The National Science Center (NCN) announced the results of the third edition of the international SHENG competition for Polish-Chinese research projects. One of the 13 grants designated for funding was awarded to Dr. hab. Eng. Wojciech Paszke from the Institute of Automation, Electronics and Electrical Engineering at the University of Zielona Góra for the project titled "Data-assisted real-time control and performance optimization for complex non-linear batch production systems". The Polish side will receive 866,000 PLN for the implementation of the grant. The project will be carried out from 2024 to 2026 in collaboration with Dalian Polytechnic, with Prof. Tao Liu as the leader of the Chinese team.
"We already applied together with this research topic in the SHENG 1 competition," said Prof. Wojciech Paszke. "Unfortunately, we did not receive funding at that time. However, we were able to secure funding in the OPUS competition resolved in 2021. The project being implemented is the first stage of our joint research. The project in OPUS is funded entirely by the Polish side, while the grant from the SHENG competition is funded by both the Polish and Chinese sides," added Prof. Paszke. The professors have known each other since 2015, with Prof. Paszke visiting Dalian and Prof. Liu visiting the University of Zielona Góra in 2017.
The project will be carried out simultaneously at 3 universities - at the University of Zielona Góra in the Institute of Automation, Electronics and Electrical Engineering, at Dalian Polytechnic (the main partner of the project), and at Jiangnan University in Wuxi - the twin city of Zielona Góra. Prof. Hongfeng Tao will coordinate the research work at this university.
Prof. Paszke's winning grant is the fourth one he has implemented at NCN. He emphasizes that he would not have achieved so many successes without the people he met along the way. "I owe a lot to the late Prof. Krzysztof Gałkowski, who introduced me to these research topics and shared his contacts with me. I also met Prof. Tao Liu, with whom I am implementing this project, thanks to Prof. Gałkowski," he added. "I would like to emphasize that I have not achieved anything alone. I already have a permanent team with whom I have been working for years, especially with Dr. hab. Eng. Maciej Patan and Prof. Dr. Eng. Krzysztof Patan, with whom we have already completed many projects and work very well together. I also collaborate with them on this project."
In the resolved SHENG competition, 125 applications were submitted. Among those qualified for funding, there was 1 project from the social sciences group and 12 from the exact and technical sciences group. The total value of funding for all projects is over 15 million PLN.
The funded research will be conducted in Poland and China, with two directors overseeing each project: one on the Chinese side and one on the Polish side. The received funds can be used for conducting research, compensating the research team, providing scholarships for students or doctoral students, purchasing or producing scientific research equipment, and covering other costs associated with the expenses necessary for the implementation of the Polish part of the research project.
The SHENG competition
The international bilateral SHENG 3 competition for Polish-Chinese research projects is organized by the National Science Center in collaboration with the Chinese agency National Natural Science Foundation of China (NSFC), following a parallel evaluation procedure. This means that both agencies conduct a parallel formal and substantive evaluation of the applications, and funding will only be granted to projects that receive recommendations from both NCN and NSFC simultaneously. In the SHENG 3 competition, applications could include basic research in selected areas of disciplines covered by panels ST1-ST3, ST6-ST7, ST9-ST10, and HS4.
PROJECT DESCRIPTION:
With the rapid development of many industries such as chemical and pharmaceutical production, steel, and automobiles, the importance of batch production systems has increased significantly. These systems allow for a significant increase in the number of products with noticeably better quality, thus enabling companies to increase profits. However, modeling the dynamics of such a production system with constantly increasing non-linearity and complexity has become much more challenging, and even impossible, significantly complicating the direct application of model-based control and production performance optimization methods. Furthermore, in the last two decades, advanced measurement techniques have been widely used for real-time monitoring of various process variables, effectively facilitating the control of batch production processes. Therefore, both in the academic environment and in the industry, control methods for batch processes based on measured data (as opposed to model-based methods) have gained significance.
Given the above facts, the project aims to develop data-assisted control and optimization methods for industrial non-linear batch production systems, along with active disturbance rejection methods to improve the quality of individual batches production.
To overcome the limitations of existing control methods for existing batch production systems, this project will investigate the application possibilities of iterative learning control (ILC) methods based on data to solve the difficult problem of time-varying uncertainties related to the actual batch process using only real-time input-output data and historical data from previous batches. This will avoid the difficulties in modeling the considered processes.
Additionally, new ILC methods will be developed in conjunction with an active disturbance rejection approach to overcome the negative impact of non-repeating or periodic load disturbances, often encountered in batch processes, e.g. raw material feeding or product unloading, which could seriously degrade the effectiveness of existing ILC methods or even destabilize the resulting production systems. Moreover, adaptive data-based ILC schemes will be developed for non-linear batch processes subject to unique initial conditions and variable batch periods, as these issues pose challenges in applying known batch process optimization methods and may even destabilize control systems. Therefore, a new theory of data-based ILC schemes will be developed to analyze the convergence of all proposed ILC schemes, along with an appropriate stability analysis.
This research project will be an excellent opportunity to improve coordination and synergy between research groups from Dalian Polytechnic, Jiangnan University, and the University of Zielona Góra. Focusing on the challenge of applying control methods utilizing direct analysis based on measured data for complex non-linear batch production systems, the project will significantly deepen the bilateral cooperation between Chinese and Polish teams and contribute to a new and fruitful collaboration with industrial partners on both sides. Consequently, the project will be an important step towards integrating academic and industrial environments in China and Poland, thereby enabling significant progress in the demanding field of control engineering to modernize significant industries. Additionally, the planned outcomes of the project include:
