On-line evolution of robust control systems: an industrial active magnetic bearing application

摘要

An electrical pump running on active magnetic bearings (AMBs) is described. To overcome the difficulty of obtaining an accurate model of the system, the control system is designed on-line. An optimiser modifies controller parameters running on the controller (a digital signal processor) in real time and the resulting sensor data is recorded and processed. On-line optimisation of the controller is achieved from within a commercial CACSD software package using H, and H. measures of tracking as design objectives. A multiobjective genetic algorithm is used to drive the optimisation for the AMB system. The resulting controller is compared with that of a manually tuned controller and significant improvements in performance and robustness are observed.