Pub Date : 2021-12-03DOI: 10.1109/ICICIP53388.2021.9642199
Erzhen Shang, Yang Gao, Yang Li, Bo Yu, Jiasen Sun, Yilin Jia, Cheng Zhong, Guoqiang Zhu, Xiuyu Zhang
A hybrid adaptive control scheme for quadrotor control system based on event-triggered mechanism is proposed for the trajectory tracking control problem of quadrotor UAV. The high-gain state observer is constructed to estimate the unmeasurable states, then the adaptive radial basis function neural networks (RBFNNs) dynamic surface control strategy is designed to achieve precise tracking control. The event-triggered mechanism is introduced, which is effective reduces the update frequency of the system control signal. The simulation results show that the proposed control scheme can achieve more accurate tracking performance than the traditional backstepping sliding mode control (BSMC) scheme without sacrificing the tracking performance of the control system.
{"title":"Event-Triggered Based Adaptive Dynamic Surface Control for a Class of Quadrotor UAVs*","authors":"Erzhen Shang, Yang Gao, Yang Li, Bo Yu, Jiasen Sun, Yilin Jia, Cheng Zhong, Guoqiang Zhu, Xiuyu Zhang","doi":"10.1109/ICICIP53388.2021.9642199","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642199","url":null,"abstract":"A hybrid adaptive control scheme for quadrotor control system based on event-triggered mechanism is proposed for the trajectory tracking control problem of quadrotor UAV. The high-gain state observer is constructed to estimate the unmeasurable states, then the adaptive radial basis function neural networks (RBFNNs) dynamic surface control strategy is designed to achieve precise tracking control. The event-triggered mechanism is introduced, which is effective reduces the update frequency of the system control signal. The simulation results show that the proposed control scheme can achieve more accurate tracking performance than the traditional backstepping sliding mode control (BSMC) scheme without sacrificing the tracking performance of the control system.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129845551","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}
In this paper, we investigate the exponential synchronization problem for a class of linear coupled dynamic complex networks. In a complex network system, it is difficult to achieve synchronization only by the coupling of the network itself without the controller. Based on the linear feedback method, this paper proposes a strategy to achieve global exponential stability of the general complex dynamic network in the target state by means of pinning control. Some nodes of the complex network are controlled to achieve the same state of all nodes of the complex network. In addition, the conditions of global exponential synchronization of the complex network are given, and the strict proof is given by using Lyapunov stability theory. Numerical analysis and simulation results are presented to demonstrate effectiveness of the criterion.
{"title":"On Pinning Synchronization of An Array of Linearly Coupled Dynamical Network","authors":"Wudai Liao, Haoran Chen, Jinhuan Chen, Chaochuan Zhang, Xiufen Xin, Xiaobo Han","doi":"10.1109/ICICIP53388.2021.9642181","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642181","url":null,"abstract":"In this paper, we investigate the exponential synchronization problem for a class of linear coupled dynamic complex networks. In a complex network system, it is difficult to achieve synchronization only by the coupling of the network itself without the controller. Based on the linear feedback method, this paper proposes a strategy to achieve global exponential stability of the general complex dynamic network in the target state by means of pinning control. Some nodes of the complex network are controlled to achieve the same state of all nodes of the complex network. In addition, the conditions of global exponential synchronization of the complex network are given, and the strict proof is given by using Lyapunov stability theory. Numerical analysis and simulation results are presented to demonstrate effectiveness of the criterion.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114496413","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}
Pub Date : 2021-12-03DOI: 10.1109/ICICIP53388.2021.9642163
Yanzhi Wu, Lu Liu
The optimal control problem is investigated for linear system with unknown dynamics in this paper. For linear system, adaptive dynamic programming (ADP) techniques and gradient descent method are combined to obtain an approximated optimal controller. We design ADP algorithms to calculate the system matrices of the linear system. Based on these calculated system matrices, a gradient descent algorithm is utilized to approximate the optimal feedback control gain. Finally, a numerical example is included for illustration.
