Performance Enhancement of Learning Tracking Systems Over Fading Channels With Multiplicative and Additive Randomness
Abstract:
This paper applies learning control to repetitive systems over fading channels at both output and input sides to improve tracking performance without applying restrictive fading conditions. Both multiplicative and additive randomness of the fading channel are addressed, and the effects of fading communication on the data are carefully analyzed. A decreasing gain sequence and a moving-average operator are introduced to modify the generic learning control algorithm to reduce the fading effect and improve control system performance. Results reveal that the tracking error converges to zero in the mean-square sense as the iteration number increases. Illustrative simulations are presented to verify the theoretical results.
Related Concept Videos
Multiple Pipe Systems
Series Configuration
In a series configuration, fluid flows sequentially from one pipe...
Conjugate Addition (1,4-Addition) vs Direct Addition (1,2-Addition)
Conjugate addition results in a thermodynamically stable product. The reaction retains the stronger C=O bond at the expense of the weaker C=C π bond. The process is slow as the β carbon is less electrophilic than the carbonyl carbon.
Direct addition products are...
Random Error
Random Variables
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
Randomized Experiments
Simple randomization
Simple...
Conjugate Addition of Enolates: Michael Addition


