Complex engineering systems (Alhambra, Calif.)最新文献_第3页

How to deal with the complexity in robotic systems? 如何处理机器人系统的复杂性?

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.33

H. Karimi

引用次数: 0

Comparison of battery modeling regression methods for application to unmanned aerial vehicles 电池建模回归方法在无人机上的应用比较

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.03

Jon Ander Martin, Justin N. Ouwerkerk, Anthony P. Lamping, Kelly Cohen

{"title":"Comparison of battery modeling regression methods for application to unmanned aerial vehicles","authors":"Jon Ander Martin, Justin N. Ouwerkerk, Anthony P. Lamping, Kelly Cohen","doi":"10.20517/ces.2022.03","DOIUrl":"https://doi.org/10.20517/ces.2022.03","url":null,"abstract":"An effective battery prognostics method is fundamental for any application in which batteries have a critical role, such as in unmanned aerial vehicles. Given the batteries' variable nature, effectively predicting their End of Discharge or End of Life can become a difficult task. Therefore, developing an accurate and efficient model becomes a key step of this problem. The framework provided by traditional modeling techniques usually leads to inaccurate results, so newer state-of-the-art methodologies are needed to successfully build a model from a dataset. This paper compares the accuracy and time performance of three existing methods: a maximum likelihood optimal Support Vector Machine, a Bayesian Relevance Vector Machine, and a Fuzzy Inference System. Through this research, we aim to implement a real-time battery prognostics system in an Unmanned Aerial Vehicle. The three methods are used to model a Lithium-ion (Li-ion) battery's discharge curve while accounting for the State of Health of the battery for the estimation of voltage. %This paper compares the accuracy and time performance of a maximum likelihood optimal Support Vector Machine, a Bayesian Relevance Vector Machine, and a Fuzzy Inference System for the modeling of Lithium-ion (Li-ion) batteries' discharge curve. Moreover, the model accounts for the State of Health of the battery for the estimation of voltage. We show that the three methodologies are valid for the modeling of the discharge curve with similar accuracy values. The Relevance Vector Machine proves to be the most computationally efficient method.","PeriodicalId":72652,"journal":{"name":"Complex engineering systems (Alhambra, Calif.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67656938","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: 2

A comparative study of energy management systems under connected driving: Cooperative car-following case 网联驾驶下能源管理系统的比较研究——以协同跟车为例

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.06

Ozan Yazar, S. Coskun, Feng Zhang, Lin Li

{"title":"A comparative study of energy management systems under connected driving: Cooperative car-following case","authors":"Ozan Yazar, S. Coskun, Feng Zhang, Lin Li","doi":"10.20517/ces.2022.06","DOIUrl":"https://doi.org/10.20517/ces.2022.06","url":null,"abstract":"In this work, we propose connected energy management systems for a cooperative hybrid electric vehicle (HEV) platoon. To this end, cooperative driving scenarios are established under different car-following behavior models using connected and automated vehicles technology, leading to a cooperative cruise control system (CACC) that explores the energy-saving potentials of HEVs. As a real-time energy management control, an equivalent consumption minimization strategy (ECMS) is utilized, wherein global energy-saving is achieved to promote environment-friendly mobility. The HEVs cooperatively communicate and exchange state information and control decisions with each other by sixth-generation vehicle-to-everything (6G-V2X) communications. In this study, three different car-following behavior models are used: intelligent driver model (IDM), Gazis–Herman–Rothery (GHR) model, and optimal velocity model (OVM). Adopting cooperative driving of six Toyota Prius HEV platoon scenarios, simulations under New European Driving Cycle (NEDC), Worldwide Harmonized Light Vehicle Test Procedure (WLTP), and Highway Fuel Economy Test (HWFET), as well as human-in-the-loop (HIL) experiments, are carried out via MATLAB/Simulink/dSPACE for cooperative HEV platooning control via different car-following-linked-vehicle scenarios. The CACC-ECMS scheme is assessed for HEV energy management via 6G-V2X broadcasting, and it is found that the proposed strategy exhibits improvements in vehicular driving performance. The IDM-based CACC-ECMS is an energy-efficient strategy for the platoon that saves: (i) 8.29% fuel compared to the GHR-based CACC-ECMS and 10.47% fuel compared to the OVM-based CACC-ECMS under NEDC; (ii) 7.47% fuel compared to the GHR-based CACC-ECMS and 11% fuel compared to the OVM-based CACC-ECMS under WLTP; (iii) 3.62% fuel compared to the GHR-based CACC-ECMS and 4.22% fuel compared to the OVM-based CACC-ECMS under HWFET; and (iv) 11.05% fuel compared to the GHR-based CACC-ECMS and 18.26% fuel compared to the OVM-based CACC-ECMS under HIL.","PeriodicalId":72652,"journal":{"name":"Complex engineering systems (Alhambra, Calif.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67656946","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

Sampled-based bipartite tracking consensus of nonlinear multiagents subject to input saturation 输入饱和非线性多智能体基于采样的二部跟踪一致性

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.08

Luyang Yu, Ying-liu Cui, Z. Lu, Yurong Liu

引用次数: 3

Reinforcement learning-based control for offshore crane load-landing operations 基于强化学习的海上起重机装卸作业控制

