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Compensation for Time Delay in Closed-Loop Shape Control System of Cold Rolling Mill

Author: SunFu
Tutor: WangYiQun
School: Yanshan University
Course: Mechanical and Electronic Engineering
Keywords: Plate - shaped closed-loop control Lag compensation Smith Predictor PID neural network Internal Model Control
CLC: TG335.5
Type: Master's thesis
Year: 2008
Downloads: 170
Quote: 2
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Abstract


Plate shape is an important indicator to measure the quality of cold-rolled strip, influenced by many factors, the complexity of the relevant law. With the growth of the demand on the strip, relying solely on simple artificial pre-set control mode has been difficult to meet production needs, on the basis of pre-set plate-shaped closed loop automatic control problems to be solved. In the closed-loop control, flatness detection signal lag Shapemeter some distance away from the strip at the exit, so that the entire control system to become a the hysteresis control system, increase the difficulty of control. Hysteresis control itself is the problem of the control sector, has yet to put forward a common set of mature controller design, lag compensation method in the study plate-shaped closed-loop control, automatic control of plate-shaped, has important theoretical significance and practical application value. This paper systematically studied the 300mm roller cold with closed loop control system constitutes reversible mill shape. A direct impact on the dynamic characteristics of the shape control means control the effect of the system, and thus targeted roll bending and roll roller system. In order to accurately obtain their dynamic behavior, first by the method of theoretical analysis, the establishment of the mechanism model, a priori knowledge of system identification, followed by screening a large number of step response data, the use of off-line identification method and Matlab Identification Toolbox, to be more realistic system discrete model, to lay the foundation for the controller design. Traditional Smith predictor lag compensation, but because it is estimated linear mathematical model lag time system into a non-lag time system, so there is strong dependence of the model, to adapt to the difference defects. Adaptive and self-learning ability of the neural network can undoubtedly make up for this deficiency, its complex structure, however, tedious calculations has seriously hampered the efficiency of the implementation, it is difficult to be applied to the real-time requirements engineering practice. In order to ensure real-time and adaptive design a single neuron PID Smith predictor and online learning neural network internal model controller. Simulation results show that the selected method can effectively make up for the shortcomings of the Smith predictor, get a good system performance. Will be applied to the actual rolling process, the results show that the designed controller has better adaptability than the traditional Smith predictor, more stable control.

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CLC: > Industrial Technology > Metallurgy and Metal Craft > Metal pressure processing > Rolling > Rolling process > Sheet, strip,foil rolling
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