Basis Weight Control Research Articles

Novel Parameter Identification Method for Basis Weight Control Loop of Papermaking Process

The basis weight control loop of the papermaking process is a non-linear system with time-delay and time-varying. It is impractical to identify a model that can restore the model of real papermaking process. Determining a more accurate identification model is very important for designing the controller of the control system and maintaining the stable operation of the papermaking process. In this study, a strange nonchaotic particle swarm optimization (SNPSO) algorithm is proposed to identify the models of real papermaking processes, and this identification ability is significantly enhanced compared with particle swarm optimization (PSO). First, random particles are initialized by strange nonchaotic sequences to obtain high-quality solutions. Furthermore, the weight of linear attenuation is replaced by strange nonchaotic sequence and the time-varying acceleration coefficients and a mutation rule with strange nonchaotic characteristics are utilized in SNPSO. The above strategies effectively improve the global and local search ability of particles and the ability to escape from local optimization. To illustrate the effectiveness of SNPSO, step response data are used to identify the models of real industrial processes. Compared with classical PSO, PSO with time-varying acceleration coefficients (PSO-TVAC) and modified particle swarm optimization (MPSO), the simulation results demonstrate that SNPSO has stronger identification ability, faster convergence speed, and better robustness.

Multidimensional Interpolation Decoupling Strategy for CD Basis Weight of Papermaking Process

With a focus on the multivariable coupling characteristics in a cross-directional (CD) basis weight control system, we study the coupling characteristics of a CD control system and decoupling control, and we propose a novel multivariable interpolation decoupling control strategy and a real-time decomposition algorithm in this paper. Based on a model of the CD basis weight profile, a system non-square interaction matrix of high-dimensional data is analyzed by experimental studies and numerical simulation. Along the diagonal of the interaction matrix, the matrix block method is adopted to reduce the system dimension and convert it into a square system. A multivariable control system with high dimensionality is divided into several subsystems. For the high-dimensional Toeplitz symmetric subsystem with small-scale coupling characteristics, an interpolation decoupling algorithm is proposed. Then, a decoupling compensator with the structure of a symmetric Toeplitz matrix was obtained. Compared with the conventional diagonal decoupling matrix, the branch number of the new decoupling network is reduced from 2408 to 186, which realizes the fast decoupling of multivariable systems. The results were even better when we used a double size interaction matrix obtained by interpolation between actual values. By designing the diagonalized controller for the new decoupled system, a decouped CD control system for corrugated paper with a basis weight of 133 g/m2 was implemented in an actual project in a paper mill.

PSO-based Parameter Tuning for a Two-Degree-of-Freedom IMC Scheme and Its Application to Paper Basis Weight Control

PSO-based Parameter Tuning for a Two-Degree-of-Freedom IMC Scheme and Its Application to Paper Basis Weight Control

Effect of Dilution Water on Pulp Consistency in Cross-directional Basis Weight Control

Effect of Dilution Water on Pulp Consistency in Cross-directional Basis Weight Control

Decoupling control method of paper cross‐directional basis weight based on sparse decomposition

With a focus on the coupling problems of multivariable control for the paper cross‐directional (CD) basis weight caused by a hydraulic headbox, a novel approach of multivariable decoupling control based on sparse decomposition is proposed. The model function of the CD basis weight control for a single dilution water branch valve is used as the basis of a sparse atomic library. Then, according to the deviation curve of the CD basis weight, the particle swarm optimization (PSO) algorithm is used to obtain atoms corresponding to each control unit (the multiple dilution water branch valves) to form a sparse atomic library. As each atom in the atomic library contains the control information of the corresponding dilution water branch valve, the decoupling control of paper CD basis weight can be realized via mining control information. The essence of this method is to solve the coupling problems of multivariable control by using optimization theory. Experimental results demonstrate that this method achieves a remarkable decoupling control effect.

Active scanner control on paper machines

ABSTRACT The cross-directional (CD) basis weight control on paper machines is improved by optimizing the path of the scanning measurement. The optimal path results from an LQG problem and depends on how the uncertainty of the present estimate of the basis weight and the intensity of process noise vary in CD. These factors are assessed by how accurately the CD basis weight estimate predicts the measured optical transmittance with a linear adaptive model on synchronized basis weight and transmittance data. Simulations on optimized scanner path in disturbance scenarios are presented, and the practical implementation of scanner control is discussed.

