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The paper discusses a self tuning control algorithm for a multivariable plant applied to a grammage cross profile control of a paper machine. The plant model represents the steady-state couplings as well as the dynamics behaviour of the system. The control algorithm handles special situations including the case where the numper of measurments is not equal to the numper of actuators and the case where special actuators are locked. The whole identification algorithm with a specical filter and an estimation of the required measurment accuary for a succesful identification of the steady-state couplings will be discussed. The paper shows how to proof the stability of the control system including the cases of locked actuators and identification errors. Finally, the whole conrol system is verified by in house simulations and at a real plant. The obtained control results are discussed.

Proportional Integral Derivative (PID) controller tuning is an area of interest for researchers in many areas of science and engineering. This paper presents a new algorithm for PID controller tuning based on a combination of bacteria foraging and particle swarm optimization. BFO algorithm has recently emerged as a very powerful technique for real parameter optimization. To overcome delay in an optimization, combine the features of BFOA and PSO for tuning the PID controller. This new algorithm is proposed to combine both the algorithms to get better optimization values. The real time prototype model of paper machine is designed and controlled by using PIC microcontroller embedded with the programming in C language.

This paper defines the efficiency similarity of different motor driving devices. Based on the efficiency function characteristics which can be approximately considered a concave, non-negative function through the origin, we present a kind of optimal control method for a felt driven by three different motors in paper machine. It gives the minimum total power consumption. The optimal control method is to keep the same torque rate for each motor driving device. This method is independent of the linearity or nonlinearity of the system and has no need for the system’s state equation or transfer function. Since the shapes of efficiency functions in nature are similar, the conclusion can also be applied to the energy optimization of other general devices.

This paper is focuses modeling of the last part of the paper machine – the drying section. Paper is dried by letting it pass through a series of steam heated group of cylinders and the evaporation is thus performed by the latent heat of vaporization of the steam. The moisture in the paper is controlled by adjusting the set point of the steam presure controllers to the cylinders. There exist several incentives to focus on the performance of the moisture control. The time to perform a grade change is often limited by the moisture and shorter grade change time is directly correlated to economic profit. The plant model is identified periodically and the changes in its dynamic characteristics are observed. Periodic identification gives a great advantage over the conventional controller tuning methods, which uses the plant model at the nominal operating conditions. A variety of model structures are available to assist in modelling a system. Model for the drying process of Paper industry is established based on gathering 1000 groups of 2500 real-time sample data. Based on the collection of data, that was adapted to both the conventional and intelligent modelling process. Finally the suitable model is tuned with the suitable controller for optimal control of the drying process.

Total Pressure and Stock Level in the headbox of a paper machine control the quality of paper produced and cross directional flow at the slice. Thus, these are the important parameters to be controlled. With the advancement in artificial intelligence, mathematical approaches that demand high degree of precision has been avoided by using the best estimates in the research work. Soft computing technique i.e. fuzzy logic is used in this paper and the simulation results are compared with classical PID controller.

The modern headbox has many attributes that are highly significant for all paper-makers. Uniformity of flow, absence of streaks and large eddies, headbox stability and ease of operation are required features for all paper grades. Consistency in a headbox is a very important parameter in paper mills in their various stages of operations. Without the knowledge of consistency, it is not possible to optimize productivity with optimal quality. In the present study, a multivariable, linearized, state space model of a paper machine headbox was selected for control of consistency and liquid level in the headbox of a paper machine using the advanced control strategy Model Predictive Control (MPC). MPC uses a model to predict the process output along a future time horizon. It performs the calculation of a control sequence to optimize a performance index. It is based on receding horizon strategy so that at each instant the horizon is moved towards the future, involving the application of the first control s...

Small motions will result in heavy influence to the production in high-speed paper machine, therefore, decoupling control is necessary. This passage Puts forward the opposite angles strategies to solve the function of decoupling aiming at solving the difficulty that occurs in practice, like the characteristic of hard-coupling and non-linear. According to the mathematics model of the flow box, decoupling the quantity of the two couplings in the processes. Meanwhile, Introduces the SIEMENS S7-300 PLC and the DCS system that is realized by the it.

