Geometric Analysis Based Double Closed-loop Iterative Learning Control of Output PDF Shaping of Fiber Length Distribution in Refining Process

Journal Article · Wed Nov 07 00:00:00 EST 2018 · IEEE Translations on Industrial Electronics

DOI:https://doi.org/10.1109/TIE.2018.2879293· OSTI ID:1482213

Li, Ming jie ^[1]; Zhou, Ping ^[1]; Wang, Hong ^[2]; Chai, Tianyou ^[3]

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1. Northeastern Univ., Liaoning (China)
2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
3. State Key Laboratory of Synthetical Automation for Process Industries (China)

In order to improve the pulp quality and to reduce the energy consumption, the fiber length distribution (FLD) is generally employed as one of the important technological indexes in the refining process. Considering that the traditional mean and variance of fiber length are unable to adequately characterize the non-Gaussian distribution properties, this paper proposes a novel geometric analysis based double closed-loop iterative learning control (ILC) method for probability density function (PDF) shaping of output FLD in the refining process. Primarily, a RBF neural network (NN) with Gaussian-type is utilized to approximate the square root PDF in the inner loop, where the RBF basis function parameters (center and width) are tuned between any two adjacent batches by using an ILC law, and the subspace identification method can be applied to establish the state-space model of weight vector. Then, for the sake of accelerating the convergence rate of the closed-loop sysyem, a geometric analysis based ILC method is adopted in the outer loop. Lastly, both simulation and experiments demonstrate the effectiveness and practicability of the proposed approach.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: 61290323, 61473064; AC05-76RL01830
• OSTI ID: 1482213
• Report Number(s): PNNL-SA-127287
• Journal Information: IEEE Translations on Industrial Electronics, Vol. 66, Issue 9; ISSN 0278-0046
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

42 ENGINEERING
Probability density function (PDF)
stochastic distribution control (SDC)
iterative learning control (ILC)
geometric analysis
fiber length distribution (FLD)
refining process