Abstract
This paper presents a new method for the modeling and control of the output probability density functions (PDFs) of linear stochastic systems. At first, a new PDF approximation method, namely the rational square-root B-spline model is proposed and the innovative concept of pseudoweights is introduced. The new model is then compared with the existing B-spline models in terms of feasible domains. Next, a controller is developed to realize the output PDF tracking performance. An alternative minimal entropy control strategy is also provided for the case that no target PDF is available. Finally, illustrative examples indicate the effectiveness of the proposed algorithms.
| Original language | English |
|---|---|
| Pages (from-to) | 343-351 |
| Number of pages | 9 |
| Journal | Acta Automatica Sinica |
| Volume | 31 |
| Issue number | 3 |
| Publication status | Published - 2005 |
Keywords
- dynamic stochastic systems
- probability density function (PDF)
- B-spline neural network
- robust control
- minimum entropy control