• Journal of Power Electronics
• /
• v.5 no.2
• /
• pp.129-141
• /
• 2005

A high-performance robust hybrid speed controller for a permanent-magnet synchronous motor (PMSM) drive with an on-line trained neural-network model-following controller (NNMFC) is proposed. The robust hybrid controller is a two-degrees-of-freedom (2DOF) integral plus proportional & rate feedback (I-PD) with neural-network model-following (NNMF) speed controller (2DOF I-PD NNMFC). The robust controller combines the merits of the 2DOF I-PD controller and the NNMF controller to regulate the speed of a PMSM drive. First, a systematic mathematical procedure is derived to calculate the parameters of the synchronous d-q axes PI current controllers and the 2DOF I-PD speed controller according to the required specifications for the PMSM drive system. Then, the resulting closed loop transfer function of the PMSM drive system including the current control loop is used as the reference model. In addition to the 200F I-PD controller, a neural-network model-following controller whose weights are trained on-line is designed to realize high dynamic performance in disturbance rejection and tracking characteristics. According to the model-following error between the outputs of the reference model and the PMSM drive system, the NNMFC generates an adaptive control signal which is added to the 2DOF I-PD speed controller output to attain robust model-following characteristics under different operating conditions regardless of parameter variations and load disturbances. A computer simulation is developed to demonstrate the effectiveness of the proposed 200F I-PD NNMF controller. The results confirm that the proposed 2DOF I-PO NNMF speed controller produces rapid, robust performance and accurate response to the reference model regardless of load disturbances or PMSM parameter variations.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.29 no.3
• /
• pp.45-53
• /
• 2015

A I-V and P-V characteristic of solar cell is changed to nonlinear by radiation and temperature. Therefore, to use efficiently PV system, operating point of PV system is must operate at maximum power point always. A performance of conventional the PO and the IC method is depend on the step size. So it has weakness which is must select optimal step size. Also, MPPT control applying PI and fuzzy control is not expected satisfactory performance, because of PI controller has fixed gain and fuzzy control has cumulative error by an integral calculus. Therefore, this paper proposes the VS-PO(Variable Stepsize - Perturbation & Observation) MPPT control that is automatically adjusted the step size according to the operating conditions. The VS-PO MPPT method proposed in this paper analyzes control characteristic about condition of radiation and compares with conventional methods. The validity of this paper proves using this results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.18 no.6
• /
• pp.84-90
• /
• 2004

Many control techniques have been proposed in order to improve the control performance in the control system. In the feedback control system the output of controller is generally used as the input of a plant But the undesired noise is included in the output of a controller. Therefore, there is a need to use a precompensator for rejecting the undesired noise and improving the response characteristic of a system. In this paper, the design method of a precompensator is proposed for the model following control in the I-PD control system. The proposed precompensator is implemented with a neural network. The games of a precompensator are adjusted automatically to obtain a desired response of a system when the response characteristic of a system is changed under a condition.