{"title":"Optimal Control Problem for Linear System Based on Adaptive Dynamics Programming and Gradient Descent Method","authors":"Yanzhi Wu, Lu Liu","doi":"10.1109/ICICIP53388.2021.9642163","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642163","url":null,"abstract":"The optimal control problem is investigated for linear system with unknown dynamics in this paper. For linear system, adaptive dynamic programming (ADP) techniques and gradient descent method are combined to obtain an approximated optimal controller. We design ADP algorithms to calculate the system matrices of the linear system. Based on these calculated system matrices, a gradient descent algorithm is utilized to approximate the optimal feedback control gain. Finally, a numerical example is included for illustration.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"189 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122111026","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}
Aiming at the problem of tracking control system of the aircraft flight path angle, an adaptive discrete time dynamic surface control algorithm is proposed. Firstly, introducing the concept of discrete time system, the sampling signal form used is easy to suppress noise, and the impact of delay on the system is reduced through sampling. Afterwards, the dynamic surface control and the first-order digital low pass filter is introduced which making both controller and parameters easier and avoiding differential explosion in traditional backstepping method. Furthermorethe RBF Neural Network is introduced to approximate the unknown parameters and uncertain items in the system and the unknown interference part of the externa, which reduces the requirements on the system and structure. By using the Lyapunov function theory, it is proved that the closed-loop system is semi-globally ultimately uniformly bounded. Finally, simulation verification is performed and the results show that the proposed control algorithm can not only make the flight path angle track the reference trajectory, but also has a certain degree of robustness to unknown system parameters and unknown external interference.
{"title":"Adaptive Discrete Time Dynamic Surface Control for Aircraft Flight Path Angle with Unknown Disturbances","authors":"Huan He, Xiaodi Xu, Yilin Jia, Cheng Zhong, Guoqiang Zhu, Xiuyu Zhang","doi":"10.1109/ICICIP53388.2021.9642183","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642183","url":null,"abstract":"Aiming at the problem of tracking control system of the aircraft flight path angle, an adaptive discrete time dynamic surface control algorithm is proposed. Firstly, introducing the concept of discrete time system, the sampling signal form used is easy to suppress noise, and the impact of delay on the system is reduced through sampling. Afterwards, the dynamic surface control and the first-order digital low pass filter is introduced which making both controller and parameters easier and avoiding differential explosion in traditional backstepping method. Furthermorethe RBF Neural Network is introduced to approximate the unknown parameters and uncertain items in the system and the unknown interference part of the externa, which reduces the requirements on the system and structure. By using the Lyapunov function theory, it is proved that the closed-loop system is semi-globally ultimately uniformly bounded. Finally, simulation verification is performed and the results show that the proposed control algorithm can not only make the flight path angle track the reference trajectory, but also has a certain degree of robustness to unknown system parameters and unknown external interference.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115519497","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}
In order to improve the performance of deep reinforcement learning (DRL) algorithm in high-dimensional observation environments, we propose a new auxiliary task to learn representations to aggregate task-relevant information of observations. Inspired by Q-irrelevance abstraction, our auxiliary task trains a deep Q-network (DQN) to predict the true Q value distribution over all discrete actions. Then we use the output of DQN to train the encoder to discriminate states with different Q values. The encoder is used as the representation of proximal policy optimization (PPO). The resulting algorithm is called as Q-irrelevance Abstraction for Reinforcement Learning (QIARL). After training, the encoder can aggregate states with similar Q value distributions together for any policy and any action. Thus the encoder can encode the important information that is relevant to reinforcement learning task. We test QIARL in four Procgen environments compare with PPO, A2C and Rainbow. The experimental results show QIARL outperforms the other three algorithms.
