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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 describes a flow control of the dye in the paper mill with the quasi-Z-source indirect matrix converter (QZSIMC) fed induction motor drive. More than a decade the voltage-source inverter (VSI) and current-source inverter (CSI) have been used to control the speed of the induction motor, which in turns controls the flow of dye. Recently, the matrix converter (MC) has been an excellent competitor for the VSI or CSI for its compactness. The voltage transfer ratio of the VSI, CSI, and MC has been limited to 0.866. Thus, the efficiency of these converters is less. To improve the voltage transfer ratio the quasi-Z-source network (QZSN) is to be used between voltage source and indirect MC (IMC). The modification in the shoot-through duty ratio of the QZSN varies the voltage transfer ratio greater than 0.866. Different voltage transfer ratios are needed for different voltage sag conditions. For a variation of the duty ratio of the QZSN, the fuzzy logic controller has been presented. To control the IMC vector control with space vector modulation has been presented. This paper proposes the implementation of QZSIMC adjustable speed drive for the flow control of dye in paper mill during different voltage sag conditions. A 4-kW prototype has been built and the effectiveness of the proposed system is verified with simulation results and experimental setup. Simulation is done in MATLAB, Simulink platform. Experimental setup is done with the aid of a TMS320F2812 (Texas Instrument) processor. The experimental results validate the maintenance of the speed of an induction motor at the set condition, thus controlling the perfect flow of dye in paper manufacturing technology.

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.

This paper presents the design of a fractional order combined model reference adaptive control scheme. This approach is based on the estimates of the plant unknown parameters and the adjusted controller parameters, which are obtained from adaptive laws using the identification error, the control error and the so called closed loop estimation errors. Fractional order indirect algebraic model reference adaptive control and fractional order indirect dynamic model reference adaptive control schemes are also proposed in this paper, which are used for comparison purposes with the combined approach. Boundedness of all the signals in the control schemes is analytically proved, as well as the convergence to zero of the mean values of the control, identification and closed loop estimation errors. Simulation results are presented to show the effectiveness of the proposed control strategies.

To extend inverted decoupling control method to the non-square multivariable time delay system, this paper presents a block inverted decoupling control approach with internal model structure. In this method, the non-square system is divided into two subsystems, and the decoupling structure is composed of two blocks. Each block in the designed structure is applied to each subsystem. With the proposed method, complex matrix computations are avoided, and the designed controller has low order. The stability of closed-loop system with the proposed method is analyzed in the paper. Numerical simulations are performed to illustrate the effectiveness of this methodology.

The paper proposes a reconfigurable control design of steering and torque vectoring using a variable-geometry suspension system. Torque vectoring control is based on the independent driving of the wheels. Simultaneously, the steering angle is generated by the variable-geometry suspension system by varying the camber angle of the front wheels. The efficiency of wheel tilting and torque vectoring, and their coordinated actuation are in the focus of the paper. In the analysis a reachable set computation method on the polynomial model of the vehicle based on the trajectory reversing method and the Sum-of-Squares (SOS) programming is proposed. Based on the analysis results a reconfigurable control is designed using the Linear Parameter Varying (LPV) method.

Critical sections of a paper machine such as the wet end presses, size press, on-machine coater, and reel may be required to undergo large and fast load changes in normal operation. These changes must result in minimum disturbance to the ingoing sheet tension or nip roll speed in order to avoid sheet breaks or wrinkling. This paper evaluates two disturbance-rejection control techniques, one using disturbance feedforward (or disturbance input decoupling) based on a nip-pressure disturbance observer and the other using a two-degrees-of-freedom controller. Evaluations were done in both a press section and a size press section of a lightweight paper machine, and the results showed that both methods are very effective in reducing the maximum speed deviation to about 10% of the values without compensation and can operate combined with torsional oscillation compensation without interference between them

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.

Cross direction (CD) control in sheet-forming process forms a challenging problem with high dimensions. Accounting the interactions between different properties and actuators, the dimensionality increases further and also computational issues arise. We present a multiple property controller feasible to be used especially with imaging measurements that provide high sampling frequency and therefore enable short control interval. The simulation results state the benefits of multiple property CD control over single property control and single property control using full feedforward compensation. The controller presented may also be tuned in automated manner and the results demonstrate the effect of tuning on input saturation.

