Abstract
This paper presents a controller design for shaping conditional output probability density functions (pdf) for non-Gaussian dynamic stochastic systems whose coefficients are random and represented by their known pdfs. The moment-generating function is applied to all the pdfs, leading to a simple mathematical relationship amongst all the transferred conditional pdfs of the system output and random parameters. A new performance function is introduced and its minimisation is performed so as to design an optimal control input that makes the shape of the conditional output pdf follow a target distribution. An example is included to illustrate the use of the algorithm. Copyright © 2011 Inderscience Enterprises Ltd.
Original language | English |
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Pages (from-to) | 82-94 |
Number of pages | 12 |
Journal | International Journal of Systems, Control and Communications |
Volume | 3 |
Issue number | 1 |
DOIs | |
Publication status | Published - Mar 2011 |
Keywords
- Dynamic stochastic systems
- Gradient-based optimisation
- Probability density functions
- The moment-generating function