山東大學控制科學與工程學院教授，碩士生導師，博士生導師
基本介紹
- 中文名：王炳昌
- 外文名：Bingchang Wang
- 畢業院校：中國科學院
學習工作經歷:
2011年7月在中國科學院系統科學所獲得博士學位;
2011年10月至2012年9月在阿爾伯塔大學(加拿大)作博士後;
2012年9月至2013年9月在紐卡斯爾大學(澳大利亞)作Research Academic;
2013年10月加入山東大學控制科學與工程學院;
2014年11月至2015年5月訪問卡爾頓大學(加拿大)任Research Associate.
研究方向：
多智慧型體(機器人)協作、分散式計算與最佳化、隨機控制與隨機算法、無線感測網路、大數據分析
社會兼職
擔任中國自動化學會青年工作委員會委員，中國自動化學會控制理論專業委員會隨機系統學組、多自主體控制學組委員.
擔任Session Co-chair/Chair of Chinese Control Conference (CCC2014, 2015, 2016)， Program Committee Member of the 12th World Congress on Intelligent Control and Automation (WCICA 2016).
擔任IEEE Transactions on Automatic Control, SIAM Journal on Control and Optimization, IEEE Conference on Decision and Control, IFAC World Congress 等國際期刊和會議的審稿人.
科研項目：
主持國家自然科學基金優秀青年基金一項，面上項目一項、青年項目一項、教育部留學回國基金一項、山東大學自主創新基金一項；參與重大國際合作與交流項目(260萬)一項、國家自然科學基金面上項目兩項(已結題)和青年項目一項.
在國際期刊和會議上發表論文50餘篇，主要包括:
期刊論文
[1] Bing-Chang Wang*,and Ji-Feng Zhang,Social optima in mean field LQG models with Markov jump parameters, SIAM Journal on Control and Optimization, 55(1), 429-456, 2017.
[2] Bing-Chang Wang*, Xiangyu Meng and Tongwen Chen, Event based pulse-modulated control of linear stochastic systems, IEEE Transactions on Automatic Control, 59(8), 2144-2150, 2014.
[3] Bing-Chang Wang*, and Ji-Feng Zhang, Hierarchical mean field games for multi-agent systems with tracking-type costs: Distributed epsilon-Stackelberg equilibria, IEEE Transactions on Automatic Control, 59(8), 2241-2247, 2014.
[4] Qiang Zhang, Bing-Chang Wang*, and Ji-Feng Zhang, Distributed dynamic consensus under quantized communication data. International Journal of Robust and Nonlinear Control, 25, 1704–1720, 2015.
[5] Bing-Chang Wang*, and Ji-Feng Zhang, Distributed output feedback control of Markov jump multi-agent systems, Automatica, 49(5), 1397-1402, 2013.
[6] Bing-Chang Wang, and Ji-Feng Zhang*, Mean field games for large-population multiagent systems with Markov jump parameters, SIAM Journal on Control and Optimization, 50 (4), 2308-2334, 2012.
[7] Bing-Chang Wang, and Ji-Feng Zhang*, Distributed control of large population multiagent systems with random parameters and a major agent, Automatica, 48 (9), 2093-2106, 2012. (Regular paper)
[8] Bing-Chang Wang, and Yuan-Yuan Liu*, Local asymptotics of a Markov modulated random walk with heavy tailed increments, Acta Mathematica Sinica, English Series (SCI), 27(9), 1843-1854, 2011.
[9] Zhen-Ting Hou, and Bing-Chang Wang*, Makov skeleton process approach to a class of partial differential-integral equation systems arising in operation research, International Journal of Innovative Computing, Information and Control(SCI), 7(12), 6799-6814, 2011.
[10] Bing-Chang Wang, and Ji-Feng Zhang, Consensus conditions of multi-agent systems with unbalanced topology and stochastic disturbances, Journal of Systems Science and Mathematical Sciences, 29(10), 1353-1365, 2009. (in Chinese)
[11] Bing-Chang Wang, and Hai-Ling Dong, Some local asymptotic results on Markov renewal theorems, Mathematica Applicata, 2010, 23 (2), 237-243. (in Chinese)
[12] Bing-Chang Wang, Hai-Ling Dong, and Xiu-Li Chen, An expression of local equivalent relation on Markov renewal measure, Mathematica Applicata, 2009, 22 (3): 485-489. (in Chinese)
[13] Hai-Ling Dong, Zhen-Ting Hou, and Bing-Chang Wang, A Class of Markov-modulated continuous infectious disease model, Journal of Biomathematics, 2008, 23(1), 79-84. (in Chinese)
[14] Yibing Sun, Minyue Fu, Bingchang Wang, Huanshui Zhang, Damian Marelli, Dynamic state estimation for power networks using distributed MAP technique, Automatica, 2016.
[15] Hai-Ling Dong, Jia-Mu Zhou, and Bing-Chang Wang, Exponential synchron- ization on Markov jump networks with random occurs and nonlinearities coupling via event-triggered strategy, resubmitted to IEEE Transactions on Neural Networks and Learning Systems.
[16] Bing-Chang Wang and Minyue Fu, Optimal sampling for state estimation of discrete-time linear systems, preprint.
會議論文
[1] Bing-Chang Wang, and Minyi Huang, Dynamic production output adjustment with sticky prices: A mean field game approach, Proceedings of 54th IEEE Conference on Decision and Control(CDC), Osaka, Japan, 2015.
[2] Yibing Sun, Minyue Fu, Bingchang Wang, Huanshui Zhang, A distributed MAP approach to dynamic state estimation with applications in power networks, Proceedings of 14 European Control Conference, Linz, Austria, 2015.
[3] Bing-Chang Wang, Mean field team decision problems for Makov jump multiagent systems, Proceedings of the 34th Chinese Control Conference, July 28-30, 2015, Hangzhou, 1845-1860.
[4] Bing-Chang Wang, and Minyue Fu, Comparison of periodic and event based sampling for linear state estimation, World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, 2014.
[5] Bing-Chang Wang, Mean field games for Markov jump multi-agent system，Proceedings of the 33th Chinese Control Conference, July 28-30, Nanjing, 2014, pp. 5397-5402.
[6] Xiangyu Meng, Bingchang Wang, Tongwen Chen and Mohamed Darouach, Sensing and actuation strategies for event triggered stochastic optimal control. Proceedings of 52nd IEEE Conference on Decision and Control (CDC), Florence, Italy, 2013, pp. 3097-3102.
[7] Bing-Chang Wang, and Ji-Feng Zhang, Stackelberg games of large population multiagent systems: Centralized and distributed strategies, Proceedings of the 31th Chinese Control Conference, Hefei, 2012, pp. 6303-6308.
[8] Bing-Chang Wang, and Ji-Feng Zhang, Distributed control of multi-agent systems with major agents and Markov parameters, Proceedings of the 30 Chinese Control Conference, Yantai, China, July 22-24, 2011, pp. 4835-4840.
[9] Bing-Chang Wang, and Ji-Feng Zhang, Mean field games for large-population stochastic multi-agent systems with Markov jump parameters，Proceedings of the 29th Chinese Control Conference, July 29-31, Beijing, 2010, pp. 4572-4577.