A mechanistic nonlinear model of the wet end of paper machine 6 (PM6) at Norske Skog Saugbrugs, Norway has been developed, and used in an industrial MPC implementation. The MPC uses an infinite horizon criterion, successive linearization of the model, and estimation of states and parameters by an augmented Kalman filter. Variation in important quality variables and consistencies in the wet end have been reduced substantially, compared to the variation prior to the MPC implementation. The MPC also provides better efficiency through faster grade changes, control during sheet breaks and start ups, and better control during periods of poor measurements. From May 2002 of the MPC has been the preferred controller choice for the process operators at PM6. In this paper we also study if the model can be applied to PM4 at Norske Skog Saugbrugs, and PM3 at Norske Skog Skogn, Norway. No structural changes were necessary in order to fit the model to PM4 and PM3 data. The time spent on fitting the PM6 model to PM4 and PM3 is approximately 1% of the time spent on developing the original model. This should be a strong incentive for focusing on mechanistic modeling in industries were there are many similar production lines or units.

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 paper deals with the fault-tolerant reconfigurable control design of a four-wheel independently-actuated (4WIA) electric vehicle. The purpose of the proposed method is to ensure the velocity and path tracking of the 4WIA vehicle in the event of a fault or performance degradation in one or even several in-wheel electric motors. The novelty of the presented method is the high-level control reallocation method based on the Linear Parameter Varying (LPV) control framework, by which the torque vectoring and steering of the vehicle are modified in order to deal with the impact of faulty in-wheel motors. The operation of the designed fault-tolerant method is validated in CarSim simulation environment.

A controllability analysis of a paper machine forming zone in a newsprint mill was performed to determine the maximum allowable variability of the pulp furnished to the process. The goal was to keep the output variables, basis weight and first-pass retention between certain limits in spite of disturbances and paper grade changes. The results indicate that the process is more disturbed at high frequencies, and that the two output variables may be maintained within the interval ±1% of their nominal values if the maximum variability in the consistency and fines content of the thick-stock is kept lower than ±1 and ±2%, respectively.

In pulp and paper plants, power transformers play a critical role in process continuity. These transformers are subject to internal short circuits, external short circuits, and abnormal operating conditions. The following protection challenges to power transformers will be explored, and methods to improve the protection are provided. First, remanence in a current transformer (CT) may cause misoperation of phase differential protection due to compromised CT performance. Heavy through-faults, sympathetic inrush, and recovery inrush all cause high current. This, combined with high remanent flux, can create a security issue. IEEE CT performance calculations will be used to support the use of dual slope differential characteristics to promote secure differential protection operation when challenged with unequal CT performance. Second, on transformer energizing, the second harmonic current has been traditionally used as a means to prevent phase differential misoperation. Certain transformers may not exhibit high enough the second harmonic, causing a dependability issue if the restraint is set too low. The use of the second and fourth harmonics for inrush detection will be shown to enhance the reliability during energizing inrush situations. Third, overexcitation can occur from abnormal operation of the utility system or the plant's excitation control. Causes of overexcitation will be outlined and the use of volts per hertz protection is explored. With overexcitation occurring from system voltage rise, the phase differential protection has been traditionally blocked using the fifth harmonic restraint. This may cause an undesired nonoperation of the phase differential protection if an internal fault occurs while the transformer is overexcited, causing a delay in tripping and severe damage to the transformer. A technique using adaptive phase differential pickup value will be illustrated to overcome this challenge. Finally, on resistance-grounded power transformers, phase differential protection sensitivity for ground faults near the neutral is decreased. The use of ground differential protection will be explored and the increased sensitivity gained will be demonstrated.

A mechanistic nonlinear model of the wet end of paper machine 6 (PM6) at Norske Skog Saugbrugs, Norway has been developed, and used in an MPC application. The MPC provides reduced variability in many key variables, and better efficiency through faster grade changes, start ups, and improved control during periods of poor measurements. The model and controller can be rolled-out to other paper machines, as found by studying and fitting the model to data from PM4 at Norske Skog Saugbrugs, and PM3 at Norske Skog Skogn, Norway. No changes to the model, except for parameter values, were introduced, and still the validation results were good. The time spent on fitting and validating the PM6 model to PM4 and PM3 are approximately 1% of the time spent on developing the original model. This should be a strong incentive for focusing on mechanistic modeling in industries were there are many similar production lines or units.

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.

Inertial stabilized platforms are extensively used to keep the light of sight free from the effects of vehicle motion or vibration. In order to reduce the assembly difficulty and cost as well as achieve an accurate pointing in the presence of disturbances, a finite-time output feedback control strategy is proposed. On the basis of the dynamic model with both matched and unmatched uncertainties, two high-order sliding mode observers are designed to estimate the newly defined virtual state and the lumped uncertainty, respectively. Combing with the nonsingular terminal sliding mode technique, an output feedback control based on the estimates and the output is developed. The proposed method can achieve not only stability and robustness against uncertainties but also the finite-time convergence to the desired angular rate without control chattering. Finally, the comparative simulations are performed to show the effectiveness of the proposed method.

