University of Groningen
Coordination networks under noisy measurements and sensor biases
Shi, Mingming
DOI:
10.33612/diss.99968844
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Publication date: 2019
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Citation for published version (APA):
Shi, M. (2019). Coordination networks under noisy measurements and sensor biases. Rijksuniversiteit Groningen. https://doi.org/10.33612/diss.99968844
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Coordination networks under
noisy measurements and
sensor biases
The research described in this dissertation has been carried out at the Faculty of Science and Engineering, University of Groningen, the Netherlands.
This research was supported by Chinese Scholarship Council (CSC), the Chinese Ministry of Education.
The research reported in this dissertation is part of the research program of the Dutch Institute of Systems and Control (DISC). The author has successfully completed the educational program of DISC.
The cover picture is downloaded from Unsplash uploaded by Meagan Carsi-ence.
The thesis is printed by IPSKAMP printing. ISBN 978-94-034-2015-8 (printed version) ISBN 978-94-034-2014-1 (electronic version)
Coordination networks under noisy
measurements and sensor biases
PhD Thesis
to obtain the degree of PhD at the University of Groningen
on the authority of the Rector Magnificus Prof. dr. E. Sterken
and in accordance with the decision by the College of Deans This thesis will be defended in public on
Friday 25 October 2019 at 12:45 hours
by
Mingming Shi born on 18 May 1989
Supervisor Prof. C. De Persis Co-Supervisor Dr. P. Tesi Assessment committee Prof. C. Altafini Prof. D. Bauso Prof. J. Hendrickx
To my family, Xia Man,
Shi Junchang, Zhao Xiaoge, Shi Kaiyu, Shi Panpan
Acknowledgements
”one time, one meeting.”
–Sen no Rikyū
How time flies! The four years PhD time is going to draw an end. I still feel that my first arrival at the central station of Groningen happened not long ago. The four years’ staying in this small, quiet and beautiful city undoubtedly leaves a unique and deep impression in my mind and will still shine in my later life. Even though I am not a person who socialize much, there are still a lot of memories emerging now when I am sitting in the corner of my office. In fear of losing these moments many years later, I write this chapter to record and thank the people who flash into my mind.
My sincere gratitude goes to my Supervisors Claudio De Persis, who is know-ledgeable, sharp and witty. I would like to thank him gratefully for his pa-tience when I got stuck, his rigor when I was sloppy, and his encouragement when I was unconfident. He always encourages me to try my best in pursuing simple and interesting problems, and criticizes me for the messy communic-ation skills. Looking back to the first year when I was here, these criticisms and encouragement make me improve greatly in being as a Phd. I would also like to thank my co-promoter Pietro Tesi for his guidance in the problem for-mulation and paper writing. He is easygoing, smart and good at listening. With not many words, he could easily convey sharp thought. All in all, pur-suing the Phd under the supervision of my supervisors is very comfortable and more like to learning and fighting with two experienced friends. I am also grateful to Nima Monshizadeh for the nice discussion and help in working on the problem in the fifth chapter. His flexibility and quick thinking really impress me.
I would like to thank the assessing committee for their dedication in reading my thesis and provide me with their instructive suggestions. I should also thank the group support team, especially Frederika for her effort in the confer-ences, events and group outings. Great thanks to Qin Yuzhen and Ji Chengtao
viii
for accepting to be my paranymphs. They are also two of my best friends in Groningen. I spend a lot of time with you in having food, playing Mahjongg and card games, watching movies, travelling and discussing.
My gratitude also goes to my former office-mates and -neighbors, Erik, Danial, Shuai, Tobias, Sebastian and Tjardo. Much gratitude goes to Shuai, Erik and Tobias for their daily help, both academically and non-academically. I am grateful to Tobias for the translation of the summary of the thesis. I enjoyed the discussion about the research on the noisy consensus with Danial. Talking with the current members of our group, Mehran, Meichen, Guopin, Monique and Alexandro during the lunch also brings me a lot fun in the last year of the Phd.
