimal operations. The unknown function is then intelligently learnt over the whole operating region through neural network training. The difference between the nonlinear function and the actual constrained variables measured in real-time is then used as CVs. When the CVs are controlled at zero in real-time, near-optimal operation can be ensured globally whenever active constraint changes. The efficacy of the proposed approach is demonstrated through an evaporator case study.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48703847","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: 4

GAN-based clustering solution generation and fusion of diffusion 基于GAN的聚类解生成与扩散融合

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-01-12 DOI: 10.1080/21642583.2021.2024100

Wenming Cao, Zhiwen Yu, H. Wong

{"title":"GAN-based clustering solution generation and fusion of diffusion","authors":"Wenming Cao, Zhiwen Yu, H. Wong","doi":"10.1080/21642583.2021.2024100","DOIUrl":"https://doi.org/10.1080/21642583.2021.2024100","url":null,"abstract":"In this paper, we propose a framework to generate diverse clustering solutions and conduct solution retrieval to improve performance. Specifically, we first project unlabelled data from multiple domains into a shared space while preserving the respective semantics. This space allows that representations of samples in a hard domain are recovered by a linear combination of those of others in the easy domains. Meanwhile, a clustering algorithm is adopted to provide pseudo labels for a conditional generative adversarial network to synthesize representations that in turn promote the learning of the above space. Second, we conduct the joint learning of feature projection and partition matrices on batches of representations, where the former ones are considered as clustering solutions and input into another generative adversarial network to generate more solutions. Third, we utilize the fusion of diffusion to effectively retrieve and extract the knowledge in multiple solutions to obtain the final clustering. We perform comparative experiments against other methods on multiple benchmark data sets. Experimental results demonstrate the effectiveness and superiority of our proposed method.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41693096","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: 1

Nonlinear dynamic process monitoring using deep dynamic principal component analysis 基于深度动态主成分分析的非线性动态过程监测

IF 4.1

Systems Science & Control Engineering Pub Date : 2022-01-08 DOI: 10.1080/21642583.2021.2024915

Simin Li, Shuang-hua Yang, Yi Cao, Zuzhen Ji

{"title":"Nonlinear dynamic process monitoring using deep dynamic principal component analysis","authors":"Simin Li, Shuang-hua Yang, Yi Cao, Zuzhen Ji","doi":"10.1080/21642583.2021.2024915","DOIUrl":"https://doi.org/10.1080/21642583.2021.2024915","url":null,"abstract":"Data-driven method has gained its popularity in fault detection. Conventional methods are associated with one-single-layer process monitoring. Information extracted by such a method may not be sufficient to detect some faults for complicated process systems. Inspired by the deep learning conception, a multi-layer fault detection method, namely Deep Principal Component Analysis (DePCA) was proposed previously in the literature. DePCA has the capability to extract deep features for a process resulting in better fault detection performance. However, it assumes that the value of the variable at each moment is unrelated, which is not suitable for complex nonlinear dynamic system. To address the concerns, by adopting dynamic PCA to extract dynamic features, a new deep approach, namely Deep Dynamic Principal Component Analysis (DeDPCA), is proposed. In the new approach, both Dynamic feature and nonlinear feature can be extracted in different layers so that more process faults can be detected. A Tennessee Eastman process case study was then employed for application and validation of the DeDPCA, which indicates the proposed method is suitable for monitoring complex dynamic nonlinear processes.","PeriodicalId":46282,"journal":{"name":"Systems Science & Control Engineering","volume":null,"pages":null},"PeriodicalIF":4.1,"publicationDate":"2022-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43602054","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: 4