๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

A comparison of five algorithms for the training of CMAC memories for learning control systems

โœ Scribed by P.C. Parks; J. Militzer

Publisher
Elsevier Science
Year
1992
Tongue
English
Weight
781 KB
Volume
28
Category
Article
ISSN
0005-1098

No coin nor oath required. For personal study only.

โœฆ Synopsis

First, the cerebellar model articulation controller (CMAC), invented in the early 1970s by AIbus, and the associative memory system (AMS), developed for learning control systems by H. Tolle et al. in the early 1980s, are briefly described. The underlying mathematics of the AMS learning or training algorithm is then given with a geometrical interpretation from which its convergence properties may be deduced. These are illustrated for some simple cases.

The original algorithm devised by Albus is very simple to compute but is slow to converge, and the second part of the paper investigates various algorithms with improved convergence properties. One of these, the so-called "maximum error" algorithm, is particularly recommended.

๐Ÿ“œ SIMILAR VOLUMES

Robustness and convergence rate of a dis
Robustness and convergence rate of a discrete-time learning control algorithm for a class of nonlinear systems
โœ Samer S. Saab ๐Ÿ“‚ Article ๐Ÿ“… 1999 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 127 KB ๐Ÿ‘ 2 views

In this paper, we apply a discrete-time learning algorithm to a class of discrete-time varying nonlinear systems with a$ne input action and linear output having relative degree one. We investigate the robustness of the algorithm to state disturbance, measurement noise and reinitialization errors. We