The problem of curse-of-dimensionality in finite state and action Markov decision processes is considered using iterative clustering of closed-loop data and repeated discretization of the state space process model. The performance of the control design approach is demonstrated using a multi-input van der Vusse continuous stirred tank reactor control benchmark. It is demonstrated that the finite state description provides a simple implementation of Bayesian state estimation using cell filters, and dynamic programming gives means to conduct optimization of closed-loop performance of a nonlinear stochastic multidimensional chemical plant.

A machine that transports paper sheet by using a pair of flat belts, handles various paper sheet with regard to size, thickness and texture. This often causes the gap between the sheets to change when it is transported over a long distance. If the gap becomes shorter than a certain threshold value, it causes sheet jam. We have therefore developed a gap control system that determines the transport distance of sheets and measures the gap change before the sheets reach the gap controller. Using thses information, it estimates the gap change after the gap controller and sets a target value. The contoller varies the transport velocity in an optimum pattern and controls the gap to the target value. We applied the system to a transport route and it reduced the standard deviation of gap into 2/3.

The choice of this investigation is to tune the proportional-integral-derivative (PID) parameters separately for controlling the moisture content in paper industry by using Particle Swarm Optimization (PSO). This paper boon a new algorithm for PID controller tuning based particle swarm optimization. PSO algorithm has recently developed as a very powerful method for real parameter optimization. This new process is proposed to combine both the algorithms to get better optimization values. The proposed algorithm tuned the PID parameters and its performance has been compared with PID algorithm. Compared to PID algorithm technique, dynamic performance requirements such as rise time settling time and peak overshoot optimal values produced by PSO. The plant model represented by the transfer function is obtained by the system identification toolbox.

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.

This paper presents an application of Generalised Predictive Control (GPC) to the paper machine benchmark. The plant features a relatively large dead-time and severe retention level variation at the wire section. From simulations, results show that the controller has good performance when the the retention levels are at their nominal values, and that there is large output variation if the retention varies as specified.

To increase the efficiency of photovoltaic (PV) systems, maximum power point (MPP) tracking of the solar arrays is needed. Under partially shaded conditions (PSCs), the solar arrays power–current (P–I) characteristic has multiple MPP. This paper presents various methods and approaches of tracking the MPP from a PV generator operating under PSC. Some comparisons, advantages, drawbacks and critical analysis of each method are discussed. It was found that, indirect methods use empirical data or mathematical expressions of numerical approximations to estimate the MPP from the PV generator’s voltage, current and irradiance. Direct methods offer the advantage of obtaining the actual maximum power from the PV generator’s voltage and current. Artificial intelligence methods do not need exact mathematical models. They can perform under parameter variation, load and supply voltage disturbances. Finally, novel methods require less number of iterations to converge, independent to the initial conditions. All t...

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.

This paper concerns the global cooperative output regulation problem for a class of nonlinear multi-agent systems with unknown control directions and unknown exosystem. The communication among agents makes it difficult to implement the Nussbaum gain technique to handle the non-identical unknown control directions. Moreover, the unknown parameter in the exosystem, which cannot be easily handled by the estimators in existing results, makes our problem more intricate. To overcome these challenges, we employ a novel internal model candidate to develop a two-layer control scheme for an adaptive distributed controller design. Theoretic stability analysis is presented and a numerical example is given to show the effectiveness of the proposed controller.

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.

Model-based controllers based on incorrect estimates of the true plant behaviour can be expected to perform poorly. This work studies the effect of model plant mismatch on the closed loop behaviour and system performance for a certain class of MIMO systems. Performance is measured using a minimum variance index and a closely related user-specified criterion. We study the effect of model plant mismatch on the output variance and performance indices. Under mild assumptions, the performance of each output in a MIMO system can be analysed independently. Moreover, we propose an approach to distinguish the effect of model–plant mismatch from the effect of changes in disturbance characteristics on closed-loop performance. We define a sensitivity measure that relates system performance to model–plant mismatch, and use it to explore this sensitivity for three realistic types of parametric modelling errors. Next, we suggest a quantitative method that compares a system's actual output to its desired response in a transient setting. The performance of the transient response is demonstrably more sensitive to the model–plant mismatch than the steady state performance. The results are illustrated on industrial paper machine data.

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.

The paper focuses on the robust control design of a look-ahead cruise control system. The aim of the look-ahead control is to consider the topographic conditions and speed regulations of the oncoming road sections. The look-ahead cruise control leads to an optimization method, which generates a fuel and time optimal reference speed for the vehicle. It requires external topographic and road information, and measurements concerning the vehicle, such as speed and acceleration. Since the signals of the vehicle are considered in the generation of the reference speed, the generator has an impact on the stability of the cruise control system. In the paper a robust H∞ cruise control design method is proposed, which considers the efect of the reference speed generation, and guarantees the stability and the speed tracking performance of the entire system. The efciency of the method is analyzed through a simulation example with real highway data.

