Symposium on Optimal Guidance and Control for Autonomous Systems IUTAM on March 19-21, 2020 in Hawaiian Ocean View, United States
- Short Name: IUTAM
- Event Type: Conference
- Website URL: https://manoa.hawaii.edu/ISOGCAS2020/
- Contact URL: https://manoa.hawaii.edu/ISOGCAS2020/contact/
- Location: Hawaiian Ocean View, United States
- Date: March 19-21, 2020
- Organization: University of Hawaii
- Conference Tags: control control engineering control systems intelligent control microcontrollers control theory automatic control nonlinear control
The IUTAM Symposium on Optimal Guidance and Control for Autonomous Systems 2020 invites papers representing the results of research and studies in optimal guidance and control, and the utilities of these theoretical developments in the performance of autonomous systems.
Over the last two decades, the theories, concepts and methods of optimal control, calculus of variations, dynamic systems, motion stability, sensor fusion, optimal guidance and machine learning have contributed to paving the way to or to leveraging the autonomy of controllable systems, including space, air, surface and underwater vehicles, and swarm networks. Design, analysis and development of such systems have been associated with safety, stability, accuracy, autonomy, maneuverability, navigation and guidance problems, and their real-time or near real-time solutions, especially for performance in uncertain environments. These problems have been investigated via such conventional and non-conventional solutions methods and approaches as Lagrange and Hamilton-Jacobi- Bellmann’s formalisms, direct and indirect methods, and formalisms based on the sufficient conditions of absolute optimality. Analytical integrability of canonical systems, solvability of Hamilton-Jacobi equation, completeness of necessary and sufficient conditions of optimality, existence of Pontryagin minimum, synthesis of control regimes, real-time integration of optimal control, guidance, navigation and targeting are only some of the still remaining and underlying fundamental issues and challenges of leveraging the autonomy and optimization of the controllable systems. These solutions are critical to not only mission design and analysis, but also to the systems’ satisfactory performance. Utilities of these solutions have led to increased and strengthened requirements for motion planning, dynamics and performance of the onboard control systems or their components.
The symposium intends to bring together leading scientists, experts and engineers engaged in the development and application of novel concepts, theories and methods of optimal guidance and control, nonlinear dynamic systems and motion stability, sensor fusion and machine learning to discuss and address the issues relevant to theory and performance autonomous and other controllable systems. As such, this meeting represents a wide range of research and studies involving the theories and methods in the areas mentioned above, fundamental issues of autonomy and approaches to their solutions, and utility and implementation of these solutions in leveraging the autonomy of the controllable systems.
Scientific Commitee
Chair:
Full name: Dilmurat Azimov
Affiliation: University of Hawai’i at Manoa
City: Honolulu
Country: USA
Email: [email protected];
Member:
Full name: Corey Ippolito
Affiliation: NASA Ames Research Center
City: Moffett Field, CA
Country: USA
Member:
Full name: Peter Hagedorn
Affiliation: Technische Universität Darmstadt
City: Darmstadt
Country: Germany
Member:
Full name: Markus Landgraf
Affiliation: European Space Agency
City: Noordwijk
Country: The Netherlands
Member:
Full name: Yukihiro Kubo
Affiliation: Ritsumeikan University
City: Kyoto
Member:
Full name: Frederic Bonnans
Affiliation: Ecole Polytechnique
City: Palaiseau
Country: France
Member:
Full name: Andrei Dmitruk
Affiliation: Central Economics & Mathematics Institute, Russian Academy of Sciences
City: Moscow
Country: Russia
IUTAM Representative:
Full name: Peter Eberhard
Affiliation: IUTAM
City:
Country: Germany
Organizing Commitee (all at UH-Manoa, HI, USA):
Dilmurat Azimov
Zhuoyuan Song
Yingfei Dong
Evan Tengan
Evan Kawamura
Dylan Morrison-Fogel
Melissa Onishi
Minji Jo
Gang Yuan
Motion planning
Optimal Control
Optimal Guidance
Feedback control
Machine learning
Swarm network control
Centralized or decentralized control
Guidance, navigation and control (GNC)
Stability
Targeting
Data processing
Sensor fusion
On-board control systems and capabilities
Autonomous GNC
Name: University of Hawaii
Website: http://manoa.hawaii.edu
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