{"title":"Adaptive consensus control of nonlinear fractional-order multi-agent systems with a leader","authors":"Jiajun Yang, Wei Luo, Hao Yi, Wenqiang Xu","doi":"10.1109/ISASS.2019.8757753","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757753","url":null,"abstract":"In this manuscript, we investigate the adaptive consensus control problem of nonlinear fractional-order multi-agent systems with a leader. To solve the problem, an adaptive control protocol based on neighboring agent state information under undirected communication topology is presented. Then, according to the Lyapunov stability theory of the fractional order system, Barbalat lemma, Kronecker product and Schur complement lemma, the sufficient conditions for the researched systems to be consistent are obtained. Finally, the corresponding numerical simulation is given to verify the correctness of the obtained results.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131290573","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}
{"title":"Research on Path Planning of Mobile Robot Based on Improved A* in Special Environment","authors":"Ren Yiyue, Xiaoru Song, Gao Song","doi":"10.1109/ISASS.2019.8757721","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757721","url":null,"abstract":"Aiming at the problems of A* algorithm in a large environment with density of obstacles, such as large memory overheads, long calculation times, an novel method based on the fusion of static weight method and jump point search is proposed in this paper. Static weight method improves heuristic function, then the search space is limited and brute force search is reduced. Jump point search filters key points, then unnecessary nodes are reduced and search speed is accelerated The experimental results demonstrate that compared with traditional A* algorithm, the number of invisited nodes is reduced, and the search speed is accelerated. Therefore, the proposed algorithm can meet the requirements of fast path finding in special environments.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133684274","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}
{"title":"Distributed fault-tolerant consensus control for uncertain nonlinear multi-agent systems","authors":"Zhijie Li, C. Hua, Kuo Li","doi":"10.1109/ISASS.2019.8757715","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757715","url":null,"abstract":"This paper investigates a distributed fault-tolerant consensus control problem for a class of uncertain nonlinear multi-agent systems with actuator faults and process faults. Most of the existing works about tolerant control for multi-agent systems solely consider actuator faults. Different from the works, the proposed faults in this paper are more comprehensive subjecting to both actuator faults and process faults. For the un-certain nonlinear term, we propose a less conservative Lipschitz condition. Based on the Lyapunov stability theory, it is proved strictly that the proposed controllers make the followers reach consensus with the leader. Finally, a simulation example is given to verify the effectiveness of the theoretical result.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132745347","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}
{"title":"A Multi-AUV Searching Algorithm Based on Neuron Network with Obstacle","authors":"S. Lv, Yakun Zhu","doi":"10.1109/ISASS.2019.8757793","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757793","url":null,"abstract":"In this paper, a region search algorithm based on bio-inspired neural network is proposed, which can be used for AUVs to perform target search tasks in underwater regions with obstacles. Compared to neuron cells, the search area is divided into several discrete sub-areas. Adjacent neurons have synaptic connections and can transmit excitatory action. In order to avoid collisions during the search process, the obstacles and AUVs involved in search tasks are introduced as inhibitory sources of excitation into the neural network by constructing a neuronal excitation delivery model. By constructing hypothetical targets and introducing them into the neural network as stimulating sources of excitation, the AUVs are guided to quickly search for areas where the target is likely to exist, thereby they can efficiently completing the search tasks. Finally, the corresponding simulation results are given in order to prove the effectiveness of the search algorithm.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115652992","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}
{"title":"Robust Stability for Uncertain Fuzzy Systems with Time-delay Based on Sampled-Data Control","authors":"Chao Ge, Ganlei Zhang, Jiaping Tian, Hanxiao Zhao","doi":"10.1109/ISASS.2019.8757754","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757754","url":null,"abstract":"In this paper, we address the robust stability for un-certain fuzzy systems with time-varying delays based on sampled-data control. By developing some new terms, an improved piecewise Lyapunov-Krasovskii functional (LKF) is constructed to take full advantage of characteristic about real sampling pattern. Furthermore, some relaxed matrices proposed in the LKF are not necessarily positive definite. By using the LKF and Free-Matrix-Based (FMB) integral inequality, some sufficient criteria are established to ensure the stability of fuzzy systems and reduce the influence of external disturbance with an $mathcal{H}_{infty}$ norm bound. Then, the memory sampled-data controller can be derived by solving a group of linear matrix inequalities (LMIs) with the maximal sampling period. Finally, a numerical example is given to demonstrate the benefits and the superiority of the approach proposed.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124016533","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}
{"title":"Robust stabilization for constrained switched positive linear systems with mode-dependent average dwell time","authors":"Jinjin Liu, Chunyue Song","doi":"10.1109/ISASS.2019.8757702","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757702","url":null,"abstract":"In this paper, robust stabilization problems of constrained switched linear systems with mode-dependent average dwell time are considered via output-feedback. First, we focus on the robust stabilization by decomposing control gain matrix. Second, constrained controllers such that the closed-loop system is stable and positive. Also, the conditions we obtained are described as linear programming. Finally, validity of the proposed method is shown by a numerical example.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122677167","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}
{"title":"Human-object Interaction Recognition Using Multitask Neural Network","authors":"W. Yan, Yue Gao, Qiming Liu","doi":"10.1109/ISASS.2019.8757767","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757767","url":null,"abstract":"Human behavior recognition is a popular research area in the field of computer vision and has been studied due to its important applications such as visual surveillance and video retrieval. In this paper, we propose a new approach for recognizing human-object interaction actions based on multitask 2D convolutional neural network, which combines human body motion, human hand motion and object recognition network. By using RGBD camera and digital gloves, refined recognition of human body and hand movements are collected and learned. In addition, a new object recognition network based on YOLOv3 is introduced which increases the accuracy of predicting human-object interaction labels. We designed eight representative actions and built our own data set containing body and accurate hand motions. In our experiment, the accuracy of recognizing interactive actions reached 93%, which shows the correctness and effectiveness of the multitasking framework we propose.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127232440","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}
{"title":"Asynchronous Localization with Stratification Effect for Underwater Target: A Reinforcement Learning-based Approach","authors":"Yadi Gong, Xin Li, Jing Yan, Xiaoyuan Luo","doi":"10.1109/ISASS.2019.8757772","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757772","url":null,"abstract":"In this paper, we are concerned with the localization of underwater target under the asynchronous clock and stratification effect. A network architecture is established that comprises of surface buoys, sensor nodes and the target. Sensor nodes act as anchor nodes and communicate with target. With the collected localization messages, the relationship of time differences and propagation delay is established. Then the reinforcement learning-based approach is designed to solve the localization optimization problem. The value iteration process is given to determine the optimal policy. Finally, simulation results are presented to show the effectiveness of the proposed method.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126854345","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}
{"title":"Takagi-Sugeno Fuzzy-based Kalman Filter Observer for Vehicle Side-slip Angle Estimation and Lateral Stability Control","authors":"Liqin Zhang, Boyuan Li, H. Du, Baogang Zhang","doi":"10.1109/ISASS.2019.8757751","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757751","url":null,"abstract":"In current literature, the side-slip angle estimation has been extensively focused due to the importance of the side-slip angle information on the vehicle system control. In this study, the innovative Kalman filter observer for side-slip angle is proposed based on the Takagi-Sugeno (T-S) fuzzy modeling of vehicle non-linear lateral dynamics. Then based on the estimated side-slip angle, the fuzzy logic direct yaw moment controller is proposed to improve the vehicle performance. Finally, simulation results are presented to verify the proposed estimator and controller.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121630876","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}