The minimum variance controller has been extensively used as a benchmark in the performance assessment of both univariate and multivariate control loops when time delay is the fundamental performance limitation. In this paper, the spatial and temporal performance limitations in the cross-directional (CD) control of paper machines are analyzed. The idea of minimum variance benchmarking is extended to the CD process based on these performance limitations. Based on an industrial CD controller, a user-specified benchmark, which is more practical and less aggressive, is also proposed. In addition, several related performance indices are proposed for the CD process based on both the minimum variance benchmark and the user-specified benchmark. Illustrative examples from a paper machine simulator and industrial data sets are provided to show the effectiveness of the proposed performance indices.

In this contribution, the dynamical behavior of a paper-making system is presented and an advanced controller is developed to minimize the amount of recycled paper used in the paper making process. The advanced controller is a model based control strategy, and therefore, a model is developed in order to evaluate the loss of paper during the transition between two points of operation. The wastage model is adapted to be used in the cost function of an in-house developed predictive control algorithm. Performance evaluation is described and the corresponding results are presented.

This paper solves the controller tuning problem of machine-directional predictive control for multiple-input–multiple-output (MIMO) paper-making processes represented as superposition of first-order-plus-dead-time (FOPDT) components with uncertain model parameters. A user-friendly multi-variable tuning problem is formulated based on user-specified time domain specifications and then simplified based on the structure of the closed-loop system. Based on the simplified tuning problem and a proposed performance evaluation technique, a fast multi-variable tuning technique is developed by ignoring the constraints of the MPC. In addition, a technique to predict the computation time of the tuning algorithm is proposed. The efficiency of the proposed method is verified through Honeywell real time simulator platform with a MIMO paper-making process obtained from real data from an industrial site.

In the present work, the problem of controlling recipe transitions in a paper-making process is addressed, in order to avoid paper breakage and reduce paper waste. A decoupling control scheme is proposed, based on the control of speed differences between contiguous motors. This guarantees smooth and fast transitions of all the motor speeds along the production line. A front-tracking scheme is also employed, in order to adapt the recipe change to the actual plant conditions. A simulation model has been constructed and validated for a real industrial paper-making plant, and the effectiveness of the proposed control algorithm has been tested by means of simulation.

Wind turbine rotor imbalances may be created by a multitude of causes, e.g. pitch misalignment, blade erosion. In such situations, machines experience undesired vibrations, which cannot be compensated or mitigated by the controllers generally adopted by industry today. This happens because the control action may be collective or both collective and cyclic, but, in order to cope with imbalances, it is necessary to employ a fully individual control which allows a blade to move independently from the others. In this paper we present a new individual pitch control algorithm able to simultaneously target the imbalance and reduce oscillating loads at frequencies multiple of the rotor revolution. The effectiveness of the proposed control is demonstrated in a high-fidelity simulation environment.

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.

A retention control system trial was performed for the wet part of a papermaking machine. By introducing two intelligent pulp and ash (filler) low consistency sensors (Kajaani : RM-200 M) to the stock supply line of head box and the white water (WW) filtrate line of wire part, we can monitor its wet end process conditions continuously. The retention control system using these sensors stabilizes the wet part process by controlling WW consistency, that is by an appropriate action of the retention aid dosage using a gap added PI (Proportional plus Integral) controller. As many grades production is running and grade changes are run frequently in this paper machine, it is difficult to determine the target set value (SV) of WW consistency. So we developed a new algorithm to judge the process stability by itself and to determine the SV target value of WW consistency automatically.

The pressurized headbox is one of the most important pieces of equipment on a modern paper machine. It is a special two-inputs-twooutputs process, and proper matching of input and output of control loops is very important. Relative gain analysis and computer simulation based on a mathematics model of the pressurized headbox shows that the common used configuration in paper industry is not the best. For this kind of configuration, a multi variable predictive control algorithm is designed. Computer simulation shows that this kind of control algorithm can deal with the headbox control very well. A control system with this kind of controller for full scale pressurized headbox has a good performance with excellent control precision, very short response time and very small offsets.