{"title":"Learning Representation with Q-irrelevance Abstraction for Reinforcement Learning","authors":"Shuai Hao, Luntong Li, Minsong Liu, Yuanheng Zhu, Dongbin Zhao","doi":"10.1109/ICICIP53388.2021.9642160","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642160","url":null,"abstract":"In order to improve the performance of deep reinforcement learning (DRL) algorithm in high-dimensional observation environments, we propose a new auxiliary task to learn representations to aggregate task-relevant information of observations. Inspired by Q-irrelevance abstraction, our auxiliary task trains a deep Q-network (DQN) to predict the true Q value distribution over all discrete actions. Then we use the output of DQN to train the encoder to discriminate states with different Q values. The encoder is used as the representation of proximal policy optimization (PPO). The resulting algorithm is called as Q-irrelevance Abstraction for Reinforcement Learning (QIARL). After training, the encoder can aggregate states with similar Q value distributions together for any policy and any action. Thus the encoder can encode the important information that is relevant to reinforcement learning task. We test QIARL in four Procgen environments compare with PPO, A2C and Rainbow. The experimental results show QIARL outperforms the other three algorithms.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"30 52","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120837830","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}
Pub Date : 2021-12-03DOI: 10.1109/ICICIP53388.2021.9642218
Yuting Zhang, Hongwei Zhang, Honghai Liu
Sound source localization finds its applications in various scenarios, such as video conferences, human-robot interaction, intelligent robotics, transportation, fault detection and medical treatment. To overcome the conflict of low frequency resolution issue for the microphone array with small aperture and spatial aliasing issue caused by the microphone array with large aperture, this paper adopts a uniform concentric circular array topology and proposes an improved method based on delay and sum beamforming algorithm to realize the multiple sound sources localization. Experimental results illustrate the effectiveness of the proposed algorithm.
{"title":"An Improved Multiple Sound Source Localization Method Using a Uniform Concentric Circular Microphone Array","authors":"Yuting Zhang, Hongwei Zhang, Honghai Liu","doi":"10.1109/ICICIP53388.2021.9642218","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642218","url":null,"abstract":"Sound source localization finds its applications in various scenarios, such as video conferences, human-robot interaction, intelligent robotics, transportation, fault detection and medical treatment. To overcome the conflict of low frequency resolution issue for the microphone array with small aperture and spatial aliasing issue caused by the microphone array with large aperture, this paper adopts a uniform concentric circular array topology and proposes an improved method based on delay and sum beamforming algorithm to realize the multiple sound sources localization. Experimental results illustrate the effectiveness of the proposed algorithm.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131995306","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}
Pub Date : 2021-12-03DOI: 10.1109/ICICIP53388.2021.9642177
Yang Shi, Guoqian Liu, Jie Wang, Jiazheng Zhang, Jian Li, Dimitrios Gerontitis
In this paper, an advanced discrete generalized-neurodynamic (A-DGND) model is proposed to solve discrete time-variant augmented Sylvester equation (DTV-ASME) with perturbation suppression. Firstly, we present the discrete time-variant augmented Sylvester matrix equation that can be transformed into a simple matrix-vector problem. Secondly, in the continuous-time environment, for solving the continuous time-variant augmented Sylvester matrix equation (CTV-ASME), an advanced continuous generalized-neurodynamic (A-CGND) model is obtained. Then, based on the four-step discretization formula, an A-DGND model is proposed by discretizing the A-CGND model for solving DTV-ASME with perturbation suppression. Finally, according to the numerical experiment results, the effectiveness and robustness of A-DGND model for solving DTVASME are verified.
