{"title":"Event-triggered Control of Positive Switched Systems Based on Linear Programming","authors":"Lai-You Liu, Junfeng Zhang, Yu Shao, Miao Li","doi":"10.1109/ISASS.2019.8757720","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757720","url":null,"abstract":"This paper investigates the problem of event-triggered control for positive switched systems without/with input saturation. A 1-norm based event-triggered mechanism is established for positive switched systems. Using a gain matrix decomposition technique, an event-triggered controller is designed for the systems without input saturation. The saturation term in the saturation systems is transformed into an interval form under the event-triggered mechanism. Then, the upper and lower bound of the saturation systems matrix are obtained. An event-triggered controller is designed to guarantee the positivity of the lower bound closed-loop systems and the stability of the upper bound closed-loop systems in the saturation systems. Meanwhile, a cone attraction domain is constructed and a cone attraction domain gain matrix design approach is proposed. All presented conditions can be formulated into linear programming. Compared with existing results, the event-triggered control is more practical and efficient. Finally, a simulation example is provided to illustrate the validity of the design.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128436114","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 Simple Conceptor Model for Hand-written-digit Recognition","authors":"Wenqiang Xu, Xiumin Li, Hao Yi, Z. Deng","doi":"10.1109/ISASS.2019.8757783","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757783","url":null,"abstract":"Traditional recognitions of the MNIST hand-written-digits need vast amounts of datasets to assure high accuracy based on artificial neural networks (ANNs). In this paper, we present a simple preprocessing method for image classification. Firstly, the image pixels are converted into spike streams by using the Poisson distribution method. Similar as the integration of synaptic current in brain, spike or binary streams are integrated into continuous signals which are used to feed into the input layer of the conceptor network. The conceptor network is a recurrent neural network used to generate high-dimensional dynamic information. We use the MNIST database to investigate the computational performance of this model. Our results show that this method can achieve high recognition accuracy with much smaller training samples (6000 in this model V.S. 60000 in traditional other methods). Note that in this model, information for each image is decoded into a continuous sequence and fully analyzed through the conceptor network. Therefore, the number of training samples can be remarkably reduced.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116375027","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}
Hao Yi, Xiumin Li, Wenqiang Xu, Z. Deng, Jiajun Yang
{"title":"Pattern recognition of a spiking neural network based on visual motion model","authors":"Hao Yi, Xiumin Li, Wenqiang Xu, Z. Deng, Jiajun Yang","doi":"10.1109/ISASS.2019.8757738","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757738","url":null,"abstract":"With the rapid development of artificial intelligence, deep learning which has been broadly applied on the image processing, pattern recognition and data mining. However, it requires huge amounts of data and computing power. As we all know, the human brain is very complex but effective with much lower energy consumption. It is of great significance to process information with reference to the brain processing mechanism which not only helps us to understand how the brain works, but also can build smart chips with lower power consumption. In this paper, images preprocessed by the visual motion model and mapped into the V2 layer with different orientations, and then, we train the connection between V2 and output by supervised STDP rule. The results show that we can achieve the same recognition accuracy with fewer training samples, which contributed by the visual model preprocessing. The visual preprocess can amplify the spatiotemporal information and highlight the feature of images.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131232249","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 Power Control in D2D-Enabled Vehicular Communication Network","authors":"Yuan-ai Xie, Zhixin Liu, K. Ma, Yazhou Yuan","doi":"10.1109/ISASS.2019.8757748","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757748","url":null,"abstract":"The power control scheme is investigated for device-to-device-enabled vehicular communications (D2D-V) system in this paper. The D2D-V system is underlaid in cellular network, where one cellular uplink and multiple D2D-V links share a common channel. To pursue a fine D2D-V system, the sum rate of all D2D-V links is maximized, and the cochannel cellular link reliability is ensured by the cellular user (CU) interference constraint. However, the channel is time-varying and with high uncertainty, especially in the high mobility vehicular environment. To make the power control scheme be more robust against the channel fluctuations, the CU interference probability constraint is introduced, and it is transformed into deterministic one by Bernstein approximation since the probabilistic constraint is intractable. The deterministic constraint is reformulated as a separable structure for a more efficient solution. Besides, the nonconvex problem whose objective function involves the nonconvex logarithmic form, is transformed into a convex one by successive convex approximation method. After that, a distributed robust power control algorithm is proposed to achieve the optimal solution. Numerical simulations are performed to evaluate the performance of the proposed scheme and demonstrate velocity impacts on system performance when a high mobility vehicular environment is considered.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115117455","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":"Accurate Initialization Method for Monocular Visual-Inertial SLAM","authors":"Abderraouf Amrani, Hesheng Wang","doi":"10.1109/ISASS.2019.8757790","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757790","url":null,"abstract":"This In robotics, visual-inertial sensor fusion has become one of the most active research topics; optimization-based fusion approaches have gone beyond filtering approaches in terms of robustness and accuracy. For the optimization-based visual-inertial Simultaneous Localization and Mapping (SLAM), accurate initialization is essential for this nonlinear system which requires an accurate estimation of the initial states (Inertial Measurement Unit (IMU) biases, scale, gravity, and velocity). Therefore, our goal is to propose a more robust initialization method. First, we estimate the gyroscope bias, initial scale, and gravity. Then, we use the gravity magnitude to refine the gravity direction by minimizing the error state on the tangent space of the estimated gravity vector. After that, we estimate the accelerometer bias separately from gravity. Finally, based on the condition number and convergence process, we propose a robust and automatic termination criterion to indicate when the initialization is successfully achieved. Additionally, we use all the initial estimated values to initialize a visual-inertial SLAM system. We test our initialization method with different sequences of the public EuRoC dataset, and real-time hand-held experiment in indoor and outdoor environments. The results demonstrated good performance of both the estimated initial state and the automatic termination criterion. They also illustrated that the estimated gravity converges within a short time interval using the refinement approach.