I would also like to express my gratitude to the (former) Chinese member in DTPA and JBI, which are all kind and easygoing, especially for Qin Yuzhen and his wife Ge Shanshan, Yang Qingkang, Jiao Junjie, Chen Liangming, Xue Dong, Guo Miao and his wife Tian Bei, Zhou Ning, Zhang Hongyu, Cheng Xiaodong, Huang Jie, Bai Xiaoshan. I would miss the time of dinners and card games with you. My foreigner colleagues are always humorous and bringing fun to the chat. I feel pleased to talk with them, particularly with Alain, Yu, Hadi, Nelson, Martijn, Matthijs.
Many thanks to my (former) neighbors, Yan Xingchen, He Wei, Guo Hao, Fu Haigen, Xu Liang, Wu huala, Tao Yehan, Xu Qi, Ge Luo. We shared a lot of fun and silly times in the weekends, which often started with a hotpot or barbe-cue and are followed by board games. Sometime, these times were also shared with my (our) friends, Gu Xianming, Guo Yafei and Li Jiuling, Tian Yuchen, Zhang Yanxi and Liu Bin. I also miss the walking with some of you in the cit-ies and the mountains of the eastern Europe, which was exhaustive but full of laughing. I want to thank Deng Chenglong, Zhang Xuewen and Xiao Chengy-ong for reserving the ground for the badminton and helping me to improve my skill. I would also like to thank other friends I made in Groningen, Liu Yuru, Gao Kai, Cao Huangtang, Tang Xiaoying, etc. who have helped me directly and indirectly, and shared fun with me in the last four years.
Apart from my friends in Groningen, I feel grateful to Ye Dong, which guided me in the master research and convinced me to apply for the Phd position abroad. Without his help, there is no chance for me to end up with the Phd degree in Groningen. I would also like to thank the friends in my master who still share their life with me: Li Haiqin, Hou Zhili, Jiang Bingqiang, Huang Simeng, Fang Xiang, Sun Rui, Wan Neng, Han Weixin, Shao Qi, Shen Donghao
ix and Ren Bin. Chatting with you really release my pressure in pursuing the
Phd. Hope we will keep in touch.
At last, the deepest gratitude goes to my parents for their insistence on the higher education of my sisters and mine, which was not easy for a family with three children in a small village of China in the early of the last decade. I should also thank my sisters who accompanied and took care of my parents in the last four years. Endless love to my wife. I feel guilty that I can not spend more time with you in the last four years.
Mingming Shi Groningen 17thof September, 2019
Contents
1 introduction
1
1.1 Network coordination under communication noise . . . 2
1.2 Self triggered coordination . . . 4
1.3 Sensor bias estimation . . . 4
1.4 Outline of this thesis . . . 5
2 preliminaries
7
2.1 Notation . . . 72.2 Graph-theoretic notions . . . 7
2.3 Bipartite graphs . . . 8
2.4 Compressed sensing . . . 9
3 self-triggered network coordination over noisy
communica-tion channels
13
3.1 Introduction . . . 143.2 Framework and Outline of the Main Results . . . 15
3.3 Self-triggered Coordination with Adaptive Consensus Thresholds 17 3.4 Noiseless Case . . . 19
3.5 Noisy Case . . . 22
3.6 Adaptive Thresholds, Sign Function and Node-to-node Error . . 32
3.7 Numerical Examples . . . 38
3.8 Conclusions . . . 44
3.9 Appendix A: Communication Delays . . . 45
4 benefits of saturating information in coordination networks
with noise
55
4.1 Introduction . . . 564.2 Problem formulation – Self-triggered interval consensus . . . . 57
4.3 Main Result . . . 59
4.4 Asymptotic consensus . . . 67
4.5 Numerical examples . . . 68
4.6 Conclusion . . . 72
xii contents
4.7 Appendix B: Proofs of the results of the asymptotic consensus . 75
5 bias estimation in sensor networks
83
5.1 Introduction . . . 84
5.2 Problem formulation – biases estimation in sensor networks . . 87
5.3 Non-bipartite graphs . . . 90
5.4 Bipartite graphs . . . 94
5.5 Numerical Simulations . . . 105
5.6 Conclusion . . . 110
6 conclusions and future research
111
6.1 Conclusions . . . 1116.2 Future Research . . . 112
