The paper describes an active magnetic bearing (AMB) system used in a high-speed energy storage flywheel. The conventional PID structure is used for the decentralised control of two radial magnetic bearings, and the control parameters are on-line tuned using a genetic algorithm (GA). The control and tuning are implemented on a digital signal processor, and the results of the optimisation are presented. The genetic algorithm has been used as a design tool for generating optimal active magnetic bearing controllers for a high speed flywheel energy storage system for use in electric vehicles. The optimization is performed directly on the AMB rig through a digital signal processor and an associated software interface with MATLAB/SIMULINK, and a comprehensive measure of AMB performance such as singular value of rotor response, is used as the objective for the optimization. In this way, a number of satisfactory controllers are generated which can be directly used for real-time applications. The improvement of control performance against the manually tuned controllers is clearly shown by experiments on a prototype DSP-controlled flywheel magnetic bearing system.
On-line GA auto-tuning of magnetic bearing controllers for a flywheel energy storage system
1999
4 Seiten, 10 Bilder, 6 Quellen
Aufsatz (Konferenz)
Englisch
Auto Tuning of PID Controllers
NTIS | 1993
|Neural Network Controller Design for a Magnetic Bearing Flywheel Energy Storage System
SAE Technical Papers | 1992
|Genetic auto-tuning of PID controllers
IET Digital Library Archive | 1995
|