{"title":"Adaptive flow control in industrial pneumatics","authors":"Christian Busch, Norman Brix, S. Lambeck","doi":"10.1109/ICIEA.2012.6360689","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6360689","url":null,"abstract":"This article describes an online optimization method of an air flow control system realized in pneumatic industrial applications. With respect to the limited computational power of industrial hardware the presented algorithm is optimally designed for a low execution time and source consumption. Based on a least square optimization method the presented algorithm leads to an effective and robust control of the nonlinear plant. Special learning cycles known from other industrial applications are not required. By the use of an adaptive feedforward control and a closed loop controller for the compensation of static inaccuracy, a high dynamic response to setpoint changes with stationary accuracy could be reached.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115713509","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}
Min Guo, J. Lan, Juanjuan Li, Zongshu Lin, Qing Li
{"title":"Restoring algorithm for traffic data based on self-adaptive generation of area geometry","authors":"Min Guo, J. Lan, Juanjuan Li, Zongshu Lin, Qing Li","doi":"10.1109/ICIEA.2012.6361025","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6361025","url":null,"abstract":"Intelligent Transportation System (ITS) is provided with basic data support and continuous motive force by traffic information. So the quality of the raw traffic data detected by traffic sensors will directly affect the follow-up benefits of the entire system. Traditional restoration processing method, such as algorithms based on historical trend data and linear interpolation, faded in shortage for data processing, so that the true and implicit orderliness in the traffic flow data can not be reflected. In order to improve the accuracy of raw traffic data, a traffic data restoring algorithm based on self-adaptive generation of area geometry is proposed in this paper, which can judge and restore the incomplete traffic data after validity test. Through the validation using the Beijing actual traffic data, it is proved that this algorithm is precise and reliable compared with several common data restoring algorithms.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114270977","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":"Context and policy based fault-tolerant scheme in mobile ubiquitous computing environment","authors":"Haibin Cai, Linhua Jiang, Yue Zhang","doi":"10.1109/ICIEA.2012.6361001","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6361001","url":null,"abstract":"In ubiquitous computing system, the increasing mobile and dynamic of software and hardware resources and frequentative interaction among function components make fault-tolerant design very challenging. In this paper, we propose a context and policy based self-adaptive fault-tolerant mechanism for a mobile ubiquitous computing environment such as a mobile ad hoc network. In our approach, the fault-tolerant mechanism is dynamically built according to various types of detected faults based on continuous monitoring and analysis of the component states. We put forward the architecture of fault-tolerant system and the context-based and policy-based fault-tolerant scheme, which adopts ontology-based context modeling method and the Event-Condition-Action execution rules. The mechanism has been designed and implemented as self-adaptive fault-tolerant middleware, shortly called SAFTM, on a preliminary prototype for a dynamic ubiquitous computing environment such as mobile ad hoc network. We have performed the experiments to evaluate the efficiency of the fault-tolerant mechanism. The results of the experiments show that the performance of the self-adaptive fault tolerant mechanism is realistic.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117255975","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":"Kernel-based Regularized Neighbourhood Preserving Embedding in face recognition","authors":"Pang Ying Han, A. Teoh","doi":"10.1109/ICIEA.2012.6360849","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6360849","url":null,"abstract":"Face images always have significant intra-class variations due to different poses, illuminations and facial expressions. These variations trigger substantial deviation from the linearity assumption of data structure, which is essential in formulating linear dimension reduction technique. In this paper, we present a kernel based regularized graph embedding dimension reduction technique, known as kernel-based Regularized Neighbourhood Preserving Embedding (KRNPE) to address this problem. KRNPE first exploits kernel function to unfold the nonlinear intrinsic facial data structure. Neighbourhood Preserving Embedding, a graph embedding based linear dimension reduction technique, is then regulated based on Adaptive Locality Preserving Regulation Model, established in [7] to enhance the locality preserving capability of the projection features, leading to better discriminating capability and generalization performance. Experimental results on PIE and FERET face databases validate the effectiveness of KRNPE.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115014340","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}
K. M. Goh, S. H. Ong, Y. Y. Joe, P. Kusolpalin, W. P. Moh, K. V. Ling
{"title":"FPGA based wireless sensor node for distributed process monitoring","authors":"K. M. Goh, S. H. Ong, Y. Y. Joe, P. Kusolpalin, W. P. Moh, K. V. Ling","doi":"10.1109/ICIEA.2012.6361045","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6361045","url":null,"abstract":"In this paper, we investigate FPGA based wireless sensor node for distributed process monitoring. The research uses Collaborative Clusters of wireless sensor nodes concept to achieve distributed monitoring. To demonstrate the concept, a virtual chemical process unit in a typical chemical plant is used as an example application. The paper also presents the implementation of wireless sensor node with FPGA as the secondary processor. The sensor nodes will measure and pre-process raw data from sensor source before sending them to a higher order node in the network in order to achieve real-time monitoring. To enable the sensor nodes for rapid creation of wireless sensing applications, an improved system setup is proposed and the results of the implementation will be discussed.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115133889","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}
F. Schimbinschi, M. Wiering, R. Mohan, J. K. Sheba
