Abstract
The speed and tension control problem of a web handling system is investigated in this paper. From the system equations of motion, we developed a backstepping-sliding mode control for web speed and tension regulation tasks. It is obvious that the designed control depends heavily on roll inertia information. Dissimilar to other researches that were based on the assumptions of rolls with perfect cylindrical form with the rotating shafts of the rolls considered properly aligned, the novelty of this paper is the presentation of a neural network to compensate the effects of imperfect roll arrangement. The neural network design is based on the Radial Basis Function (RBF) network estimating the uncertainty of roll inertia. The information on estimated inertia is fed into a backstepping-sliding mode controller that ensures tension and velocity tracking. The control design is presented in a systematical approach. Closed loop system stability is proven mathematically. The tracking performance is shown through several simulation scenarios.
Highlights
Numerous practical applications associated with web handling systems such as flexible displays, color-shifting, lighting, solar cells, etc. utilizing Roll-to-Roll (R2R) systems are becoming prevalent in industry [1,2,3,4,5]
By taking the advantages of Backstepping and Sliding Mode Control (BSMC) [21], a new control approach which uses BSMC integrated with an Radial Basis Function (RBF) neural network [22] (RBFN-BSMC) is proposed for the building of an R2R adaptive control system considering the presence of imperfection roll arrangements
Keeping in mind that full information of the roll to roll model is difficult to be obtained in real conditions, RBFN-BSMC law is more suitable for industrial applications than BSMC
Summary
Numerous practical applications associated with web handling systems such as flexible displays, color-shifting, lighting, solar cells, etc. utilizing Roll-to-Roll (R2R) systems are becoming prevalent in industry [1,2,3,4,5]. The control shows robustness against varying roll radius and inertia. It is strictly essential to develop an adaptive controller that deals with the problem of varying roll inertia for the control of the R2R systems. By taking the advantages of Backstepping and Sliding Mode Control (BSMC) [21], a new control approach which uses BSMC integrated with an RBF neural network [22] (RBFN-BSMC) is proposed for the building of an R2R adaptive control system considering the presence of imperfection roll arrangements. The contribution of this paper can be summarized as: i) the proposal of a nonlinear backstepping-sliding mode control for web handling systems, ii) the realization of an RBF based adaptive mechanism for compensating roll inertia uncertainty
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