Abstract
Language | English |
---|---|
Pages | 93-105 |
Number of pages | 13 |
Journal | Transactions of the Institute of Measurement and Control |
Volume | 25 |
Issue number | 2 |
DOIs | |
Publication status | Published - 2003 |
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Keywords
- stochastic systems
- rational spline model
- dynamic stochastic systems
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A rational spline model approximation and control of output probability density functions for dynamic stochastic systems. / Wang, H.; Yue, H.
In: Transactions of the Institute of Measurement and Control, Vol. 25, No. 2, 2003, p. 93-105.Research output: Contribution to journal › Article
TY - JOUR
T1 - A rational spline model approximation and control of output probability density functions for dynamic stochastic systems
AU - Wang, H.
AU - Yue, H.
PY - 2003
Y1 - 2003
N2 - This paper presents a new method to model and control the shape of the output probability density functions for dynamic stochastic systems subjected to arbitrary bounded random input. A new rational model is proposed to approximate the output probability density function of the system. This is then followed by the design of a novel nonlinear controller, which guarantees the monotonic decreasing of the functional norm of the difference between the measured probability density function and its target distribution. This leads to a desired tracking performance for the output probability density function. A simple example is utilized to demonstrate the use of the proposed modelling and control algorithm and encouraging results have been obtained.
AB - This paper presents a new method to model and control the shape of the output probability density functions for dynamic stochastic systems subjected to arbitrary bounded random input. A new rational model is proposed to approximate the output probability density function of the system. This is then followed by the design of a novel nonlinear controller, which guarantees the monotonic decreasing of the functional norm of the difference between the measured probability density function and its target distribution. This leads to a desired tracking performance for the output probability density function. A simple example is utilized to demonstrate the use of the proposed modelling and control algorithm and encouraging results have been obtained.
KW - stochastic systems
KW - rational spline model
KW - dynamic stochastic systems
U2 - 10.1191/0142331203tm076oa
DO - 10.1191/0142331203tm076oa
M3 - Article
VL - 25
SP - 93
EP - 105
JO - Transactions of the Institute of Measurement and Control
T2 - Transactions of the Institute of Measurement and Control
JF - Transactions of the Institute of Measurement and Control
SN - 0142-3312
IS - 2
ER -