{"title":"4D unconstrained real-time face recognition using a commodity depth camera","authors":"F. Schimbinschi, M. Wiering, R. Mohan, J. K. Sheba","doi":"10.1109/ICIEA.2012.6360717","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6360717","url":null,"abstract":"Robust unconstrained real-time face recognition still remains a challenge today. The recent addition to the market of lightweight commodity depth sensors brings new possibilities for human-machine interaction and therefore face recognition. This article accompanies the reader through a succinct survey of the current literature on face recognition in general and 3D face recognition using depth sensors in particular. Consequent to the assessment of experiments performed using implementations of the most established algorithms, it can be concluded that the majority are biased towards qualitative performance and are lacking in speed. A novel method which uses noisy data from such a commodity sensor to build dynamic internal representations of faces is proposed. Distances to a surface normal to the face are measured in real-time and used as input to a specific type of recurrent neural network, namely long short-term memory. This enables the prediction of facial structure in linear time and also increases robustness towards partial occlusions.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121778033","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":"Fast license plate location and recognition using wavelet transform in android","authors":"Chuin-Mu Wang, Ching-Yuan Su","doi":"10.1109/ICIEA.2012.6360875","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6360875","url":null,"abstract":"In license plate recognition system (LPRS), there have several parts which are the key steps of the LPRS as license plate location (LPL), character segmentation (CS), and character recognition (CR). In this paper, we develop a complete LPRS in mobile smart device. The reasons are that have advantages which are easy carrying, powerful camera existence, and extensive application in potential. First at all, we define a processing range which is region of interest (ROI). In the part of LPL, we use wavelet transform to detect the horizontal axis in ROI based on texture feature of license plate (LP) and block scanning based on aspect ratio of LP to locate the LP location. In the part of CS, we mark the character edges based on color feature of LP to segment the characters. In the part of CR, we normalize the characters at first, then, compare them with character samples in system database. We use voting result to recognize. As result in the experiments, the LPRS which is building on mobile smart device have superior recognition results and fast processing performance.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124020220","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":"Selfish nodes detection mechanism and stimulation mechanism over mobile peer-to-peer networks","authors":"Xingtai Wang, Da-Peng Qu, Huang Min","doi":"10.1109/ICIEA.2012.6360874","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6360874","url":null,"abstract":"The nodes over mobile peer-to-peer networks often show selfish behavior for their limited resource and different interest. So detecting and stimulating selfish nodes to cooperate is a new important research topic. Through allowing nodes to freely express their subjective forwarding willing, the detection mechanism is implemented. Through punishing nodes which have a higher selfish degree than given threshold or lie about its information, the stimulation mechanism is implemented. Simulation results show that the detection mechanism and stimulation mechanism not only can discover appropriate routing, but also can stimulate selfish nodes to actively cooperate when the degree of nodes' selfishness is excessive.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"432 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125760331","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":"NN-based adaptive dynamic surface control for a class of nonlinear systems with input saturation","authors":"Junfang Li, Tie-shan Li, Yong-ming Li","doi":"10.1109/ICIEA.2012.6360792","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6360792","url":null,"abstract":"In this paper, a new direct robust adaptive neural network controller is present for uncertain nonlinear systems with input saturation and external disturbances. By incorporating dynamic surface control (DSC) technique into a neural network based adaptive control design framework, the control design is achieved based on backstepping technique. By virtue of this technique, the problem of “explosion of complexity” inherent in the conventional backstepping method is avoided. At the same time, the controller singularity problem is avoided completely and the effect of input saturation constrains is considered in this control design. In addition, it is proved that all the signals in the closed-loop system are semi-global uniformly ultimately bounded and the tracking error converges to a small neighborhood of the origin. Finally, simulation studies are given to demonstrate the effectiveness of the proposed scheme.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125906619","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":"Adaptive control of horizontal magnetic levitation system subject to external disturbances","authors":"A. Huang, Yu-Mao Lin, Chen-Yu Kai","doi":"10.1109/ICIEA.2012.6360773","DOIUrl":"https://doi.org/10.1109/ICIEA.2012.6360773","url":null,"abstract":"In this paper, an adaptive controller is designed to a magnetic levitation system to cope with internal time-varying uncertainties and external disturbances. Since, in an experimental study, the traditional magnetic levitation design is not easy to realize external disturbances to the system, a horizontal configuration is constructed in this paper. To facilitate the analysis and controller design, the equation of motion is derived in detail. Due to the asymmetric nature of the magnetic loop, there is a big challenge in the controller design process. In addition, since some of the uncertainties enter the system in a mismatched manner, few control strategies are feasible. A multiple-surface sliding control law is proposed with the function approximation technique to stabilize the closed loop system under various uncertainties and disturbances. A rigorous mathematical proof is given to verify the feasibility of the design. Experimental studies are conducted with the comparisons with the conventional PID design to clarify the performance of the proposed controller.","PeriodicalId":220747,"journal":{"name":"2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA)","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129788403","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}