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.

A semi-physical auto-regressive moving average model of bending stiffness of the board produced at Assi Doman-Frovifors Bruk AB, as a function of measured control and disturbance variables, was identified. Based on the bending stiffness model, an adaptive on-line bending stiffness index predictor was implemented and found to have an RMS-error within the laboratory measurement accuracy. The predictor has been running for several months and consistently has a prediction accuracy of more than 75% within ± one standard deviation, for all product grades. The main difficulty in developing the predictor was that bending stiffness is seldom measured. The predictor will form the basis of a model predictive regulator of the bending stiffness.

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.

The objective of this paper is to address the problem of state estimation in an Anaerobic Digestion Reactor (ADR) with unknown inputs - typically some influent concentrations, and to compare two different state and input estimation schemes. The first one is the classical Extended Kalman Filter (EKF) based on an augmented system that considers a slowly varying input (approach that has been already applied to this system and reported in the literature), whereas the second one is a recently proposed Unknown Input Observer (UIO), formulated in the spirit of a Kalman Filter, for continuous estimation with discrete measurements. The two filters are evaluated in simulation, demonstrating the superiority of the UIO.

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, a novel coordinated control method is proposed to handle the negative voltage impacts on weak sub-transmission systems, which are caused by wind power fluctuations. Firstly, wind variations are divided into large and small fluctuations. Then, according to the different control characteristics of on-load tap changers (OLTCs) and static compensators (STATCOMs), the OLTCs are used to minimize the impacts caused by large fluctuations, while the STATCOMs are used to eliminate the impacts introduced by small fluctuations. The model predictive control (MPC) and a consensus based distributed control techniques are adopted to design the control schedules of OLTCs and STATCOMs, respectively. It is shown that by the coordination of OLTCs and STATCOMs, voltage violations of points of interconnection (POIs) are eliminated, and voltage fluctuations at unregulated load buses are mitigated. The effectiveness of our proposed control scheme is presented through a case study on the modified IEEE 14-bus test system with a real wind power profile. According to the simulation results, it turns out that the proposed approach can reduce the operation number of OLTCs significantly, and decrease the required capacity of STATCOMs dramatically by comparison with the existing control scheme.

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).

A method for the control of basis weight by supervisory optimization is worked out. The objective is to determine the optimum supervisory machine speed and basis weight set point adjustments to maximize the profitability of production subject to the constraints of plant operation. The cost function consists of production cost and the loss due to rejects. An optimization scheme is worked out to calculate an optimization policy. Furthermore, the machine speed versus profit relations are developed to arrive at a supervisory machine speed that provides the globally minimized cost (maximized profit). The sampled measurements are processed to determine the variance and expected values of process variables. The expected values are used by the optimization system to determine the set point adjustments (corrections) by using the production and reject cost data. The supervisory machine speed is determined based on the optimum cost values of operation at various speeds to reach a globally minimum cost value. The implementation by distributed control systems is described, including the benefits of such a system.

The paper presents the application of the Cole-Cole model for determining the runs of the return voltage of the paper-oil insulation sample through a computer simulation. Different insulation conditions were simulated through an adequate selection of parameters ? and ? of the Cole-Cole model. For calculation purposes, a series - parallel substitute scheme, obtained through approximation of discrete characteristic operator impedance Za of the model applied, was used. The diagnostics of the simulated insulation condition was based on the analysis of a few selected parameters of the return voltage, obtained from time characteristics.

In the automation field product quality, time to market, number of workers required for the production, cost, technology, ease of availability of components etc. are all important considerations to increase the company profile in the market. All are depends on the controlling actions and the technology used for it. Based on the application different controlling actions are taken place like Programmable Logic Controller (PLC), Distributed Control System (DCS), Supervisory Control And Data Acquisition (SCADA), image processing etc. among these, image processing uses camera and the controller or processor for automation process. Here to increase the production speed, reduce the cost and based on ease of availability of components line scan sensor and Beagle Board is used for controlling the process. Using these, the line scan camera is designed and image processing is done for detecting the defects present in the object moving on the conveyor line and the controlling action will be taken by itself. Using single Beagle Board the camera is designed as well as controlling action is taken.

The detection and control of the dry line machine direction position on a fourdrinier paper machine are considered. The dry line position is detected using a digital image processing system consisting of a CCD camera, a frame grabber and a standard PC. The system was installed on a kraft liner machine and both open loop and closed loop experiments were performed with encouraging results. The introduction of automatic control of the dry line position reduces the time for grade changes and it also reduces the machine operators work load. The reduced time leads to smaller production losses and hence to economical benefits. Godkänd; 1998; 20061029 (ysko)