Paper Machine Headbox Research Articles

New technique for decoupling control

Abstract A new technique for decoupling controller design is proposed. A reference model representing the desired closed-loop dynamic behaviour is chosen. A quadratic performance index is used to measure both coupling and tracking errors in the closed-loop system. The system state equation is organized in incremental canonical form. The optimal decoupling control law is obtained by minimizing the performance index. This algorithm has been applied to a paper machine headbox control system. The performance of the system under different conditions is satisfactory.

Fault-tolerant control of paper machine headboxes

This paper presents a model-based fault detection and fault-tolerant control technique for the pressurized headbox of a paper machine. A bank of Kalman filters is constructed corresponding to all the possible sensor failure modes. The possibility that each failure mode hypothesis is true is calculated using measurement innovation processes. The sensor failures are detected and located based on the calculated possibilities of the hypotheses. The controller and state estimator are automatically reorganized subsequent to the occurrence of failures to ensure the stability and good performance of the closed-loop system. The issues of system hardware redundancy and computational burden as well as implemental complexity are taken into account in the system design. Simulation results have shown satisfactory performance of the headbox control system after applying the presented technique.

On the Approximation of a Deflection Curve by Force Actuators With Variable Spacing

In this paper we discuss a suboptimal method of approximating a desired deflection curve of a simple beam by a given number of force actuators. The spacing between the actuators is allowed to vary as a function of the deflection curve. The method is applied to an example of approximation of a deflection curve of the slice lip on a paper machine headbox for the control of the basis weight profile of paper. The approximation error with variable spacing is compared with that obtained when the spacing is not varied (uniformly-spaced actuators). Significant reduction in error is observed.

Advanced Portable Control Station

A new data acquisition and control software package for IIP 9000/300 series UNIX workstations is presented. Four simultaneously running tasks take care of data acquisition, control, on-line graphics, and online parameter changes. The portable control station is meant for demanding on-site measurement and control tasks. Most of commercial digital automation systems are too inflexible for advanced control implementations. Commercial software for microcomputers is also quite limited, emphasizing more signal analysis than control.The paper also reviews single-input single-output (SISO) and multivariable (MIMO) control algorithms implemented in the software. Both fixed parameter (SISO PID, MIMO PID) and self-tuning algorithms (SISO STC, MIMO PI) are available. Experiments with a MIMO self-tuning Pl-controller were performed at a laboratory-scaled head box of paper machine at Tampere University of Technology. Tests on a DC-servo motor were also carried out, using a SISO-PID controller and a STC.

An Optimal Decoupling Controller with Application to the Control of Paper Machine Headboxes

This paper proposes a new algorithm for the decoupling design with additional design aims involved. A reference model which represents the desired closed-loop dynamic response is first used, then a quadratic performance index is introduced to measure both the amount of coupling and the tracking error in the closed-loop system. The control law can be obtained from optimal control technique. This algorithm has been applied on a paper machine headbox using a process control computer. The results under different conditions are obtained.

A Self-Tuning Controller for Processes with Time-Varying Delay: Application to a Paper Machine Head Box

The paper develops a new method to estimate time-varying delay in self-tuning control. Another improvement to self-tuning is a novel way to vary λ weight in the cost function matrix Q. Both ideas were tested with computer simulation and proved successful.The basic reason for developing the new method was the application of self-tuning control to paper machine head box. Preliminary experiments with scalar self-tuning control were carried out at a pilot paper machine of Tampella Ltd in Inkeroinen, Finland. The tried scalar incremental self-tunig controller worked well but the responses showed some sluggishness. Further experiments were performed at a laboratory-scaled head box at Tampere University of Technology. A new "hybrid" self-tuner, with a fixed proportional controller and a self-tuning part, gave surprisingly good results compared with PID control.

A study on flow characteristics of pulp suspension. 3rd report. The influences of the flow duct figure on flocculation.

Pulp suspension flow is characterized by a complicated relationship between fiber flocculation and turbulence intensity. The object of this study is to clarify the influences of duct construction on the flow, and to develop a high-consistency paper-forming headbox. Optical measurements were carried out to investigate the extent of dispersion in the pulp suspension flow in a duct having various turbulence generating elements. The results are as follows : (1) Both dispersion and reflocculation were remarkable in the duct flow with an orifice which is a strong turbulence generator. (2) The saw-blade-type duct flow indicated a higher dispersion rate and mild reflocculation, and therefore is suitable as the element of a paper machine headbox. (3) The power spectra of the flocculation signal suggest that the dispersion and reflocculation of a suspension is related to the turbulence scale characterized by the flowing duct dimension.