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117064363","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 Simple Control Method of Single-Link Flexible Manipulators","authors":"Chenglin Zhang, Tong Yang, Ning Sun, Jianyi Zhang","doi":"10.1109/ISASS.2019.8757711","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757711","url":null,"abstract":"Flexible manipulators with high-speed, high-load, and low-cost arise with the requirement of lightweight manipulators in aerospace, construction, manufacturing industry, etc. Lightweight flexible links make manipulators more feasible in many ways. However, their dynamic modeling and controller design are quite complex. Firstly we illustrate the model of single-link flexible manipulators. Then, by analyzing the manipulator energy, a nonlinear controller is designed, which can effectively control the system, that is, to make the rotation angle of manipulators rotate to a given angle while suppressing the vibration of manipulators. Furthermore, through rigorous and detailed theoretical analysis, it is concluded that the closed-loop system is asymptotically stable. Finally, we utilize some simulations to validate the control performance of the controller.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114376588","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}
Jionghong Gu, Cailian Chen, Shanying Zhu, Jianping He
{"title":"Efficient Error Packet Recovery without Redundant Bytes for IEEE 802.15.4 Protocol","authors":"Jionghong Gu, Cailian Chen, Shanying Zhu, Jianping He","doi":"10.1109/ISASS.2019.8757787","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757787","url":null,"abstract":"Packet corruption is inevitable in wireless sensor networks due to attenuation, multipath, and interference. Existing approaches either require additional energy consumption or sacrifice network throughput by adding redundant bytes in the packet. How to improve network performance without additional energy consumption and payload is still a challenging issue. We explores the characteristics in error packets to design novel recovery algorithms that can directly recover error packets without retransmission and redundant bytes. Specifically, through analyzing the corruptions, we first define two distinct bit error patterns in IEEE 802.15.4 PHY. Based on these analysis, we then propose an Error Packet Recovery (EPR) algorithm based on error characteristic of the adjacent data. Finally, we evaluate the performance of the proposed algorithm by conducting experiments in the outdoor environment. The results show that the EPR algorithm increases Packet Reception Rate (PRR) by more than 10%.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134019739","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":"Neuroadaptive Fault-tolerant PI Control of Nonlinear Systems with Unknown Control Direction","authors":"Yanan Zhang, Jun-Feng Lai, Zhirong Zhang, S. Tan","doi":"10.1109/ISASS.2019.8757746","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757746","url":null,"abstract":"In this paper, we propose a low-cost and effective neuroadaptive PI control for MIMO nonlinear systems with actuation failures as well as unknown control direction. In addressing both square and nonsquare systems with unknown control direction, we make use of Nussbaum-type function and the matrix decomposition technique to build a generalized PI control with adaptively adjusting gains, which do not require the time-consuming “trial and error” process for determining the gains as in traditional PI control; Furthermore, the neural network unit is constructed with the help of barrier Lyapunov function to guarantee the crucial compact set precondition for neural network training signals. Both theoretical analysis and numerical simulation on 3D trajectory tracking of unmanned vehicle authenticate the effectiveness of the proposed method.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126975420","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 Survey on Forest Fire Monitoring Using Unmanned Aerial Vehicles","authors":"F. A. Hossain, Youmin Zhang, C. Yuan","doi":"10.1109/ISASS.2019.8757707","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757707","url":null,"abstract":"Every year, forest fire causes heavy death toll and destruction around the world. The number of forest fires is increasing each year along with the damages associated with it. At this point, traditional forest fire detection methods such as point sensors, thermal sensors, watch tower, human patrol and satellite imagery are not being enough to provide early detection and continuous monitoring. Recent developments in electronics and control systems have made unmanned aerial vehicles (UAVs) more readily available and created an opportunity to utilize them for continuous forest monitoring with higher flexibility, maneuverability and precision. Early level experiments show that the limitations of the previous methods could be overcome by UAV-facilitated forest fire monitoring strategies. This paper highlights the basic idea of UAV-based forest fire monitoring and relevant researches and operations that have been conducted in this field thus far. The future of forest fire monitoring relies more on the use of UAVs and their onboard mission payloads, and the main motivation of this paper is to help for identifying the methodologies behind the existing systems and to find new methods of improving the UAV systems to fight this dreadful calamity.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"360 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120942539","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 and Application of Deep Belief Network Based on Local Binary Pattern and Improved Weight Initialization","authors":"Longyang Wang, J. Qiao","doi":"10.1109/ISASS.2019.8757780","DOIUrl":"https://doi.org/10.1109/ISASS.2019.8757780","url":null,"abstract":"In order to extract the features of the image more accurately, a deep belief network (DBN) based image feature extraction method is proposed. However, when the deep belief network extracts the features of the image, it is easy to ignore the local texture features of the image. Then the block local local binary mode is introduced to extract the local texture features of the image. At the same time, to improve the slow learning speed of the network, the initial weight of the network is improved. Finally, the proposed network is tested on the ORL image dataset. The results show that the proposed method not only improves the recognition accuracy of the network, but also accelerates the convergence speed of the network to some extent.","PeriodicalId":359959,"journal":{"name":"2019 3rd International Symposium on Autonomous Systems (ISAS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115373651","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}