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所属单位：自动化学院

发表刊物：Control Intell Syst

摘要：The significance of mathematical modelling in the classical control theory cannot be denied. However, the nonlinear system modelling is more complex than linear modelling and sometimes it is challenging to produce a nonlinear mathematical model of the system. The proposed work is mainly focused on data-driven virtual reference feedback tuning (VRFT) control combined with a model free adaptive control (MFAC) algorithm. The basic control structure of the VRFT system uses a close loop model as a reference. However, the input and output data model of the closed loop linear system is linearized in tight format. The reference model output error and the system expected output error are used as a control input. The estimated value of the pseudo partial derivative (PPD) in the past time is introduced to the new control law to improve the utilization rate of PPD. The whole performance of the controller design is essentially data driven and it does not demand any prior information about the system model. The VRFT-based MFA control system is applied to speed control of the permanent magnet DC motor in the Simulink platform. Moreover, the simulation results show that 8.6% speed tracking error is reduced using the proposed control algorithm as compared to VRFT and 4.7% is reduced as compared to MFA-based algorithms.

ISSN号：1480-1752

是否译文：否

发表时间：2017-01-01

合写作者：Masood, Rana J.,Manzoor, Muhammad F.

通讯作者：Masood, Rana J.,王道波,王道波