Research on a new high accuracy controller for periodic motion

In this paper, according to the characteristics of the periodic motion, incorporating the grey prediction, repetitive control and the conventional PID control, a design method of the Grey prediction Repetitive PID control algorithm (GRPID) is presented for the first time. The hybrid control algorithm can estimate unsure parameters and disturbance of system using grey prediction, and compensate control in terms of the prediction results, and this may improve control quality and robustness of repetitive control for controlling periodic motion. The simulation results show that this algorithm has better performances than that of the conventional repetitive control system. It indicates the control method has better application effect for motion taking on a characteristic of periodic motion.

[1]  M. Tomizuka,et al.  Digital control of repetitive errors in disk drive systems , 1990, IEEE Control Systems Magazine.

[2]  Zhang Ke,et al.  Dynamics Analysis of a Controllable Mechanism , 2005 .

[3]  Masayoshi Tomizuka,et al.  Plug in repetitive control for industrial robotic manipulators , 1990, Proceedings., IEEE International Conference on Robotics and Automation.

[4]  Jyh-Horng Chou,et al.  Application of the Taguchi-genetic method to design an optimal grey-fuzzy controller of a constant turning force system , 2000 .

[5]  Masayoshi Tomizuka,et al.  Adaptive And Repetitive Digital Control Algorithms for Noncircular Machining , 1988, 1988 American Control Conference.

[6]  Masayoshi Tomizuka,et al.  Adaptive Pulse Width Control for Precise Positioning Under the Influence of Stiction and Coulomb Friction , 1988 .

[7]  Shih-Wen Hsiao,et al.  A morphing method for shape generation and image prediction in product design , 2002 .

[8]  Shiuh-Jer Huang,et al.  Application of grey predictor and fuzzy speed regulator in controlling a retrofitted machining table , 1996 .

[9]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[10]  Masayoshi Tomizuka,et al.  Discrete-Time Domain Analysis and Synthesis of Repetitive Controllers , 1988, 1988 American Control Conference.

[11]  Danwei Wang,et al.  Digital repetitive learning controller for three-phase CVCF PWM inverter , 2001, IEEE Trans. Ind. Electron..

[12]  Toru Omata,et al.  Nonlinear repetitive control with application to trajectory control of manipulators , 1987, J. Field Robotics.

[13]  Bruce A. Francis,et al.  The internal model principle of control theory , 1976, Autom..

[14]  Li-Chang Hsu,et al.  Applying the Grey prediction model to the global integrated circuit industry , 2003 .

[15]  Deng Ju-Long,et al.  Control problems of grey systems , 1982 .

[16]  Tsu-Chin Tsao,et al.  Rejection of unknown periodic load disturbances in continuous steel casting process using learning repetitive control approach , 1996, IEEE Trans. Control. Syst. Technol..

[17]  Tsu-Chin Tsao,et al.  Periodic Sampling Interval Repetitive Control and Its Application to Variable Spindle Speed Noncircular Turning Process , 2000 .

[18]  Shiuh-Jer Huang,et al.  A fuzzy controller with grey prediction for robot motion control , 1998, Int. J. Syst. Sci..

[19]  Michio Nakano,et al.  High Accuracy Control of a Proton Synchrotron Magnet Power Supply , 1981 .

[20]  Keliang Zhou,et al.  Zero-phase odd-harmonic repetitive controller for a single-phase PWM inverter , 2006, IEEE Transactions on Power Electronics.

[21]  H. L. Broberg,et al.  Reduction of repetitive errors in tracking of periodic signals: theory and application of repetitive control , 1992, [Proceedings 1992] The First IEEE Conference on Control Applications.