A decoupling pole placement self‐tuning controller for a class of multivariable processes

AbstractThis paper describes a new multivariable self‐tuning controller that specifically handles different time delays between each of the input‐output pairs (multiple delays), and deals with unknown or varying time delay (variable dead time compensation) without requiring an explicit estimate of each delay. The new algorithm can control unstable and/or non‐minimum phase processes; it eliminates both set‐point and load offsets without having to maintain integral action continuously; it decouples the loops, both dynamically and at steady state. The effective decoupling algorithm not only minimizes significant interactions among the control loops, it permits the use of a very simple design criterion, namely the approximate assignment of the primary closed‐loop poles to prespecified locations. A straightforward autotuning technique locates the closed‐loop poles on‐line so as to optimize the system set‐point step responses. One desirable side‐effect is to account for inexact decoupling.The controller is demonstrated using a simulated paper machine head box having an unusually large amount of (off‐diagonal) interaction, a simulated two‐input, two‐output distillation column with time‐varying parameters (varying gains and time delays), and a highly interacting unstable and non‐minimum phase system on which the autotuning technique is demonstrated. These three processes place stringent requirements on any control method, and two of them have been used extensively in the literature to test various multivariable and/or self‐tuning algorithms. Hence, the success of the new technique indicates that it is a very promising candidate to deal with intransigent processes, i.e. those characterized as unstable, non‐minimum phase, time‐varying (non‐linear), and interacting.

A Multivariable Decoupling Pole-Zero Placement Self-Tuning Controller

This paper describes a new multivariable self-tuning controller which is able to handle the system with different time delays between each of the input-output pairs, and deal with the system with unknown or varying time delays. The proposed controller not only moves the closedloop-system poles to the prespecified locations but also decouples the multivariable system. It. can track time varying reference signals and eliminate tracking errors. In addition an implicit algorithm is proposed under certain conditions. The controller is demonstrated using a concentration-flow process, a paper machine head box and an unstable and nonminimum phase system having different time delays.

A Study on Flow Characteristics of Pulp Suspension Flow : Measurements of Turbulence Intensity and Fiber Concentration Unevenness

In order to examine the relationship between the turnbulence intensity and the fiber concentration unevenness in the flow of pulp suspension, these quantities were measured in a duct with various types of turbulence generators installed at the duct inlet. The turbulence intensity of suspension flow was measured by two small pressure transducers and the concentration unevenness was measured as the intensity fluctuation of light transmitted through the pulp suspension in the duct section. The results show that the concentration unevenness is inversly related to the turbulence intensity. It is also found that there is a time delay in change of the concentration unevenness due to the turbulence. It is believed that the test results provide useful information on development of improved paper-machine headboxes.

A Decoupling Pole Placement Self-Tuning Controller for a Class of Multivariable Processes

This paper describes a new multivariable self-tuning controller that specifically handles di fferent time delays between each of the input-output pairs (multiple delays), and deals with unknown or varying time delay (variable dead time compensation) without requiring an explicit estimate of each delay. The new algorithm can control unstable and/or nonminimum phase processes; it eliminates both set-point and load offsets without having to maintain integral action continuously; it decouples the loops, both dynamically and at steady state. The effective decoupling algorithm not only minimizes significant interactions among the control loops, it permits the use of a very simple design criterion, namely the approximate assignment of the primary closed-loop poles to prespecified locations.The controller is demonstrated using a simulated paper machine head box having an unusually large amount of (off-diagonal) interaction and a highly interacting unstable and nonminimum phase system.

Simulations of adaptive controllers for a paper machine headbox

The paper headbox is a crucial part of a paper machine, largely influencing the paper quality. Since this can be improved by better control, the evaluation of advanced control methods is certainly justified from an economical point of view. Not only do disturbances have to be rejected, but smooth startups and fast setpoint changes must also be possible. To design a good controller, some parameters need to be known, the determination of which can be cumbersome. However, this can be considerably alleviated by adding an on-line parameter estimator to the controller. This allows the controller to adapt itself to slowly changing process characteristics. In this paper different adaptive control methods are used on the simulated process and compared to the classical PI-controls. Particularly, a single-output self-tuning controller with feedforward action and a multivariable adaptive deadbeat controller are promising. The last one provides simultaneous offset-free control of both process outputs.

Schemes for Multivariable Parameter-Adaptive Deadbeat Control

In this paper a multivariable parameter-adaptive deadbeat controller is presented. The process dynamics are modeled by the transfer matrix requiring only a few mild conditions to be satisfied. The algorithms are derived for processes with as many input variables as output variables. Alternatives are given if the number of input variables is smaller or larger than the number of output variables: ordinary and inferential cascade control may be used or a configuration in which the redundant input variables are used as a backup of control energy. Since the control quality depends on the accuracy of the estimated process model parameters, identification procedures that lead to unbiased parameter estimates are discussed. The alqorithms are applied to some realistic examples to demonstrate their use: a helicopter, a paper-machine headbox and the control of the biological oxygen demand in river water.

