Adaptive control of a class of first order nonlinear systems without a priori information on the plant parameters

1990 ◽  
Author(s):  
R. Lozano-Leal ◽  
B. Brogliato
Keyword(s):  
Adaptive Control ◽  
Nonlinear Systems ◽  
A Priori ◽  
A Priori Information ◽  
First Order ◽  
Priori Information

Signal Based Methods to Extract A Priori Information for the Identification of Nonlinear Systems

2001 ◽  
Author(s):  
Jens-Uwe Bruns ◽  
Karl Popp
Keyword(s):  
Nonlinear Systems ◽  
Nonlinear Dynamical Systems ◽  
A Priori ◽  
A Priori Information ◽  
Nonlinear Dynamical ◽  
Additional Information ◽  
System States ◽  
Priori Information ◽  
System Order

Abstract The identification of nonlinear dynamical systems still is a non-trivial procedure. Signal based methods that retrieve basic information about the system prior to detailed identification can provide valuable assistance in this task. In the paper the detection and characterization of nonlinearities as well as the estimation of the system order are discussed. Regarding the first topic, a new method is presented that is based on the Method of Internal Harmonics Cross-Correlation by Dimentberg and Sokolov but provides additional information about the nature of the nonlinearity and uses nonlinear instead of linear correlation. Concerning the second topic, a method is presented that, in contrast to most existing methods for nonlinear systems, incorporates a random input signal to promote the excitation of all system states. Both methods are illustrated with numerical examples.

scholarly journals Analysis of Mismatched First Order A Priori Information in Iterative Source-Channel Decoding

10.14311/980 ◽  
2007 ◽  
Vol 47 (4-5) ◽  
Author(s):  
B. Schotsch ◽  
P. Vary ◽  
T. Clevorn
Keyword(s):  
Error Concealment ◽  
Source Coding ◽  
A Priori ◽  
Quality Improvements ◽  
A Priori Information ◽  
Channel Decoding ◽  
First Order ◽  
Index Assignment ◽  
Priori Information ◽  
Residual Redundancy

Due to complexity and delay constraints a usually significant amount of residual redundancy remains in the source samples after source coding. This residual redundancy can be exploited by iterative source-channel decoding for error concealment and quality improvements. One key design issue in joint source-channel (de-)coding is the index assignment. Besides conventional index assignments optimized index assignments have been developed, e.g., considering zeroth or first order a priori information of the source samples. However, in real-world scenarios it is unlikely that the amount of residual redundancy is constant over time and thus it may occur that the just deployed index assignment is suboptimal at times when the residual redundancy differs too much from the amount that it is optimized for. In this paper the performance of optimized index assignments is examined that consider first order a priori knowledge under such suboptimal conditions. 

Sign in / Sign up

Export Citation Format

Share Document