Study on the Backlash Measurement and Software Compensation of Basis Weight Control Valve

Study on the Backlash Measurement and Software Compensation of Basis Weight Control Valve

Papermaking Process Basis Weight Control Based on PIDDMC Optimal Algorithm

In the papermaking actual process basis weight of paper sheet often has properties of nonlinearity, time-varying, uncertainty and larger-time delay. With the improvement of control requirements, traditional PID control is not ideal, and DMC control depends on the process model which needs the actual feedback information to complete repeated online optimization. So a novel PIDDMC combined optimal algorithm is proposed to obtain the satisfied performance index. Simulation is analyzed to show that the algorithm can be well performed with high accuracy and stability.

Cross-Directional Basis Weight Measure and Control System Based on CARMA Model Predictive Function Control Algorithm

According to the analysis of papermaking process, combined with the principle of cross-directional basis weight(BW) detecting and controlling, predictive function control based on CARMA(Controlled Auto Return Integral Moving Average Model) model is proposed to solve the problem of time delay, nonlinearity and uncertainty of the multi-dimension system. Simulations show that multivariable predictive functional control algorithm for fast tracking velocity, good dynamic performance, and it can effectively reduce the mutual coupling effects between variables. The method has the feasibility of applying to practical papermaking process.

Design of Basis Weight Instrument Based on Wireless Transmission Technology

Design a kind of basis weight instrument based on wireless transmission technology, which adapt to the basis weight measurement and control system. Show the hardware and software structure. It uses C8051F353 as MCU, and uses CC1100 as wireless communication chip. The instrument can control the scanning bracket to detect paper’s basis weight on line automatically, or remote manual control. It may connect to wireless sensor network, or integrated in DCS. The precision is high to 0.05%. It can be used to detect all kinds of paper and board by using different radiate source.

Cost modelling for feedback control adjustment

Process control is a management problem in the performance analysis of a continuous production process. Statistical process monitoring and feedback control recently have been of interest to process control practitioners. It is imperative for the process control practitioner to know the costs of sampling and adjusting a process in order to minimize the manufacturing cost without compromising the objectives of process control. This view is kept as a basis when proposing a cost modelling methodology using some of the sampling and cost modelling principles available in literature. The sampling (adjustment) intervals are obtained by direct simulation of a feedback control algorithm in the proposed methodology. The algorithm is developed by the application of statistical and automatic process control techniques. The suggested method to develop the cost model and the associated cost functions uses adjustment intervals and is less complex. The cost function for feedback control adjustment is based on a second-order transfer function process model and a first-order noise model. The cost model and a corresponding control regulation scheme have applications in basis-weight control on a paper machine and in a batch-polymerization process that produces polymer resins in two groups of batch reactors that run in parallel and share common raw materials.

Closed-loop identification with MPC for an industrial scale CD-control problem

An approach to implementing closed-loop identification in a model predictive-control framework for the cross-direction control of basis weight is proposed. The closed-loop-identification technique uses the concepts of Markov parameters to determine a step-response model that can then be used within a model predictive controller. The technique is applied to an industrial-scale paper-machine-simulation benchmark problem for cases of varying degrees of shrinkage. The performance of wet- and dry-end full-array sensors are compared. Also, the performance of the closed-loop identification is compared for a nominal case and two cases in which shrinkage occurs in the drying process.

Autotuning PID Control for Large Time-Delay Processes and Its Application to Paper Basis Weight Control

The brief arts and crafts of the ordinary fourdrinier are introduced first in this paper. After analysis of the intractable points of paper basis weight (BW) control, an autotuning PID/PI control algorithm is then presented which is capable of controlling large time-delay processes. The algorithm can be described as below. The oscillation amplitude and frequency induced by a modified relay feedback identification method at the point where the Nyquist curve of the process intersects the negative imaginary axis in the S plane are obtained. In terms of the information obtained above, the autotuning PID/PI parameter values are thus tuned according to the specified robust specifications of amplitude and phase margin. The algorithm has many advantages such as simple parameter adjustment, little dependence on the process model, strong robustness, and ease of implementation. It is also very suitable for controlling industrial processes such as the BW loop with large time delay.