In controlling uncertain processes, it is decisive to utilize information provided by measurements in order to estimate parameters and states. Nonlinear Model Predictive Control (NMPC) is a popular method to implement feedback control and deal with uncertainties. Conventional NMPC or nominal control, however, sometimes does not provide enough information for system estimation, leading to unsatisfactory performance. Dual control attempts to strike a balance between the two goals of enhancing system estimation and optimizing the nominal objective function. In this paper, we analyze the performance of these strategies through the interplay between the performance control task and the information gain task in connection with Optimal Experimental Design. Examples illustrate the conflict and agreement between the two tasks and explain why in some cases nominal control performs well. It is also observed that measurement noise provides excitation helping to improve the quality of estimates.

Presented in this paper is a novel method to improve machine-direction moisture profile in paper machine.Kalman Filter is employed to compensate the time-varying dead time in moisture control loop. Effect of moisture-basis weight interaction is deliberately utilized in building the control scheme. Stability analysis is tried out in Laplace plane in classical manner.

In this paper, a robust controller for the paper machine benchmark problem is designed using H ∞ loop-shaping techniques. The weighting functions are tuned to minimize the effect of a sinusoidal disturbance in the filler retention level.

The paper presents four issues. The 1st is the introduction of the new web-tension control method which is useful for the control of paper-machine and versatile converting machines. The 2 nd is the performance in efficiency and torque control of GTO inverter which have been successful for energy-saving and center-drive-winder. The 3rd is the software-package for the maintenance of inverters. The last is the introduction of smart controller which is useful for revamping or improvement of old control-systems.

A robust tuning problem for a two-degree-of-freedom model predictive controller is explored for single-input, single-output uncertain paper-making processes. The objective is to achieve satisfactory closed-loop responses, as measured by overshoots, settling times and output oscillations with user-specified parametric uncertainties. As the output variation cannot be easily specified by the end users, two methods are proposed to connect a total variation specification to user-friendly indices, based on which two algorithms are designed to solve the tuning problem. An application to a process extracted from the pulp and paper industry is employed to verify the effectiveness of the proposed algorithms.

Model predictive control is a modem method which was used in many different applications. One of the applications are electrical machines. Designing a controller for a synchronous drive has shown to be a challenging task. Many papers substitute one or more controllers in the cascade structure. Nevertheless, this approach calculates only the suboptimal trajectory, not the optimal trajectory. This paper presents a linearization approach of nonlinear model predictive controller and its preparation for implementation. Simulation is performed to verify presented ideas and its results are shown and discussed at the end of the paper.

The paper mainly introduces the application of closed hood in process of paper produce. This closed hood control system bases on PLC and inverter. In this system, the data collection, calculation, loop control and the communication of PC are completed by PLC. This control system has been applied in medium and small automation transform paper machine. It is practically showed that the output of machine and the stability have been improved by the control system.

This paper presents an industrial application of multivariable combined self–tuning control techniques to a paper machine. The papermaking process is taken as a MIMO system with unequal time–lag, some time–varying parameters and unstable inverses. In order to design a suitable control scheme for the process, a new control strategy, called multivariable combined self–tuner(MCST), with the U–D factorization recursive algorithm is proposed. The capability of the proposed scheme is demonstrated by its application to the basis weight loop and the moisture loop of the Long Wire Paper Machine(LWPM) at Juxian Paper Mill, Shandong, P.R. China.

This paper presents an efficient real-time method of sensor fault detection, isolation and estimation for a class of MIMO nonlinear time-varying stochastic systems. The sensor faults may be a jump or slow drift type. The presented approach is based on the combination of the separate-bias estimation algorithm to randomly time-varying bias of nonlinear systems proposed by the authors and the modified Bayes' decision algorithm. The proposed technique is used to design a sensor fault diagnostics system for the headbox of an actual paper machine. Actual headbox data have demonstrated the effectiveness of the proposed method

Different methods for coordinated motion of the paper or board machine sections were used, mainly depending on the production date. Present solutions are based on individual sectional AC or DC drives as parts of the network control system. The drives are integrated in the control and supervision system with the application of a high performance communication protocol, usually PROFIBUS, Ethernet or DeviceNet. Quality of control system of any paper machine is ensured and the software development procedure is kept straightforward with the use of the universal control block presented in this paper. The generalized structure of the proposed control block is suitable for application on different sections found in paper or board machines, with adequate parametrization. The performance of the block is tested on the dry-end of machine, where the definite amount of sheet tension is required by the technological process. The tension force saliently couples the adjacent drives, which can compromise the performance of the drives, and even lead to unstable operation. The proposed control system structure achieves stable operation of drives coupled through the material, with the possibility to control the sheet tension force.