{"title":"Advanced Discrete Generalized-Neurodynamic Model Applied to Solve Discrete Time-Variant Augmented Sylvester Equation with Perturbation Suppression","authors":"Yang Shi, Guoqian Liu, Jie Wang, Jiazheng Zhang, Jian Li, Dimitrios Gerontitis","doi":"10.1109/ICICIP53388.2021.9642177","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642177","url":null,"abstract":"In this paper, an advanced discrete generalized-neurodynamic (A-DGND) model is proposed to solve discrete time-variant augmented Sylvester equation (DTV-ASME) with perturbation suppression. Firstly, we present the discrete time-variant augmented Sylvester matrix equation that can be transformed into a simple matrix-vector problem. Secondly, in the continuous-time environment, for solving the continuous time-variant augmented Sylvester matrix equation (CTV-ASME), an advanced continuous generalized-neurodynamic (A-CGND) model is obtained. Then, based on the four-step discretization formula, an A-DGND model is proposed by discretizing the A-CGND model for solving DTV-ASME with perturbation suppression. Finally, according to the numerical experiment results, the effectiveness and robustness of A-DGND model for solving DTVASME are verified.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133229581","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}
Pub Date : 2021-12-03DOI: 10.1109/ICICIP53388.2021.9642157
Shanwen Guan, Xiao-peng Luo
Due to the widespread use of robotics in recent years, accurate localization and tracking have become active research topic. As a low-power wireless communication and sensing technology, Ultra-wideband (UWB) has relatively accurate positioning and sensing capabilities, and has broad application prospects for precise positioning and other fields. But due to the complex environment and obstacles, the non-line-of-sight(NLOS) error generated by it will be severe. It seriously affects the position estimation of the system, resulting in low positioning accuracy and poor robustness. Improving the accuracy and robustness of the UWB positioning technology in a complex environment, a method based on the fusion of UWB and IMU data, which effectively combines global positioning and local positioning, positioning, using LSTM neural network algorithm processes the IMU data, and The EKF algorithm merge the IMU and UWB. Compared with the traditional UWB positioning method, this method can effectively suppress Control the influence of NLOS interference in positioning estimation and improve the accuracy and robustness of the positioning system.
{"title":"Fusing Ultra-wideband Range Measurements with IMU for Mobile Robot Localization","authors":"Shanwen Guan, Xiao-peng Luo","doi":"10.1109/ICICIP53388.2021.9642157","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642157","url":null,"abstract":"Due to the widespread use of robotics in recent years, accurate localization and tracking have become active research topic. As a low-power wireless communication and sensing technology, Ultra-wideband (UWB) has relatively accurate positioning and sensing capabilities, and has broad application prospects for precise positioning and other fields. But due to the complex environment and obstacles, the non-line-of-sight(NLOS) error generated by it will be severe. It seriously affects the position estimation of the system, resulting in low positioning accuracy and poor robustness. Improving the accuracy and robustness of the UWB positioning technology in a complex environment, a method based on the fusion of UWB and IMU data, which effectively combines global positioning and local positioning, positioning, using LSTM neural network algorithm processes the IMU data, and The EKF algorithm merge the IMU and UWB. Compared with the traditional UWB positioning method, this method can effectively suppress Control the influence of NLOS interference in positioning estimation and improve the accuracy and robustness of the positioning system.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128622238","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}
Pub Date : 2021-12-03DOI: 10.1109/ICICIP53388.2021.9642197
Bai-gang Mi, Yi Fan, Yu Sun
With the coming of the new information epoch, the quantity of aeronautical intelligence information increases exponentially. In the effort to improve the efficiency and security of the aeronautical industry, it has become a key factor to determine how to acquire, extract, and represent knowledge from a large set of aeronautical intelligence information and forming a knowledge base to guide the intelligent development of aeronautical intelligence information management work. In order to promote integration and sharing of information regarding aeronautical intelligence information domain and obtain the deeper information and knowledge, the construction and application of NOTAM (Notice to Air Men) ontology are developed based on text mining. The NOTAM text is collected and analyzed by web crawler technology. Combined with the professional term in specific domain, we successfully extract the key concepts of the ontology by TF-IDF (term frequency-inverse document frequency) text features. Furthermore, the hierarchical and non-hierarchical relations are automatically extracted by text cluster methods and specific domain knowledge system. Finally, the ontology editor—protégé helps us to visualize the key concepts and the relations in the ontology. Meanwhile, a NOTAM text is instanced to verify the efficiency and precision of the NOTAM ontology.
