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The model-free direct adaptive generalized predictive control approach of permanent magnet linear motor

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3 Author(s)
A. Rongmin Cao ; School of Industry, China Agricultural University, Beijing 100083, China ; B. Huixing Zhou ; C. Zhongsheng Hou

In this paper, a model-free direct adaptive nonlinear predictive control (MFDANPC) algorithm of linearization of tight format of a class of SISO based on a generalized predictive control (GPC) is applied to permanent magnet linear motor speed and position control. The design of controller is based directly on estimate and prediction of pseudo-partial-derivatives (PPD) derived on-line from the input and output information of the motor motion model using a novel parameter estimation algorithm, predicted by approach for multi-degree prediction. Stability, validity and robustness against exogenous disturbance are proved for nonlinear systems with vaguely known dynamics by the simulation examples and real experiments.

Published in:

Electrical Machines and Systems, 2009. ICEMS 2009. International Conference on

Date of Conference:

15-18 Nov. 2009