The process dynamics of filler retention in paper using a CPAM/bentonite retention aid system

In an effort to develop robust control strategies for the wet‐end of papermaking, an experimental program was carried out to model the dynamic behaviour of the filler retention in paper using a Fourdrinier pilot paper machine and a cationic poly(acrylamide)/bentonite retention aid system. A dynamic simulation model of the pilot paper machine was developed from first‐principles. To describe the wet‐end chemistry effect, the first‐pass retention was included in the model as a new independent variable. The important factors affecting the dynamics of the wet‐end are first‐pass retention and the parameters related to the white water circulation.     

Dynamics of Whitewater Consistency of a Pilot Paper Machine Using a PEO/Cofactor Retention Aid System

Experiments have been performed on a Fourdrinier pilot paper machine to characterize the behaviour of a Polyethylene Oxide (PEO) and Cofactor (CF) retention aid system under slow wire speed and very low shear conditions. Three wet‐end variables (PEO state of entanglement, PEO dosage and CF to PEO ratio) have been manipulated and the dynamic variations of whitewater consistency have been recorded. The identification of the dynamics shows that the three variables affect the whitewater consistency significantly. A semi‐empirical model based on mass balances has shown that the time constants of the system are determined by the mixing dynamics of the chemicals prior to the wire and by the whitewater recirculation loop dynamics. These findings have been confirmed by a dynamic simulation of the wet‐end section of the paper machine, which could be used to design advanced control strategies of this critical papermaking step.     

Extension of multiunit global optimisation to three‐input systems

Finding the global optimum of an objective function has been of interest in many disciplines. Recently, a global optimisation technique based on multiunit extremum seeking has been proposed for scalar and two‐input systems. The idea of multiunit extremum‐seeking is to control the gradient evaluated using finite difference between two identical units operating with an offset. For scalar systems, it was shown that the global optimum could be obtained by reducing the offset to zero. For two‐input systems, the univariate global optimisation is performed on the circumference of a circle of reducing radius. In this study, the concept is extended to three‐input systems where the circle of varying radius sits on a shrinking sphere. The key contribution lies in formulating the rotation required to keep the best point found in the search domain. The theoretical concepts are illustrated on the global optimisation of several examples. Comparison results with other competitive methods show that the proposed technique performs well in terms of number of function evaluations and accuracy. © 2011 Canadian Society for Chemical Engineering     

Dynamic simulation and control of a paper machine wet end

A good simulation model for paper machines can be used to identify deficiencies in the design, bottlenecks during operation, and regions of poor control. It also allows users to test their hypotheses and innovations without potentially causing major upsets and reducing throughput. In this work, a dynamic model of the wet end system has been developed using the IDEAS^TM platform, describing the distribution of fines, fillers and fibres throughout the system. The model was then tested at steady state with mill data for the low‐ash and high‐ash production grades, and the results show that over 70% of the predicted values had only 5% deviation. The dynamic simulation was also used to show that the retention aid controller would react in the wrong direction due to changes in the wire pit consistency and the stock ratio would cause major changes in stream compositions and consistencies of the wet end.     

模糊自适应PID控制算法在纸机烘缸蒸汽系统中的应用

介绍一种模糊自适应PID控制算法及其实现方法.它包含四个部分:①模糊自适应PID参数模型的整定;②模糊逻辑推理及PID参数修正方法;③模糊自适应PID控制算法的实现方法;④系统稳定性分析.该算法能够实现造纸机干燥部烘缸蒸汽温度按设定曲线控制.应用结果表明该算法合理,实现简单,烘缸干燥效果更佳.     

Influence of retention system and curing on paper wet strength improvement by a copolymer containing glycidyl groups

The copolymer (PGS) synthesized by polymerization of glycidyl methacrylate with styrene had a significant effect on paper wet strength. Factors such as retention aids, curing temperature, and curing time were investigated. The results showed that among four kinds of partially aminated poly N‐vinylformamide (APNVF), APNVF‐4 that had the highest charge density was the most effective for strengthening paper. The effectiveness of the retention systems increased with their wet functionality in the order APNVF‐4 > C‐PAM ≈ PAAm > PEI > PDADMAC. The curing temperature and curing time had little influence on paper dry strength, but they influenced paper wet strength greatly. The FTIR studies on model reactions showed that glycidyl groups could react with amino groups and carboxyl groups under common curing conditions. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 81: 2791–2797, 2001     

Extremum seeking control using a partial sum of input-output product

Recent extremum seeking control that uses a continuous perturbation and the integral feedback of perturbation- output product is based on a static nonlinear process. The method can be applied to dynamic nonlinear processes for tracking and maintaining the optimal operating points. It has several tuning parameters, such as the integral controller gain and the magnitude and frequency of the continuous perturbation signal. The frequency of the continuous perturbation signal should be low enough to ensure the time-scale separation between the real-time optimization and the process dynamics for the closed-loop stability. However, for some processes, fast perturbations are preferred because they can be attenuated easily in subsequent processes such as buffers and storages. For this, we propose an extremum seeking control method where the partial sum of perturbation-output product is used for a faster squarewave perturbation. Simulations for two processes of parallel competing reactions have been given, and a simple liquid level system to test extremum seeking control methods is suggested.     