随着新信息时代的到来，航空情报信息量呈指数级增长。如何从海量的航空情报信息中获取、提取和表示知识，形成知识库，指导航空情报信息管理工作智能化发展，已成为提高航空工业效率和安全性的关键因素。为了促进航空情报信息领域信息的整合与共享，获取更深入的信息和知识，基于文本挖掘技术开发了NOTAM (Notice to Air Men)本体的构建与应用。利用网络爬虫技术对NOTAM文本进行采集和分析。结合特定领域的专业术语，利用TF-IDF (term frequency-inverse document frequency)文本特征成功提取出本体的关键概念。在此基础上，利用文本聚类方法和特定的领域知识系统，自动提取层次关系和非层次关系。最后，本体编辑器proprosamug帮助我们将本体中的关键概念和关系可视化。同时，实例化了一个NOTAM文本，验证了NOTAM本体的效率和精度。
{"title":"Ontology Intelligent Construction Technology for NOTAM","authors":"Bai-gang Mi, Yi Fan, Yu Sun","doi":"10.1109/ICICIP53388.2021.9642197","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642197","url":null,"abstract":"With the coming of the new information epoch, the quantity of aeronautical intelligence information increases exponentially. In the effort to improve the efficiency and security of the aeronautical industry, it has become a key factor to determine how to acquire, extract, and represent knowledge from a large set of aeronautical intelligence information and forming a knowledge base to guide the intelligent development of aeronautical intelligence information management work. In order to promote integration and sharing of information regarding aeronautical intelligence information domain and obtain the deeper information and knowledge, the construction and application of NOTAM (Notice to Air Men) ontology are developed based on text mining. The NOTAM text is collected and analyzed by web crawler technology. Combined with the professional term in specific domain, we successfully extract the key concepts of the ontology by TF-IDF (term frequency-inverse document frequency) text features. Furthermore, the hierarchical and non-hierarchical relations are automatically extracted by text cluster methods and specific domain knowledge system. Finally, the ontology editor—protégé helps us to visualize the key concepts and the relations in the ontology. Meanwhile, a NOTAM text is instanced to verify the efficiency and precision of the NOTAM ontology.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128632538","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}
Regenerative braking can effectively improve fuel consumption for hybrid electric vehicles, and it is a critical technology related to the multi-objective control situation, which is used to realize vehicle braking safety, the energy of braking recovery, and braking stability. Therefore, this paper put forward an adaptive fuzzy control (AFC) method for energy recovery in electric vehicles, mainly for a regenerative braking system. In particular, adaptive control is designed for estimating the road condition. The fuzzy logic control is proposed based on the braking strength of the vehicle, the battery state of charge, and vehicle speed. Combine the mentioned methods, an electric vehicle model is established in the Simulink environment to verify the applicability of the proposed control algorithm.
{"title":"Design and Implementation of Braking Control for Hybrid Electric Vehicles","authors":"Peng Mei, Shichun Yang, Bing-rui Xu, Kangkang Sun, Chao Zhang","doi":"10.1109/ICICIP53388.2021.9642191","DOIUrl":"https://doi.org/10.1109/ICICIP53388.2021.9642191","url":null,"abstract":"Regenerative braking can effectively improve fuel consumption for hybrid electric vehicles, and it is a critical technology related to the multi-objective control situation, which is used to realize vehicle braking safety, the energy of braking recovery, and braking stability. Therefore, this paper put forward an adaptive fuzzy control (AFC) method for energy recovery in electric vehicles, mainly for a regenerative braking system. In particular, adaptive control is designed for estimating the road condition. The fuzzy logic control is proposed based on the braking strength of the vehicle, the battery state of charge, and vehicle speed. Combine the mentioned methods, an electric vehicle model is established in the Simulink environment to verify the applicability of the proposed control algorithm.","PeriodicalId":435799,"journal":{"name":"2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114666533","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}
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