Speaker: Chunxi Yang, Kunming University of Science and Technology, China
Title: Design, Modelling and Control of a Modular Reconfigurable Flight Array
Abstract: The modular reconfigurable flight array (MRFA) is known as a special multi-rotor craft which composes of no less than four flight modules with the same function. This flight array can change its structure arbitrarily to fit in different environments and missions, or recover from damage. Through the combination of multiple flight modules, the novel vehicle can be assembled into different configurations easily and quickly. Therefore, it has many special characteristics that the traditional one cannot have such as irregular configurations, natural overdrive feature and stronger failure redundancy capability. Despite its benefits, the current MRFA face a significant challenge both in structural design and in control method for its abnormal structure. To further develop the value of MRFA and its ability to cope with various complex environment and missions’ requirements, several feasible methods related to structural design, modeling and control of MRFA will be developed for comprehensive applications.
In this lecture, the main ideas and technologies of MRFA will be introduced, including the mechanical design of the MRFA module, the on-line module configurations algorithm, universal modelling method for its irregular configurations and controller design for better performances. Several application examples will also be presented to show the advantages of MRFA.
Biography: Chunxi Yang, a professor of Kunming University of Science and Technology. He served as the key member of Yunnan Key Laboratory of Intelligent Control and Application, vice President of department of intelligent manufacturing engineering. He authored and coauthored more than 100 papers, 20 patents. His research interests include intelligent control of complex mechanical and electrical system, networked control system and bag data technique, etc.
Speaker：Honggang Cui，Executive Director of Kunming KESC Smart Airport Technology Co.
Title：The Control Technology For Automated Baggage Handling System In Large Hub Airports
Abstract: Due to its large scale, complex structure, high processing capacity and reliability requirements, the automated baggage handling system in large hub airports places stringent requirements on the control system. This topic will introduce the structure, characteristics and proprietary technology of the control system according to the practice of baggage handling system engineering, and provide reference for the design of related logistics system automation system.
Biography: Honggang Cui, a researcher-level senior engineer and an expert enjoying special government allowances from the State Council. He graduated from Northwestern Polytechnical University in 1997 with a major in industrial automation and is currently employed by Kunming KSEC Smart Airport Technology Co., Ltd. He has long been engaged in the applied research of automation and information technology applications, and has presided over and participated in the research and development of more than 10 provincial and ministerial-level scientific research projects. His research achievements have won 3 first prizes and 2 third prizes for provincial and ministerial scientific and technological progress. He has published more than 10 papers and obtained more than 10 patent authorizations.
Speaker：Yunping Liu, Nanjing University of Information Science and Technology, China
Title：A fast formation obstacle avoidance algorithm for clustered UAVs based on artificial potential field
Abstract: The aim of this studies is to improve the rapid obstacle avoidance control of UAVs cluster in a complex obstacle environment, primarily utilizing the finite-time consistent formation control algorithm and the improved artificial potential field algorithm to design the fast obstacle avoidance control strategy. Firstly, a finite-time consistent formation control algorithm is adopted to address the problems of slow formation speed and low control accuracy of UAVs clusters for establishing the formation model and control of UAVs cluster. Then, taking static and dynamic obstacles as obstacle avoidance targets, the improved artificial potential field algorithm is utilized, and the auxiliary potential field and dynamic situation field range of obstacle velocity are also introduced. The algorithm enhances obstacle avoidance speed and efficiency from the two aspects: time optimization and space optimization. Meanwhile, dynamic perturbation is introduced to address the local minimum problem of traditional artificial potential field. Finally, the effectiveness of the algorithm is confirmed through simulation on a verification platform and testing on a physical prototype verification platform.
Biography: Yunping Liu received his PhD degree in College of Mechanical and Electrical Engineering from Nanjing University of Aeronautics and Astronautics of China in 2009 and he was a Post Doctor in Beijing University of Aeronautics and Astronautics from March 2013 to March 2016. He is now a professor and doctoral supervisor of the School of Automation, Nanjing University of Information Science and Technology. He has been engaged in intelligent robot and equipment research for a long time, and has published more than 20 papers in academic journals such as the Journal of Mechanical Engineering and the Journal of Field Robotics.
Speaker：Deming, Lei, Wuhan University of Technology, China
Title：Production scheduling problems with batch processing machines in the real-life manufacturing processes
Abstract: The aim of this studies is to solve some production scheduling problems in some real-world manufacturing processes by using meta-heuristics with new optimization mechanisms. Firstly, parallel batch processing machines scheduling problem in fabric dyeing process is considered and an adaptive shuffled frog-leaping algorithm is presented. Secondly, hybrid flow shop scheduling problems with batch processing machines at a middle stage is solved, which exists extensively in casting process. An adaptive artificial bee colony algorithm is applied to minimize maksepan. A lower bound is also provided for makespan. Finally, energy-efficient hybrid flow shop scheduling problems with batch processing machines is solved by using a feedback artificial bee colony algorithm. The objectives are makespan, total tardiness and total energy consumption.
Biography: Deming Lei received his PhD degree in Department of Automation from Shanghai Jiaotong University of China in 2005 and he was a Post Doctor in Wuhan University of Technology from January 2006 to January 2008. He is now a professor and doctoral supervisor of the School of Automation, Wuhan University of Technology. He has been engaged in intelligent optimization, scheduling and control for intelligent systems for a long time, and has published more than 80 papers in SCI journals. He is Highly Cited Chinese Researches since 2014. He served as Editorial Board Member for two SCI Journals and a Chinese Journal, which are Computers, Materials & Continua, Symmetry, Control and Information Technology.