Good cross-directional control of sheet variables in a paper machine depends on a number of factors. One such factor is the correct alignment of actuators with their corresponding responses. The alignment changes with time either locally or across the whole paper sheet due to a variety of reasons. In this paper, we provide an online mapping technique based on estimating the cross-correlation between actuator movement and the measurements. This procedure involves two steps–in the first step (called alignment monitoring) we determine if the current mapping is wrong at any CD position, and in the second step (called re-mapping), the alignment of actuators is corrected. The main advantage of this method is in its ability to re-align under closed loop conditions with minimal operational disruption.

In this paper, the bilinear control strategy for paper-making process is developed based on the characteristic of paper-making process. The bilinear decoupling control, bilinear observer and bilinear disturbance compensator as the typical techniques are discussed. Their applications to the headbox control of a paper machine at a real paper mill, as an example, are presented. On-line operation and simulation results show that the performance of the bilinear control system is satisfactory.

The integration of process design and control (IPDC) has become increasingly important and received considerable academic and practitioner attention over the recent decades. Moreover, some works in the field have utilized advanced controllers into IPDC framework. Considering the fact that the hierarchical control structure which consists of local PID controllers and an advanced process control (APC) as the central controller has been used widely in industrial practice, in this paper, the two-level hierarchical control structure is taken into account within the IPDC framework for the first time. The IPDC problem using hierarchical control structure is formulated as a bi-level optimization problem, which separates the design decisions from the APC decisions and then keeps the problem size manageable. And the APC decisions are incorporated in a superstructure-based dynamic optimization formulation which considers both cost and controllability. A continuous stirred tank reactor is used to test the proposed IPDC methodology.

In this paper two control problems for a surface robotic vessel are addressed. One is design of a dynamic positioning (DP) system. The other deals with advanced dynamic positioning (ADP) which is extended by an unknown disturbance rejection. Considered plant is represented as a MIMO system which comprised of three independent SISO channels. For the DP problem all SISO channels are controlled by virtual control inputs generated using a robust approach, so called, "consecutive compensator". Then after an inverse MIMO transformation real control signals are calculated for robotic actuators. For the APD problem we design the cancellation scheme for channels with input delays that may be caused by a command transmission via the radio channel or computational complexity of the image processing. To finalize the investigation proposed DP algorithm is applied to the robotic complex of vessel motion modeling.

The paper proposes a method for the LPV-based (Linear Parameter-Varying) control design of the variable-geometry suspension system. The tilting actuation of the front wheel improves the lateral dynamics of the vehicle and assists for the driver in avoiding critical situations. The novelty of the method is the consideration of the nonlinearities in the tyre characteristics. The tyre forces are approximated by polynomials, which are used in the linearizing of the vehicle model. A parameter-varying vehicle model is derived, on which a robust LPV control is designed. The proposed method improves the performances of vehicle dynamics, and handles the critical maneuvers caused by e.g. a skidding car and high velocities. The proposed method is illustrated through CarSim simulation examples.

Torsional oscillations bound the speed loop bandwidth (BW) of industrial drives and servo systems, deteriorating the transient response to commands and to disturbances. This is especially harmful in multi-drive systems, like paper machines, that need to run synchronized. This paper presents two methods to dynamically compensate the torsional oscillations produced by the compliant components between the motor and the load: either a notch filter or acceleration feedback based on the rigid-body Luenberger observer. The evaluation includes the effect of the reducer backlash, whereby both time and frequency domain responses are used to compare the benefits of each technique in a typical paper machine section. Results show that both methods, if properly tuned, are effective techniques to reduce torsional oscillations, and are robust to parameter variations

