Distributed Model Predictive Control of the Multi-Agent Systems with Improving Control Performance. (5th April 2012)
- Record Type:
- Journal Article
- Title:
- Distributed Model Predictive Control of the Multi-Agent Systems with Improving Control Performance. (5th April 2012)
- Main Title:
- Distributed Model Predictive Control of the Multi-Agent Systems with Improving Control Performance
- Authors:
- Shanbi, Wei
Yi, Chai
Penghua, Li - Other Names:
- Xi Yugeng Academic Editor.
- Abstract:
- Abstract : This paper addresses a distributed model predictive control (DMPC) scheme for multiagent systems with improving control performance. In order to penalize the deviation of the computed state trajectory from the assumed state trajectory, the deviation punishment is involved in the local cost function of each agent. The closed-loop stability is guaranteed with a large weight for deviation punishment. However, this large weight leads to much loss of control performance. Hence, the time-varying compatibility constraints of each agent are designed to balance the closed-loop stability and the control performance, so that the closed-loop stability is achieved with a small weight for the deviation punishment. A numerical example is given to illustrate the effectiveness of the proposed scheme.
- Is Part Of:
- Journal of control science and engineering. Volume 2012(2012)
- Journal:
- Journal of control science and engineering
- Issue:
- Volume 2012(2012)
- Issue Display:
- Volume 2012, Issue 2012 (2012)
- Year:
- 2012
- Volume:
- 2012
- Issue:
- 2012
- Issue Sort Value:
- 2012-2012-2012-0000
- Page Start:
- Page End:
- Publication Date:
- 2012-04-05
- Subjects:
- Control theory -- Periodicals
629.831205 - Journal URLs:
- https://www.hindawi.com/journals/jcse/ ↗
- DOI:
- 10.1155/2012/313716 ↗
- Languages:
- English
- ISSNs:
- 1687-5249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 11160.xml