Dual model reference adaptive control on paper machine headboxes

When industrial processes operate under variable production conditions, linear models and linear controllers are generally not efficient. When a paper machine operates at variable speed, the control of the headbox must be efficient for large operating point transitions.We present a dual model reference adaptive controller (DMRAC) that allows the control of linear time varying systems and the explicit on line identification of the process with delayed inputs.The application of the DMRAC to a pressurized headbox when large operating point transitions are applied is presented. Finally a functional decomposition of the DMRAC algorithm for its implementation in a multi-microprocessor system is presented.

Dual Model Reference Adaptive Control on Paper Machine Headboxes

When industrial processes operate under variable production conditions, linear models and linear controllers are generally not efficient. When a paper machine operates at variable speed, the control of the headbox must be efficient for large operating point transitions.We present a dual model reference adaptive controller (DMRAC) that allows the control of linear time varying systems and the explicit on line identification of the process with delayed inputs.The application of the DMRAC to a pressurized headbox when large operating point transitions are applied is presented. Finally a functional decomposition of the DMRAC algorithm for its implementation in a multi-microprocessor system is presented.

Application of Several Parameter-Adaptive Controllers to a Paper Machine Headbox

Several authors have pointed to the importance of optimal paper headbox control as a crucial part of the global paper making process. External disturbances influence the output, also many startups of the process may be required. Since the paper quality can be improved by better control, the evaluation of advanced control algorithms is well justified.The introduction of process computers and microprocessors in the control environment has opened new perspectives for the control of paper making too. To design a good controller, a number of numerical coefficients must be known accurately. The determination of these parameters can be cumbersome. However, this can be considerably alleviated by adding an on-line parameter estimator to the controller. Then the regulator can adapt itself to slowly changing process characteristics. These parameter-adaptive controllers were extensively tested on the Laboratory of Automatic Control in Ghent. Several combinations of controllers and parameter estimators are possible. It will be demonstrated in the paper that several of these controllers improve the control quality of the paper headbox. They are not very sensitive to the noise structure and cause no offset of the output variable. Since the implementation of such adaptive controllers requires very few a priori knowledge, it may be expected that in the future many industrial applications of these will be seen.

Application of several parameter-adaptive controllers to a paper machine headbox

Several authors have pointed to the importance of optimal paper headbox control as a crucial part of the global paper making process. External disturbances influence the output, also many startups of the process may be required. Since the paper quality can be improved by better control, the evaluation of advanced control algorithms is well justified.The introduction of process computers and microprocessors in the control environment has opened new perspectives for the control of paper making too.To design a good controller, a number of numerical coefficients must be known accurately. The determination of these parameters can be cumbersome. However, this can be considerably alleviated by adding an on-line parameter estimator to the controller. Then the regulator can adapt itself to slowly changing process characteristics. These parameter-adaptive controllers were extensively tested on the Laboratory of Automatic Control in Ghent. Several combinations of controllers and parameter estimators are possible. It will be demonstrated in the paper that several of these controllers improve the control quality of the paper headbox. They are not very sensitive to the noise structure and cause no offset of the output variable. Since the implementation of such adaptive controllers requires very few a priori knowledge, it may be expected that in the future many industrial applications of these will be seen.

Non interacting multivariable paper machine headbox control: Some comparisons with classical loops

A non interacting multivariable papermachine headbox control is discussed and compared with some classical loops. The control design is based on quadratic optimization criterion with a discrete state variable process model. Two reference models are used in this control structure: Tracking model and Perturbation model. Integrators have not been used to remove steady state error. Different results are obtained on an experimental headbox, controlled by a process control computer.

Non Interacting Multivariable Paper Machine Headbox Control: Some Comparisons with Classical Loops

A non interacting multivariable papermachine headbox control is discussed and compared with some classical loops. The control design is based on quadratic optimization criterion with a discrete state variable process model. Two reference models are used in this control structure : Tracking model and Perturbation model. Integrators have not been used to remove steady state error. Different results are obtained on an experimental headbox, controlled by a process control computer.

Stochastic state-variable model for a paper-machine headbox

A state-variable model for a pilot plant of paper-machine headbox has been developed using actual input-output data. The linearised physical equations have been considered and effects of plant disturbance and measurement errors have been included. For estimating the unknown parameters of the model from noisy measurements, two recursive estimation techniques, namely ‘extended Kalman filter’ and ‘two-stage estimation algorithm’, have been used. The model validity has been checked by carrying out residual error tests for both the techniques. Further, estimated responses in both the cases have been compared with the actual output.