<p><p>This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for n
Nonlinear and nonnormal filters using Monte Carlo methods
โ Scribed by Hisashi Tanizaki
- Year
- 1996
- Tongue
- English
- Leaves
- 23
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
In this paper, a non-linear and non-normal filter using Monte Carlo simulation techniques is proposed, where the density function derived from the measurement equation and the random draws of the state-vector generated from the transition equation are utilized. The proposed filter has less computational burden and easier programming than the other non-linear and non-normal filters such as the numerical integration procedure and the Monte Carlo integration approach. Furthermore, the proposed filtei is extended to prediction and smoothing algorithms. Finally, by Monte Carlo experiments, wc compare the non-linear and non-normal procedures.
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