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.28

Khaled Said Ahmed Maamoun, H. Karimi

{"title":"Reinforcement learning-based control for offshore crane load-landing operations","authors":"Khaled Said Ahmed Maamoun, H. Karimi","doi":"10.20517/ces.2022.28","DOIUrl":"https://doi.org/10.20517/ces.2022.28","url":null,"abstract":"Offshore crane operations are frequently carried out under adverse weather conditions. While offshore cranes attempt to finish the load-landing or lifting operation, the impact between the loads and the vessels is critical, as it can cause serious injuries and extensive damage. Multiple offshore crane operations, including load-landing operations, have used reinforcement learning (RL) to control their activities. In this paper, the Q-learning algorithm is used to develop optimal control sequences for the offshore crane’s actuators to minimize the impact velocity between the crane’s load and the moving vessel. To expand the RL environment, a mathematical model is constructed for the dynamical analysis utilizing the Denavit–Hartenberg (DH) technique and the Lagrange approach. The Double Q-learning algorithm is used to locate the bias that is common in Q-learning algorithms. The average return feature is studied to assess the performance of the Q-learning algorithm. Furthermore, the trained control sequence was tested on a separate sample of episodes, and the hypothesis that, unlike supervised learning, reinforcement learning cannot have a global optimal control sequence but only a local one, was confirmed in this application domain.","PeriodicalId":72652,"journal":{"name":"Complex engineering systems (Alhambra, Calif.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67657436","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

Explainable fuzzy cluster-based regression algorithm with gradient descent learning 基于梯度下降学习的可解释模糊聚类回归算法

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.14

Javier Viaña, Stephan Ralescu, A. Ralescu, Kelly Cohen, V. Kreinovich

{"title":"Explainable fuzzy cluster-based regression algorithm with gradient descent learning","authors":"Javier Viaña, Stephan Ralescu, A. Ralescu, Kelly Cohen, V. Kreinovich","doi":"10.20517/ces.2022.14","DOIUrl":"https://doi.org/10.20517/ces.2022.14","url":null,"abstract":"We propose an algorithm for n-dimensional regression problems with continuous variables. Its main property is explainability, which we identify as the ability to understand the algorithm’s decisions from a human perspective. This has been achieved thanks to the simplicity of the architecture, the lack of hidden layers (as opposed to deep neural networks used for this same task) and the linguistic nature of its fuzzy inference system. First, the algorithm divides the joint input-output space into clusters that are subsequently approximated using linear functions. Then, we fit a Cauchy membership function to each cluster, therefore identifying them as fuzzy sets. The prediction of each linear regression is merged using a Takagi-Sugeno-Kang approach to generate the prediction of the model. Finally, the parameters of the algorithm (those from the linear functions and Cauchy membership functions) are fine-tuned using Gradient Descent optimization. In order to validate this algorithm, we considered three different scenarios: The first two are simple one-input and two-input problems with artificial data, which allow visual inspection of the results. In the third scenario we use real data for the prediction of the power generated by a Combined Cycle Power Plant. The results obtained in this last problem (3.513 RMSE and 2.649 MAE) outperform the state of the art (3.787 RMSE and 2.818 MAE).","PeriodicalId":72652,"journal":{"name":"Complex engineering systems (Alhambra, Calif.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67657028","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

A feedforward air-conditioning energy management method for high-speed railway sleeper compartment 高速铁路卧铺车厢前馈空调能量管理方法

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2021.14

Zhuoyun Li, Jicheng Chen, Jinghuai Deng

引用次数: 1

PEM fuel cell system to extend the stack life based on a PID-PSO controller design 基于PID-PSO控制器设计的PEM燃料电池系统延长堆寿命

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.02

J. Ghasemi, S. M. Rakhtala, Jalal Rasekhi, Seyed Reza Dokhtala

{"title":"PEM fuel cell system to extend the stack life based on a PID-PSO controller design","authors":"J. Ghasemi, S. M. Rakhtala, Jalal Rasekhi, Seyed Reza Dokhtala","doi":"10.20517/ces.2022.02","DOIUrl":"https://doi.org/10.20517/ces.2022.02","url":null,"abstract":"In this paper, the nonlinear model of polymer exchange membrane (PEM) fuel cell system is first extracted and then tested and evaluated for various temperatures and pressures. With the severe nonlinear characteristics of the PEM fuel cell system, using the proportional-integral-derivative (PID) controller for the linear model of the PEM fuel cell system could not guarantee robust control under parametric uncertainty and severe load fluctuations. The use of a linear model-based controller increases the pressure in both the anode and cathode areas, which in turn induces a high pressure difference across the polymer membrane, thus reducing the lifespan of the fuel cell. The proposed method uses the particle swarm optimization (PSO) algorithm, taking into account practical parameters, to design a PID controller for a nonlinear model of the fuel cell. Comparison of the results obtained from the conventional PID controller and the proposed PID-PSO structure shows that PID-PSO can desirably guarantee the specifications of overshoot, transient time, and settling time for a defined pressure difference across the anode and cathode plates.","PeriodicalId":72652,"journal":{"name":"Complex engineering systems (Alhambra, Calif.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67656929","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: 2

An improved A star algorithm for wheeled robots path planning with jump points search and pruning method 基于跳点搜索和剪枝的轮式机器人路径规划改进A星算法

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2022.12

Hongqian Huang, Yanzhou Li, Qing Bai

引用次数: 4

Backstepping-based state estimation for a class of stochastic nonlinear systems 一类随机非线性系统的状态估计

Complex engineering systems (Alhambra, Calif.) Pub Date : 2022-01-01 DOI: 10.20517/ces.2021.13

Xin Yin, Qichun Zhang

引用次数: 7