Refined Anti-Disturbance Control and Applications for UAVs: Green, Immunity and Survival
School of Automation Science and Electrical Engineering, Beihang University (BUAA), Beijing, China
Head, Center for Aircraft Intelligence Autonomous Systems
UAVs have shown wide applicability in diverse domains and make changes in our daily life. However, safety and “survival” of UAVs under disturbances, accidents, and failures, has become one of the most challenging problems. In this presentation, we will provide an overview of recent developments of refined anti-disturbance control (RADC) methodologies for multiple disturbance systems and will introduce applications of RADC for UAVs functioning in complex environments.
The RADC theory, including multiple-disturbance modeling, disturbance observer, and composite hierarchical anti-disturbance control (CHADC) methods, has been successfully utilized in practical applications since 2005, especially in motion control. It will be shown that RADC can deal with “extreme” environments exhibiting multiple disturbances and other uncertainties, possible sudden changes, degradations, failures, and faults. The revised and unified RADC design framework is established via modelling, analysis of anti-disturbance capability, disturbance compensation/absorption and attenuation, and task reconfiguration. The principle of disturbance dynamic regulation is presented instead of the well-known disturbance invariance principle. This is also different from the traditional anti-disturbance control tools involved in internal stability analysis and single performance indexes.
For an autonomous system, to a large extent, intelligence reflects the ability to deal with disturbances and uncertainties. Firstly, RADC will realize a “green” anti-disturbance control strategy with both less-conservative anti-disturbance capability and energy conservation ability. For multiple possible disturbances/failures, the “immune” intelligent strategy for UAVs by using RADC will be presented, which includes the links of diagnosis, recognition, cancellation, inhibition, adaptation, regulation in the context of bionics. To enhance the intelligence of UAVs, RADC will be applied to guarantee safety and “survival” under the above-mentioned extreme environments. Experiments will demonstrate applicability and effectiveness.
Biography: Prof. Lei GUO was born in Qufu, China. He received his BS and MS degree both from Qufu Normal University, in 1988 and 1991, respectively, and the PhD degree from Southeast University, Nanjing, in 1997. From 1999 to 2003, he was a research associate/fellow with the IRCCyN, France, Loughborough University, and University of Manchester Institute of Science and Technology (UMIST), UK. Currently, he is a distinguished professor with the School of Automation Science and Electrical Engineering, Beihang University (BUAA), China. He is an awardee of National Natural Science Award, National Technological Invention Award, the National Science Fund for Distinguished Young Scholars of China, and the Changjiang Distinguished Professor of the Ministry of Education of China. He is the director of the Technical Committee on Navigation, Guidance and Control, and the deputy director of the Technical Committee on Adaptive Dynamic Programming and Reinforcement Learning, of Chinese Association of Automation. He has published more than 220 papers and 5 monographs and has authorized more than 90 patents. His research interests include anti-disturbance control and its applications in aerospace systems.