Fast incremental best estimate directed search-a significantly expedited algorithm for Takagi-Sugeno type fuzzy logic controller automatic optimization

Over the last few years, a series of cell state space based algorithms has been proposed for Takagi-Sugeno type fuzzy logic controller automatic optimization with promising results. The core algorithm is called incremental best estimate directed search (IBEDS), which is an implementation of the conc...

Full description

Saved in:
Bibliographic Details
Main Authors: Feijun Song, Smith, S.M.
Format: Conference Proceeding
Language:English
Subjects:
Automatic control
Computational modeling
Control systems
Controllability
Fuzzy logic
Modems
Optimized production technology
State-space methods
Weight control
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Over the last few years, a series of cell state space based algorithms has been proposed for Takagi-Sugeno type fuzzy logic controller automatic optimization with promising results. The core algorithm is called incremental best estimate directed search (IBEDS), which is an implementation of the concept called globally directed random search. Originally, IBEDS only applies global random search on the training set, this paper presents a new approach that applies global random search to both the training set and the controller parameter set to further speed up the optimization process. The simulation results with a 4D inverted pendulum show that the new approach is much faster than the original IBEDS when the initial training set is empty and the search needs to bootstrap itself.
DOI:10.1109/FUZZ.2001.1009092