Implementing machine-directional basis weight control for a pilot paper machine

The model of a paper machine is very complex and difficult to describe completely by a mathematical model. There are a lot of parameters in both the wet and dry end of the machine and there is a very large time delay in the system which effects the quality of the paper being produced. Although the PID controller is widely used for these types of applications, it is often not tuned very well. In this work, a newly developed algorithm (Munro, The systematic design of PID controllers, IEE Colloquium in Robust Control: Theory, Software and Applications, Austin Court, Birmingham, 1999) is used for tuning the PID controller. Along with this controller, a Smith-predictive controller is applied to the plant and the transient and steady-state behaviours of these controllers are compared. Hardware and software implementations of the closed-loop control are also presented in the paper.

Integrated system offers on-line measurement and control of basis weight and moisture for non-wovens

Integrated system offers on-line measurement and control of basis weight and moisture for non-wovens

Block Discouple Control of Cross-Directional Basis Weight on Paper Machines

This paper presents a new approach for the cross-directional basis weight control on paper machines. The multivariable control system with high-dimension is discoupled into several subsystems by introducing a new constraint on control variables to satisfy the computation and capability limitation of existing on-line control system. A block discoupling algorithm is developed, and a parallel control strategy is proposed to implement the control algorithm. Based on the strategy, a multiprocessors system is designed to realize the simulation. Simulation results show that the computational time can be significantly decreased and the real-time performance can be improved.

Adaptation of cross-direction basis-weight control in paper machines using fuzzy decision logic

An important quality characteristic in the production of paper webs is the range of fluctuations in the basis weight. This should be kept as small as possible. The basis-weight profile is a measure of these fluctuations. Deviations in the profile that arise during the papermaking process can be rectified by installing slice screws across the web and by suitable control functions. However, due to web shrinkage and displacement in the cross direction, the location on which a slice screw is acting in the profile is not known. This relationship, or mapping, is an essential precondition for cross-direction control. If it cannot be implemented accurately enough, the profile develops unevenness and, in the worst case, becomes unstable. This paper describes a method that identifies this relationship by means of statistical process and a fuzzy decision logic, and that appropriately adapts cross-direction control.

Cross-directional control on paper machines using gram polynomials

A control algorithm for cross-directional basis weight control based on orthogonal polynomials is presented. Instead of controlling the cross-directional values at each point, the parameters of the orthogonal polynomials are controlled, taking into account the maximum bending moment of the slice lip and the relative stiffness of the slice with respect to the actuators. The Gram polynomials have inherent ability to limit bending of the slice lip in a way that conventional control does not. The slice lip will have smooth deflection, governed by the maximum order of the polynomial, which can be lowered if the bending limits are exceeded. By modelling the measurements and the actuator positions by polynomials, the mapping between the actuators and the sensors, which is the key element of the current control systems, is effectively eliminated. Computational requirements are greatly reduced by avoiding inverses of large matrices, or the inverses are found for a diagonal matrix. The performance of the Gram polynomial control method is shown to be superior to conventional control methods, especially for badly conditioned matrices.

Adaptive feedback control for unevenly sampled systems

This paper presents an adaptive control algorithm for a new type of discrete-time system that is unknown and is sampled unevenly. Such systems are obtained by unevenly sampling the unknown continuous time plant with two sequential sampling periods (T1 and T2), and are therefore referred to as unknown S(T1, T2) systems. This paper discusses their representation and stability when that system incorporates a known time delay. A generalized causal adaptive one-step-ahead controller is developed and it is shown to be able to stabilize the unknown S(T1, T2) system with respect to a uniformly bounded signal. The application to a typical S(T1, T2) system: the cross-directional basis weight control system in a paper making process, is described. Desirable results are obtained.

Headbox modelling for cross-direction basis weight control

This paper considers the representation of cross-directional (CD) basis weight on paper machines where the two-dimensional (2D) coupling between CD and machine direction (MD) is important and must be controlled. Indeed, because the flow pattern from the headbox exhibits 2D interactive behaviour, any simple non-interacting CD control model must be inadequate, hence the need for appropriate models. One solution, short of a complex hydrodynamic model, is to provide the necessary control structure with a function representing the interaction determined by considering the behaviour of the flow field. From a 2D control point of view, the mean of the control signal would relate strongly to the MD controller, with the rest being the CD controller. It thus should be possible to contrive a 2D control strategy for the headbox system based essential upon the modelling work shown here.