Identification and Control of Linear Stochastic Systems Using Spline Functions.
TEXAS UNIV AUSTIN ELECTRONICS RESEARCH CENTER
Pagination or Media Count:
The report discusses parameter identification and adaptive control of linear plants excited by white, Gaussian noise, the linear observations being made in the presence of additive white, Gaussian noise. The Bayesian approach is taken throughout this study. As this approach leads to identification and control schemes which cannot be implemented exactly, the spline functions are used to approximate these schemes very closely. These approximations are studied in detail and their performance is demonstrated by means of several examples.
- Statistics and Probability