{"title":"Hierarchical State Space Checks for Errors in Sensors, Actuators and Control of Nonlinear Systems: Diagnosis and Compensation","authors":"Md Imran Momtaz, A. Chatterjee","doi":"10.1109/ATS47505.2019.00026","DOIUrl":"https://doi.org/10.1109/ATS47505.2019.00026","url":null,"abstract":"The rapid rise of self-driving cars and drones has raised questions about the safety of autonomous robotics deployed in society. Prior work on robust and adaptive control make assumptions about the boundedness of errors or require the use of full scale system models running in the background for control reference. In this research, we show how state space checks can be used to diagnose and compensate for errors in sensors, actuators and control program execution in nonlinear systems for robotic applications. The primary focus is on lightweight methods for mitigation of transient errors in sensor data and control program execution and parametric deviations in sensor circuitry and actuator subsystems. A quadcopter is used as a test vehicle for the research and simulation results indicate that errors can be compensated with high efficiency and low computation overhead.","PeriodicalId":258824,"journal":{"name":"2019 IEEE 28th Asian Test Symposium (ATS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129408830","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":"ATS 2019 Program Committee","authors":"V. Agrawal","doi":"10.1109/ats47505.2019.00011","DOIUrl":"https://doi.org/10.1109/ats47505.2019.00011","url":null,"abstract":"Vishwani Agrawal, Auburn University Rob Aitken, ARM Ltd. Lorena Anghel, Phelma Grenoble INP, TIMA Laboratory Davide Appello, STMicroelectronics Masayuki Arai, Nihon University Manuel Barragan, TIMA Laboratory Kanad Basu, New York University Bernd Becker, Albert-Ludwigs-University, Freiburg Paolo Bernardi, Politecnico di Torino Bhargab B. Bhattacharya, IIT Kharagpur, India Krishnendu Chakrabarty, Duke University Abhijit Chatterjee, Georgia Institute of Technology Degang Chen, Iowa State University Harry Chen, MediaTek Vivek Chickermane, Cadence Design Systems Masahiro Fujita, The University of Tokyo Anne Gattiker, IBM Patrick Girard, LIRMM Dimitris Gizopoulos, University of Athens Kazumi Hatayama, Gunma University Tsung-Yi Ho, National Tsing Hua University Michael Hsiao, Virginia Tech Shi-Yu Huang, National Tsing Hua University, Taiwan Michiko Inoue, Nara Institute of Science and Technology Masahiro Ishida, Advantest Corporation Rohit Kapur, Cadence Design Systems Naghmeh Karimi, University of Maryland, Baltimore County Ramesh Karri, Polytechnic institute of NYU Haruo Kobayashi, Gunma University Abhishek Koneru, Duke University Erik Larsson, Lund University Kuen-Jong Lee, National Cheng Kung University James Li, NTU Taipei, Taiwan Huawei Li, Institute of Computing Technology, Chinese Academy of Sciences Xiaowei Li, Institute of Computing Technology, Chinese Academy of Sciences Jin-Fu Li, National Central University Shyue-Kung Lu, National Taiwan University of Science and Technology Erik Jan Marinissen, IMEC","PeriodicalId":258824,"journal":{"name":"2019 IEEE 28th Asian Test Symposium (ATS)","volume":"2672 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133218478","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}
Cheng-Hung Wu, Yu Huang, Kuen-Jong Lee, Wu-Tung Cheng, Gaurav Veda, S. Reddy, Chun-Cheng Hu, Chong-Siao Ye
{"title":"Deep Learning Based Test Compression Analyzer","authors":"Cheng-Hung Wu, Yu Huang, Kuen-Jong Lee, Wu-Tung Cheng, Gaurav Veda, S. Reddy, Chun-Cheng Hu, Chong-Siao Ye","doi":"10.1109/ATS47505.2019.000-9","DOIUrl":"https://doi.org/10.1109/ATS47505.2019.000-9","url":null,"abstract":"With the increase in design complexity and test data volume, compressed tests together with on-chip test decompression hardware such as Embedded Deterministic Test (EDTTM) are widely used in industry in order to reduce test cost. One of the challenges of such Design-for-Test (DFT) technology is to determine a set of optimal parameters such as the number of scan chains, scan channels, power budget, etc. such that it can reach the highest test coverage with a minimum amount of test data volume whilst satisfying various other constraints. To achieve the optimal compression configuration quickly, in this work deep learning technology based on Tensorflow is explored to estimate the test coverage and the data volume for a design when employing EDT under a given set of circuit parameters. Based on the estimated data, the optimal test architecture is also predicted, yielding a more efficient approach compared to the currently used trial-and-error methods. To demonstrate the advantages of our deep learning approach over the currently used utility, we present experimental data for eight industrial designs.","PeriodicalId":258824,"journal":{"name":"2019 IEEE 28th Asian Test Symposium (ATS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131813062","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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