五轴联动多功能微机控制纤维缠绕机控制系统的设计

本文根据纤维缠绕理论，从总体方案设计、基本性能、技术参数、实际运行效果、结构特点、计算机控制系统硬件和软件方面阐述了该控制系统在缠绕工艺及设备自动化方面的应用。     

一种新的纸机干燥部蒸汽冷凝水热泵控制系统

简要介绍纸幅干燥原理和热泵节能机理,设计一套基于S7—300PLC的五叠网涂布白板纸机蒸汽冷凝水热力控制系统,阐述具体的控制方案和采用的控制算法,其中主要包括热泵组的压力分段控制和热泵开度的低端选择控制、湿端低温段烘缸组压力回路分段控制、热烘箱二次蒸汽回收压力回路的分程控制和成纸水分的串级控制。实际应用效果表明该控制系统方案是可行的,同时也是有效的。     

The effect of borax‐modified starch on wheat straw‐based paper properties

This study was focused on the improvement of mechanical strength properties of wheat straw‐based paper through modification of wet‐end cationic starch with borax. Borax has been used extensively in many industrial applications for its unique physical and chemical properties. We investigated the strengthening effect of borax‐modified starch (BMS) as wet‐end paper strength additive on the mechanical strength properties especially the tensile strength of wheat straw‐based paper. Hand‐sheets made of typical wheat straw‐based papermaking furnish were investigated. Experimental results showed that BMS substantially increased the strength properties. Tensile index, elongation, tensile energy absorption, and wet tensile index were increased by 17%, 23%, 20%, and 21%, respectively. A short mill trial was also conducted on papermaking machine in which the impact of BMS on wheat straw‐based low grammage paper (<90 gsm) was investigated. The objective of mill trial was to reduce costly virgin softwood pulp content in wheat straw‐based paper recipe. Mill trial results showed similar trends in strength properties as in case of laboratory studies. Virgin softwood pulp was reduced from 30% to 25% in papermaking furnish. Furthermore, no sheet breaks were reported during trial which often happened due to poor strength of paper web. This study strongly suggests that modification of wet‐end cationic starch with borax holds a tremendous potential as wet‐end strength additive. It can provide significantly improved strength properties, reduction in softwood pulp costs, and better papermaking machine performance. © 2012 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Constraint data‐driven optimal terminal ILC of end product quality for a class of I/O constrained batch processes

In order to deal with the I/O constraints in a practical plant, a soft limiter is often added into the control design procedure directly; however, the performance of the soft limiter based control approach will be degraded greatly due to the use of the soft constraints. This paper proposes a data‐driven optimal terminal iterative learning control (constraint‐DDOTILC) approach for the end product quality control of batch processes with I/O hard constraints. To deal with nonlinearities, a novel iterative dynamic linearization method without omitting any information of the original plant is introduced such that the derived linearized data‐driven model is completely equivalent to the original nonlinear system. By transferring all the constraints on the system output, control input, and the change rate of input signals into a linear inequality, a novel constraint‐DDOTILC is developed by minimizing an objective function under the derived linear matrix inequality constraint. The optimal learning gain of the constraint‐DDOTILC can be updated iteratively according to the input and output measurements to enhance the flexibility for modifications and expansions of the controlled plant. Both theoretical analysis and simulation results confirm the effectiveness of the proposed constraint‐DDOTILC.     

Real‐time Dynamic Optimization of Non‐linear Batch Systems

In this paper, a methodology for designing and implementing a real time optimizing controller for non‐linear batch processes is discussed. The controller is used to optimize the system input and state trajectories according to a cost function. An interior point method with penalty function is used to incorporate constraints into a modified cost functional, and a Lyapunov‐based extremum seeking approach is used to compute the trajectory parameters. Smooth trajectories were generated with reduced computing time compared to many optimizations in literature. In this paper, the theory is applied to general non‐flat non‐linear systems in a true on‐line optimization.     

