This paper describes the use of Universal Learning Networks (ULNs) in the identification and control of a separately excited de motor loaded with a centrifugal pump and fed from Photovoltaic (PV) generator via dc-dc buck-boost converter. The Universal Learning Network Identifier (ULNI) is trained offline using the forward propagation algorithm to emulate the dynamic behavior of the de motor system. Then this identifier is used, instead of the motor system, for the online training of the Universal Learning Network Controller (ULNC). As a result, the motor speed can follow all arbitrarily selected reference signal. Furthermore, the overall system call operate at the Maximum Power Point (MPP) of the PV generator. which is the optimal operating point. The simulation results showed a good performance for the identifier and the controller as well.
|ジャーナル||IFAC Proceedings Volumes (IFAC-PapersOnline)|
|出版物ステータス||Published - 2003 1 1|
|イベント||13th IFAC Symposium on System Identification, SYSID 2003 - Rotterdam, Netherlands|
継続期間: 2003 8 27 → 2003 8 29
ASJC Scopus subject areas
- Control and Systems Engineering