Discipline

The Strategic Innovation Team for High-End Equipment System Integration and Simulation, taking national development strategy as its guidance, focuses its research on the key scientific issues of great social value and application prospect, and those concerning the development and future of our nation. The team, based on their common research interests, goals, and previous achievements, and with merged advantages of two key disciplines of USST (System Science---- a “Peak Discipline”, and System Engineering----a featured discipline for its application in national defense), has been devoted to modeling, analysis, fault diagnosis, synthesis, integration and simulation of the structure, performance and function of high-end equipment complex system used in the intelligent manufacturing and national defense sectors by the application of the principles and methods of system theory, information theory and control theory. The team provides strong theoretical support in the field of system science and system engineering for the design and manufacture of high-end equipment system, and meanwhile it promotes the innovative development of intelligent manufacturing, robotics and sophisticated weaponry in China by means of talent cultivation and scientific and technological services, providing further service for the national strategy of “Made in China 2025” and building Shanghai into the Center of Innovation for Science and Technology.

With the approaching of a new round of revolution and reform in science, technology and industry, the major developed countries in the world have successively reshaped their strategic layout by focusing on developing high-end equipment in order to seek technical advantages and remain at the commanding heights in the global competitions. Typical examples are the National Strategic Plan for Advanced Manufacturing in the United States, Industry 4.0 of Germany, British High-value Manufacturing, New Industrial France, and the Robot Strategy of Japan, featuring in the integration of advanced manufacturing technology and information technology into the high-end equipment.

University of Shanghai for Science and Technology, originated from University of Shanghai founded in 1906, and the later Shanghai Institute of Mechanical Engineering affiliated to the former Ministry of Machinery Industry, has been enjoying the reputation of “the Huangpu Military Academy in the Manufacturing Sector”(the earliest and best university in the sector of manufacturing) in China. It is a key university under the administration of Shanghai municipality, jointly built by State Administration of Science Technology and Industry for National Defense and Shanghai Municipal People’s Government. The Discipline of Systems Science and Systems Engineering focuses its research on complex systems, including natural system, human society system, and complex artificial system. High-end equipment is usually considered as an advanced complex artificial system that comprises many organically integrated parts of intensive technology and powerful functions, its development involving high cost, long production cycle, complex system structure, and massive cutting-edge technologies.

The research team, on the basis of long-term close cooperation, has been performing research work on integration and simulation of complex system in high-end equipment, and has formed several distinctive and internationally influential research directions. The team members have published nearly 500 papers (including accepted papers) in SCI journals in the field of systems and control, including more than 100 papers in the top journals in this field, over 70 papers have been listed as high-cited ESI papers (about 10 of them were listed as the top 0.1% of ESI hot papers). The team has published 7 monographs, has undertaken over 30 national and provincial scientific research projects. They have received one second-class prize of National Natural Science Award, and several provincial and ministerial level science and technology awards.

1

Performance analysis, synthesis and simulation of high-end equipment system with incomplete information

Information incompleteness refers to data loss, saturation, quantification, sampling, time delay and other phenomena that often occur in the equipment system. In previous literature, it is always assumed, more often indirectly, that the system measurement signals include the continuous real signals under noise interference. It is well known that the accuracy of the data measured plays a decisive role in the performance of the system. To obtain the system status and perform system synthesis and simulation on the basis of analyzing the stability, robustness and non-vulnerability of high-end equipment systems under the condition of incomplete information can provide important theoretical support for the design and manufacturing of high-end equipment systems.

Integrated collaborative control, fault diagnosis and safety monitoring of high-end equipment system

It focuses on the structure and optimization design of the high-end equipment systems used in industrial production and modern military to address the issues such as network attack, data loss and other problems occurring in multiple equipment complex systems and networked high-end equipment systems, to conduct research on the collaborative planning, synchronization, consistency, and integrated control, as well as fault diagnosis and safety monitoring during operation, providing safe and sound operation for the high-end equipment system.

Optimization and integration of big data, artificial intelligence and high-end equipment system

The design, manufacturing and operation of high-end equipment will generate massive data, which contains a large amount of useful information. By data mining, important information of equipment system can be obtained, and some deeper problems can be revealed, providing important evidences for improving the system performance and safe operation. Studying the structure and performance by means of big data and artificial intelligence algorithm, the team aims to provide theoretical basis for further optimization, analysis and integration of the system.

Academic Papers

1. Yongxiong Wang, Yubo Shi and Guoliang Wei, A Novel Local Feature Descriptor Based on Energy Information for Human Activity Recognition, Neurocomputing, vol. 228, no. 3, pp. 19-28, Mar. 2017.

2. Dongkai Zhang, Chaoli Wang, Guoliang Wei, Hengjun Zhang and Hua Chen, State-feedback Stabilisation for Stochastic Non-holonomic Mobile Robots with Uncertain Visual Servoing Parameters, International Journal of Systems Science, vol. 45, no. 7, pp. 1451-1460, Apr. 2014.

3. Quan Jiang, Chao Bi and Ruoyu Huang, A New Phase-delay-free Method to Detect Back EMF Zero-crossing Points for Sensorless Control of Spindle Motors, IEEE Transactions on Magnetics, vol. 41, no. 7, pp. 2287-2294, Jul 2005.

4. Kun Xia, Jing Lu, Chao Bi, Yuan Tan and Bin Dong. Dynamic Commutation Torque-Ripple Reduction for Brushless DC Motor Based on Quasi-Z-source Net, IET Electric Power Applications, vol.10, no. 9, pp. 819-826, Nov. 2016.

    The Method of Calculating the Number of Sensor Network Nodes, Inventors: Chen Shijie, Wei Guoliang, Fang Simin, Liu Qingyang, Wu pinting, Patent number: ZL201410209614.0, Grant date: January 16, 2018

5. Remote Monitoring System and Method for Distribution Power Transformer, inventors: Kang Yuting, Li Lin, Zhang Shaodan, patent number: ZL201410648182.3, Grant date: May 1, 2018

6. An Insulated Gate Bipolar Transistor Connected in Series on a Smooth Sliding Mode Control Method for Equalizing, Inventors: Li Ranyue, Wang Chaoli, Zhao Jian, Wang Gang, Cai Xian, Song Xiaoming, Wang Xue, Patent number: CN201610141637.1, Grant date: March 13, 2018