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Active Disturbance Rejection Control for Web Tension Regulation and Control

2001 IEEE Conference on Decision and Control

Brian Thomas Boulter
Applied Industrial Control Solutions LLC
4597 E Sprague Rd.
Independence, OH, USA 44131

Y. Hou, Z. Gao, F. Jiang ,
Department of Electrical and Computer Engineering
Cleveland State University, Cleveland Ohio, 44115

© ApICS ® LLC 2001

Abstract: A new web-handling control method is proposed for tension control of a web transport system. It is based on a unique active disturbance rejection control (ADRC) strategy, which actively compensates for dynamic changes in the system, and unpredictable external disturbances. A simulation of an industrial application is used to provide realism. The results show the effectiveness of the proposed tension controller in coping with large dynamic variations commonly seen in web tension applications. The remarkable disturbance rejection capability of an ADRC is also demonstrated.

Tension controls are widely used in web transport and strip processing systems. These systems either feed material from an unwinder (or tension reel) into a process for secondary processing, or wind processed material for storage or final shipment on a winder. The main purpose of web tension regulation is to maintain the physical integrity of the material that is being processed.

The tension control problem in strip & web processing applications is a complex one because the system dynamics are a function of many process variables that often vary over a wide range. For example, in rolling mills, these variations include changes in roll diameter, product density, web/strip modulus of elasticity, web/strip cross sectional area, the inner speed loop bandwidth and process line-speed. Due to their difficulty and importance in industry, tension problems have drawn the attention of many researchers. One problem is the establishment of a proper mathematical model. Campbell [1] and Brandenburg [2] studied the longitudinal dynamics of a moving web. Campbell developed a mathematical model of a web span but did not consider the tension in the entering span, therefore his model does not predict "tension transfer". This problem was addressed by Brandenburg and Shelton [3], with the assumption that the strain in the web is very small. Brandenburg’s work took into consideration the effects of small changes in area that result from strain changes, temperature changes, and register errors.

There are two approaches used in web processing industries for tension control: open-draw or open loop control and closed-loop control. In the "draw control" scheme, tension in a web span is controlled in an open-loop fashion by controlling the velocities of the rollers at either end of the web span. W. Wolfermann and D. Schroder [4][5] used an optimal output feedback method to control the speed of the driven rollers. A decentralized observer was designed to decouple the drives from the web tension acting on the driven rollers and this information is used to improve the speed control of the driven rollers. This method leads to considerable improvement in the speed responses of the driven rollers. An inherent drawback of indirectly controlling tension through speed control is its dependency on the open loop relationship between the speed and tension. This control method cannot reject disturbance due to "tension transfer" from adjacent web spans and interaction between adjacent web spans through an intermediate driven roller. Note that tension is also affected by the change in temperature, material, thickness, as well as other operating variables. It is also very sensitive to noise in the speed feedback devices.

The proportional-integral-derivative (PID) control approach is the primary feedback control law used in industry. For tension feedback control, however, because of the significant variations in system dynamics, PID alone has been shown to be inadequate. K. Reid, K. Shin and K. Lin [6][7][8] proposed the fixed-gain and variable-gain PID control of web tension in the winding section. For variable gain PID, the control parameters are continuously updated based on the diameter of the roller, which is a major contributor to the system dynamics. This method uses pole placement techniques.

In this paper, we proposed a new methodology for web tension regulation. It is based on a unique active disturbance rejection control (ADRC) concept. In this approach the disturbances are estimated using an extended state observer (ESO) and compensated in each sampling period. This method was developed by J. Han [9]. A survey paper of this and similar results is available upon request [10]. The proposed ADRC control system consists of the ESO and a nonlinear PD controller. It is designed without an explicit mathematical model of the plant. The controller is designed to be inherently robust against plant variations. Once it is set up for a class of problems within a predetermined range of variation in system variables, no tuning is needed for start up, or to compensate for changes in the system dynamics and disturbance. This method, because of its robustness and disturbance rejection capabilities, is particularly suitable for web tension regulation applications.

In Section II, the web tension problem is introduced. Details of the ADRC control approach is given in Section III. Simulation results based on a simplified linear model and an industrial strip processing application are given in Section IV. Finally, concluding remarks are included in Section V.

V. Conclusion

A new web tension control method is proposed. The Active Disturbance Rejection Controller (ADRC) is applied to deal with significant dynamic change in the web transport process. The new control algorithm in digital form is simulated on a simulation of an industrial process with very encouraging results. We believe that this is a promising new technology for web applications because 1) it’s intuitive; 2) it does not require explicit mathematical models of the plant under control; 3) it is inherently robust. It was shown that once the ADRC controller is setup properly, it can handle a large range of dynamic changes. High sampling rates result in a tremendous improvement in the ADRC control performance.

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