基于自适应模糊神经网络的非线性系统模型预测控制

针对非线性动态系统的控制问题,提出了一种基于自适应模糊神经网络(adaptive fuzzy neural network, AFNN)的模型预测控制(model predictive control, MPC)方法。首先,在离线建模阶段,AFNN采用规则自分裂技术产生初始模糊规则,采用改进的自适应LM学习算法优化网络参数;然后,在实时控制过程,AFNN根据系统输出和预测输出之间的误差调整网络参数,从而为MPC提供一个精确的预测模型;进一步,AFNN-MPC利用带有自适应学习率的梯度下降寻优算法求解优化问题,在线获取非线性控制量,并将其作用到动态系统实施控制。此外,给出了AFNN-MPC的收敛性和稳定性证明,以保证其在实际工程中的成功应用。最后,利用数值仿真和双CSTR过程进行实验验证。结果表明,AFNN-MPC能够取得优越的控制性能。     

基于ELM的一类不确定性纯反馈非线性系统的Backstepping自适应控制

针对一类不确定性纯反馈非线性动力学系统,在中值定理、Backstepping控制的基础上,提出一种基于极限学习机（ELM）的自适应神经控制方法。ELM随机确定单隐层前馈网络（SLFNs）的隐含层参数,仅需调整网络的输出权值,能以极快的学习速度获得良好的推广性。在每一步的Backstepping设计中,应用ELM网络对子系统的未知非线性项进行在线逼近,通过Lyapunov稳定性分析设计的权值参数自适应调节律,可以保证闭环非线性系统所有信号半全局最终一致有界,系统的输出收敛于期望轨迹的很小邻域内。将所设计的控制方法应用于化工过程中的连续搅拌反应釜（CSTR）非线性系统实例中,仿真结果表明了控制方法的有效性。     

Dependence of the Error in the Optimal Solution of Perturbation‐Based Extremum Seeking Methods on the Excitation Frequency

In perturbation‐based extremum‐seeking methods, an excitation signal is added to the input, and the gradient, computed from the correlation between the input and output variations, is forced to zero. The main drawback of the method is that the speed of convergence, which is linked to the dither frequency, is slow due to the low value of dither frequency typically chosen. Increasing the excitation frequency may cause instability, but that could be corrected by phase compensation. In this paper, it is shown that an additional problem exists, i.e., the distance between the optimum and solution reached by the perturbation method is proportional to the square of the frequency of excitation and does not go to zero even when the amplitude of the excitation goes to zero. However, for Wiener/Hammerstein approximations, the error will indeed go to zero with the excitation amplitude. Simulation results on a distributed reaction system are used to illustrate the concepts presented in this work.     

High-order iterative learning model predictive control for batch chemical processes

In order to address two-dimensional (2D) control issue for a class of batch chemical processes, we propose a novel high-order iterative learning model predictive control (HILMPC) method in this paper. A set of local state-space models are first constructed to represent the batch chemical processes by adopting the just-in-time learning (JITL) technique. Meanwhile, a pre-clustered strategy is used to lessen the computational burden of the modelling process and improve the modelling efficiency. Then, a two-stage 2D controller is designed to achieve integrated control by combining high-order iterative learning control (HILC) on the batch domain with model predictive control (MPC) on the time domain. The resulting HILMPC controller can not only guarantee the convergence of the system on the batch domain, but also guarantee the closed-loop stability of the system on the time domain. The convergence of the HILMPC method is ensured by rigorous analysis. Two examples are presented in the end to demonstrate that the developed method provides better control performance than its previous counterpart.     

Adaptive extremum-seeking control of convection-reaction distributed reactor with limited actuation

In this paper, we pose and solve an adaptive extremum control problem to optimize the productivity of a van de Vusse reaction taking place in a tubular reactor governed by a set of nonlinear hyperbolic partial differential equations. Estimation and control algorithms that take into account control input constraints are developed by using a Lyapunov-based procedure, ensuring stability and convergence under a persistency of excitation condition. Here, we assume that the temperature information along the reactor is the only available on-line measurement to estimate the unmeasured objective function at the reactor exit. Numerical application of the proposed method shows that the resulting feedback algorithm steers the system to its optimum using a non-distributed jacket temperature actuation. The time evolution of the cost function is compared with an idealized distributed version of the algorithm presented previously.     

Identification and control of a riser‐type FCC unit

This paper addresses the use of feedforward neural networks for the steady‐state and dynamic identification and control of a riser type fluid catalytic cracking unit (FCCU). The results are compared with a conventional PI controller and a model predictive control (MPC) using a state space subspace identification algorithm. A back propagation algorithm with momentum term and adaptive learning rate is used for training the identification networks. The back propagation algorithm is also used for the neuro‐control of the process. It is shown that for a noise‐free system the adaptive neuro‐controller and the MPC are capable of maintaining the riser temperature, the pressure difference between the reactor vessel and the regenerator, and the catalyst bed level in the reactor vessel, in the presence of set‐point and disturbance changes. The MPC performs better than the neuro controller that in turn is superior to the conventional multi‐loop diagonal PI controller.     

高速纸机的DCS控制系统设计及应用

描述了高速纸机的DCS控制系统设计与应用,介绍了DCS控制系统的设计要,硬件体系结构,应用软件设计和主要控制回路的控制方案,实际运行结果表明系统稳定可靠,控制精度高,满足了生产工艺的要求。