Recent Progress in Reinforcement Learning and Adaptive Dynamic Programming for Advanced Control Applications
Beijing University of Technology · Southern University of Science and Technology · +3 more institutions
Abstract
Reinforcement learning (RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming (ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively. Then, the research progress on adaptive critic control based on the event-triggered framework and under…
Citation impact
- FWCI
- 51.94
- Percentile
- 100%
- References
- 155
Authors
5Topics & keywords
- Reinforcement learning
- Computer science
- Dynamic programming
- Control (management)
- Adaptive control
- Event (particle physics)
- Optimal control
- Adaptation (eye)
- Clean water and sanitation