Title :
Robust on-line parameter identification with general knowledge on level of information noise: continuous and discrete cases
Author :
Lee, Fu-Ming ; Fu, Li-Ghen ; Fong, I. Kong
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
A robust on-line parameter identification problem is posed and solved for systems with general knowledge of the level of the inherent information noise. Both continuous-time and discrete-time cases are considered in this paper. For the former case, the knowledge can be the bound on either the magnitude or the finite-time Lp norm, p∈[1, ∞), of the noise. Whereas for the latter case, it can be the bound on either the magnitude or the finite-index lp norm, p∈[1, ∞), of the noise. Based on the knowledge, a switching type algorithm is proposed to estimate the parameters of the system from the available input-output data. In spite of the existence of the information noise, this on-line algorithm guarantees that the estimation error is monotonically decreasing, and the parameter estimate is convergent to a steady state value under a mild condition
Keywords :
continuous time systems; discrete time systems; noise; parameter estimation; continuous-time; discrete-time; estimation error; finite-index lp norm; finite-time Lp norm; information noise; mild condition; monotonically decreasing; robust online parameter identification; switching type algorithm; Chaos; Computer science; Estimation error; Information management; Noise level; Noise robustness; Parameter estimation; State estimation; Steady-state; Technology management;
Conference_Titel :
American Control Conference, Proceedings of the 1995
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2445-5
DOI :
10.1109/ACC.1995.532699