DocumentCode
3150295
Title
Notice of Violation of IEEE Publication Principles
Intelligent Control Using Online Stability-Based Knowledge Representation
Author
Yunpeng, Ma
Author_Institution
Sch. of Aeronaut. Sci. & Eng., BeiHang Univ., Beijing, China
fYear
2009
fDate
28-30 Dec. 2009
Firstpage
428
Lastpage
431
Abstract
Notice of Violation of IEEE Publication Principles
"Intelligent Control Using Online Stability-Based Knowledge Representation"
by Yunpeng Ma
in the Proceedings of the Second International Conference on Environmental and Computer Science (ICECS), December 2009, pp. 428-431
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
This paper is a near verbatim copy of the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"Intelligent Control Using Online Stability-Based Knowledge Representation"
by Fan Zhang and Dirk Soffker
in the Proceedings of the 6th Vienna Conference on Mathematical Modelling, February 2009, pp. 200-208
In this paper, a new concept for intelligent control of stability in technical systems is proposed based upon the Situation-Operator-Model-based cognitive architecture of autonomous system. The novelty of the proposed method is that the controller can accomplish the task of control without knowing the detailed structure of the system plant, nor its physical behavior, because all the information needed in the control are gained by studying the phase portrait during the interaction process between the system and the environment, with the help of the static knowledge about the stability and the goal of control. Furthermore, the performance of the control is improved according to the experiences of the controller which are gained by the cognitive functions and stored in the learned knowledge base. These two features are realized within the framework built up by Sit- uation-Operator-Model approach to represent the reality. An example of stabilizing a pendulum with unknown impulse disturbances is utilized to illustrate the approach.
"Intelligent Control Using Online Stability-Based Knowledge Representation"
by Yunpeng Ma
in the Proceedings of the Second International Conference on Environmental and Computer Science (ICECS), December 2009, pp. 428-431
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
This paper is a near verbatim copy of the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"Intelligent Control Using Online Stability-Based Knowledge Representation"
by Fan Zhang and Dirk Soffker
in the Proceedings of the 6th Vienna Conference on Mathematical Modelling, February 2009, pp. 200-208
In this paper, a new concept for intelligent control of stability in technical systems is proposed based upon the Situation-Operator-Model-based cognitive architecture of autonomous system. The novelty of the proposed method is that the controller can accomplish the task of control without knowing the detailed structure of the system plant, nor its physical behavior, because all the information needed in the control are gained by studying the phase portrait during the interaction process between the system and the environment, with the help of the static knowledge about the stability and the goal of control. Furthermore, the performance of the control is improved according to the experiences of the controller which are gained by the cognitive functions and stored in the learned knowledge base. These two features are realized within the framework built up by Sit- uation-Operator-Model approach to represent the reality. An example of stabilizing a pendulum with unknown impulse disturbances is utilized to illustrate the approach.
Keywords
intelligent control; knowledge representation; pendulums; stability; autonomous system; intelligent control; knowledge base; online stability-based knowledge representation; pendulum stabilization; phase portrait; situation-operator-model-based cognitive architecture; static knowledge; technical system; Cognitive science; Computer science; Control systems; Intelligent control; Knowledge engineering; Knowledge representation; Layout; Phase control; Phase detection; Stability; intelligent control; situation-operator-model; stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Environmental and Computer Science, 2009. ICECS '09. Second International Conference on
Conference_Location
Dubai
Print_ISBN
978-0-7695-3937-9
Electronic_ISBN
978-1-4244-5591-1
Type
conf
DOI
10.1109/ICECS.2009.9
Filename
5383475
Link To Document