Analysis of Approximations to Dual Control
Author
Summary, in English
The dual control problem for time-varying or non-linear systems is inherently analytically and computationally untractable due to the demand of alternating minimizations and mean value computations. Hence, it has to be approached using approximations leading to suboptimal dual control. The core of the successful approximative controller is its ability to be able to consider future changes in the development of the parameters. This paper presents an analysis of the dual-control concept, and a comparison between a number of suboptimal controllers. The analytical comparisons are based on a reformulation of the dual-control problem. The reformulation makes it possible to interpret and understand the nature of the different approximations to dual control, in particular the Adaptive Predictive Controller (APC) and the Active Suboptimal Dual Controller (ASOD). Furthermore, it makes the origin of the computational problems encountered more clear, and suggests new alternatives for approximation. The analysis is carried through on relatively simple examples and is illustrated with simulations. The performance of the controllers when applied to more complicated time-varying systems is illustrated with simulations as well.
Publishing year
1999
Language
English
Pages
593-620
Publication/Series
International Journal of Adaptive Control and Signal Processing
Volume
13
Links
Document type
Journal article
Publisher
John Wiley & Sons Inc.
Topic
- Control Engineering
Keywords
- Dual control
- stochastic control
- stochastic systems
- time-varying systems
Status
Published
ISBN/ISSN/Other
- ISSN: 0890-6327