Conference proceeding
A new approach to learning control via multiobjective optimization
Proceedings. 1991 IEEE International Conference on Robotics and Automation, v 3, pp 2434-2435
1991
Abstract
Summary form only given. Previous work where estimation of the parameters of a plant was incorporated through exploratory schedules (ESs) which are reference input trajectories designed to enhance the learning of system parameters, is extended. In that work, ESs were generated offline and used in an open-loop fashion. Moreover, these ESs were used in between actual control tasks, therefore limiting the process of estimation during idle time. In this work the authors present an approach for generating ESs in a closed-loop manner. Such trajectories in general may not be the desired trajectories, since they result in larger tracking errors. However, ESs offer faster convergence to the system parameters and therefore yield smaller long-term tracking errors. The automation for the design of ESs requires online modification of the desired trajectory to enhance learning at the expense of poorer initial tracking.< >
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Details
- Title
- A new approach to learning control via multiobjective optimization
- Creators
- A Guez - Drexel UniversityZ Ahmad - Drexel UniversityIEEE
- Publication Details
- Proceedings. 1991 IEEE International Conference on Robotics and Automation, v 3, pp 2434-2435
- Conference
- 1991 IEEE International Conference on Robotics and Automation
- Publisher
- IEEE Comput. Soc. Press
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:A1991BT14J00354
- Other Identifier
- 991019182655404721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Aerospace
- Engineering, Electrical & Electronic
- Physics, Applied