This paper considers a power system where about half the demand comprises industrial loads and some include large rotating machines. Therefore, the behaviour of these loads during system disturbances has to be considered for system stability studies. This paper describes a practical approach to the development of a Laplace transfer function (TF) model of a (paper) mill load connected to this power system. A PSCAD/EMTDCTM simulation model of the mill (the detailed model) was built from available information on the types of load within the mill. This detailed model was verified in a piece-wise manner, e.g. against individual motor starts. Instead of using the available generic load models, system identification theory is applied to evaluate the transfer function load model from simulated small signal disturbance responses. The model is developed for both voltage and frequency changes, and considers the actual frequency range of inter-area oscillations within the power system. In this paper the focus of the work is to accurately represent the mill load behaviour for small signal disturbances. It is recognised that the large signal requirements of a load model for transient stability studies are also important but the inevitable non-linearity of such a model would tend to saturate the loads’ behaviour during lesser disturbances. The performance of the developed small signal load model is tested using some practical disturbance profiles from this power system. This modelling approach allows development work to commence before real-life disturbance measurements are available since such data is currently scant. However, modern high bandwidth monitoring has recently come on-line for the mill and the TF load model will be fully verified over time as disturbance data builds up.

Proper operation of the dry end of a paper machine requires some type of sheet tension control. Present systems use either indirect-speed-control-based schemes, or sensor-based direct tension control utilizing load cells or swing rolls. The indirect schemes are inadequate for most newer machines, and both types of the commonly used sensor-based schemes are invasive, expensive, require either special, or extra rolls, and add complexity to the sheet runs. This paper proposes and evaluates sheet tension estimation using only conventional motor and control signals, present in all newer drive controllers, integrated into a process model observer. This observer-based approach eliminates the need for the invasive tension transducers, and may also be used to replace the inaccurate indirect speed control schemes.

In this work, a new framework for control of power flow of an energy storage is proposed. As part of the framework, an advanced controller for manipulating the power flow of an energy storage system, a photovoltaic (PV) source, and the utility grid is developed. The new controller relies on the Model-based Predictive Control (MPC) concept. The proposed controller realizes an optimal control scheme that maximizes the local self-consumption of renewable energy source. At the same time, the energy consumption supplied by the electric grid is minimized subject to its price posted in the grid. The presented approach is evaluated through computer-aided simulations using data available from a real installation in Switzerland. The data consists of photovoltaic panels, industrial building as a load as well as a battery energy storage system (BESS).

In this paper, a methodology in developing a dynamic model for the pulp preparation in the head-box of paper machine is presented. The set of partial differential equations obtained from the mass balance is solved with respect of the boundary conditions in order to obtain the dynamic version of the model for control in the standard form of the state-space representation. A quantitative discussion on numerical control of multivariable systems with use the reference-model is also presented; it is illustrated how the internal model controller (IMC) can be designed and applied to multivariable systems. The application of the IMC to a head-box in pulp and paper industry is studied, and some simulation test results are presented and discussed in the numerical control manner. >

This paper investigates application of a multivariable control technique to the multi-input multi-output (MIMO) nonlinear model of the paper machine pressurized head box. The proposed controller design is based on a feedback linearization and LQ optimization method. The method can stabilize the system at operating point. In the last, we simulated the performance of pressurized head boxes with the new controller.

This paper considers the design of a controller and a constraint-enforcement scheme for application to dualmode, autonomous and manual steering systems. A tracking controller is designed to track a desired pinion angle during autonomous operation, and to provide assistive torque during manual operation. The tracking controller is designed using H ∞ synthesis with tracking made possible via the solution to a full-information output regulation problem. A reference governor scheme is implemented in order to enforce constraints. Numerical simulations are presented corresponding to an aggressive step-steer maneuver in autonomous mode and show strict constraint enforcement.

Feedforward of a new signal based on surface temperature measurements is introduced for the paper machine drying section and its performance is evaluated. Control of the moisture content is conventionally accomplished by adjusting the steam pressure in the cylinders. By adding feedforward to a previously presented mid-ranging control system using two manipulated variables, the disturbance rejection of the moisture control can be significantly improved.

In this paper, Genetic Algorithm (GA) method has been applied in the moisture control system for auto tuning (PID) parameters. Proportional – Integral – Derivatives control scheme is used to provide an efficient and quiet easier in control engineering applications. Most of the PID tuning methods are used as manually which is difficult and time consuming. Genetic Algorithm which leads to improve the efficiency of tuning of process. The proposed algorithm is used to tune the PID parameters and its performance has been compared with Fuzzy logic techniques.Compare to the fuzzy logic technique dynamic performance specfications such as rise time, peak time and peak overshoot optimal values produced by GA. The plant model represented by the transfer function is obtained by the system identification tool box.

Proportional – Integral – Derivatives control scheme is used to provide an efficient and quiet easier in control engineering applications. Most of the Conventional PID tuning methods are used in manually which is difficult and time consuming. Soft Computing Technique is used to overcome this problem by using Fuzzy logic technique. In this research focuses dynamic performance specification is such as rise time, settling time and peak over shoot. This paper proposes to compare conventional and non-conventional techniques and the result of this comparison, The non-conventional technique (Fuzzy logic) has optimal dynamic performance. The plant model is represented by the transfer function, is obtained by the system identification tool box.

This paper presents an improved dynamic matrix control (DMC) algorithm that is suitable for measurement failure and its application for the baseweight control of a paper machine. The main idea of the refined DMC algorithm is to replace the output of a plant with the model output of DMC when measurement failure happens, that is, to control the model by using DMC. To achieve the aim of accurate prediction of the plant output when measurement failure happened, the standard model based prediction in DMC algorithm is improved by replacing the open loop prediction with a close loop prediction. This proposed algorithm has been applied to baseweight control of a paper machine, and the results show that it can process the measurement failure caused by paper breakage in the production process. >

The paper-making process is very complex, there exists long delay time, grievous nonlinearities and time-varying parameters. The paper presents a neuron model-free control method in which the neuron gain is regulated adaptively for the paper-making process. This procedure can control the process with long delay time and great range of open-loop gain variation efficiently. The simulation results for a complex paper machine is satisfying, good performances in robustness and adaptability are obtained.

Paper tension is the most important control parameter in roll material production that directly impacts the printing quality of the web offset. Based on the closed-loop paper tension control theory, by conducting a research into the simulation of paper tension control system with MATLAB/SIMULINK, presented the closed-loop control diagram about the paper tension control system. Under different control parameter, the value of the overshoot, respond speed and residual of the system varies. As a result, the quantitative research on the simulation of the system offers a valid means in improving the control accuracy.

This paper considers /spl Hscr//sub /spl infin// robustification of an industrial paper machine cross-directional (CD) control system. The existing industrial controller is reinterpreted as a precompensator weight for shaping the open-loop response. The robustification is then achieved by performing a robust stabilization of the nominal plant model and industrial controller combination. The large scale (226 inputs and 226 outputs) /spl Hscr//sub /spl infin//. optimization problem is decoupled into 226 independent SISO systems by an application of recent results for spatially invariant systems. The robustified closed-loop is then implemented by augmenting the industrial controller with a low-order prefilter. It is then demonstrated that the robustness of the closed-loop system has been significantly improved while its performance remains well-preserved.

Concerns the development of a dynamic model of a 5-ply board machine producing packaging board. Three models were developed in decreasing order of complexity. First a detailed dynamic model of the short circulations was built using Simons IDEAS, which is a special purpose dynamic simulation package intended for the pulp and paper industry. This full model contained a comprehensive differential and algebraic equation set so consequently quickly became too unwieldy for the intended uses of troubleshooting, aiding retrofits and model-based control studies. A slightly simplified version of this model was re-engineered in Simulink, dropping the algebraic constraint equations and implementing the transport delays in a more elegant manner. Finally transfer function models, suitable for online control and optimisation tasks were identified from production data with a structure given by semi-rigorous reasoning. All three models were adjusted and subsequently validated against almost one year of plant operating data. This paper highlights the difficulties in validating a large industrial system with widely varying time constants, dubious transducers and the ubiquitous noise. We also discuss the necessary, but delicate, task of performing model reduction; contrast different simulation tools used at the various levels of model hierarchy and finally the paper demonstrates the use of simplified models to improve the performance of the adaptive IMC controller for the basis weight in the finished board.

This paper presents a compound fuzzy control algorithm method having modifiable factors based on PLC, and the modified fuzzy controller and PI regulator is realized by PLC, the system solves problems of imprecise paper cutter speeds, instability, and paper cuttings of different lengths. The results show that the system can effectively restrain influences from pure time-delays while maintaining stability and strong robustness.