Dynamic Process Control Research Articles

Acceptance Speech of Arthur J. Krener for the 2012 Richard E. Bellman Control Heritage Award [People in Control

In this issue of IEEE Control Systems Magazine (CSM), this column ends with Arthur Krener's acceptance speech for the 2012 Richard E. Bellman Control Heritage Award given in Montréal, Canada, in June 2012. He is a mathematician whose research interests are in developing methods for the control and estimation of nonlinear dynamical systems and stochastic processes. In 1971 he received the Ph.D. in Mathematics from the University of California, Berkeley, and joined the faculty of the University of California, Davis (UCD). He retired from UCD in 2006 as a Distinguished Professor of Mathematics and he currently is a Distinguished Visiting Professor at the Naval Postgraduate School. He has also held visiting positions at Harvard University, Imperial College, NASA Ames Research Center, the University of Paris, the University of Maryland, the University of Padua, North Carolina State University, and the University of California, Berkeley. Honors and awards include Fellow of the Society for Industrial and Applied Mathematics (SIAM), Life Fellow of the IEEE, the W.T. and Idalia Reid Prize in Mathematics from SIAM, the IEEE Control System Society Bode Prize Lecture, and the Richard E. Bellman Control Heritage Award from the American Automatic Control Council.

The Design and Control of Distillation Column with Side Reactors for Chlorobenzene Production

The distillation column with side reactors (SRC) can overcome the temperature/pressure mismatch in the traditional reactive distillation, the column operates at temperature/pressure favorable for vapor-liquid separation, while the reactors operate at temperatures/pressures favorable for reaction kinetics. According to the smooth operation and automatic control problem of the distillation column with side reactors (SRC), the design, simulation calculation and dynamic control of the SCR process for chlorobenzene production are discussed in the paper. Firstly, the mechanism models, the integrated structure optimal design and process simulation systems are established, respectively. And then multivariable control schemes are designed, the controllability of SRC process based on the optimal steady-state integrated structure is explored. The dynamic response performances of closed-loop system against several disturbances are discussed to verify the effectiveness of control schemes for the SRC process. The simulating results show that the control structure using conventional control strategies can effectively overcome feeding disturbances in a specific range.

Persistence of Motor-Equivalent Postural Fluctuations during Bipedal Quiet Standing

Theoretical and empirical work indicates that the central nervous system is able to stabilize motor performance by selectively suppressing task-relevant variability (TRV), while allowing task-equivalent variability (TEV) to occur. During unperturbed bipedal standing, it has previously been observed that, for task variables such as the whole-body center of mass (CoM), TEV exceeds TRV in amplitude. However, selective control (and correction) of TRV should also lead to different temporal characteristics, with TEV exhibiting higher temporal persistence compared to TRV. The present study was specifically designed to test this prediction. Kinematics of prolonged quiet standing (5 minutes) was measured in fourteen healthy young participants, with eyes closed. Using the uncontrolled manifold analysis, postural variability in six sagittal joint angles was decomposed into TEV and TRV with respect to four task variables: (1) center of mass (CoM) position, (2) head position, (3) trunk orientation and (4) head orientation. Persistence of fluctuations within the two variability components was quantified by the time-lagged auto-correlation, with eight time lags between 1 and 128 seconds. The pattern of results differed between task variables. For three of the four task variables (CoM position, head position, trunk orientation), TEV significantly exceeded TRV over the entire 300 s-period.The autocorrelation analysis confirmed our main hypothesis for CoM position and head position: at intermediate and longer time delays, TEV exhibited higher persistence than TRV. Trunk orientation showed a similar trend, while head orientation did not show a systematic difference between TEV and TRV persistence. The combination of temporal and task-equivalent analyses in the present study allow a refined characterization of the dynamic control processes underlying the stabilization of upright standing. The results confirm the prediction, derived from computational motor control, that task-equivalent fluctuations for specific task variables show higher temporal persistence compared to task-relevant fluctuations.

Dynamic process control and monitoring of novel S3RS based hydrogen cooling system

Hydrogen gas is circulated in a closed loop within the generators to remove heat from its active parts. Then it is cooled by gas-to-water heat exchangers that are part of the stator frame. Faster heat dissipation of generators in power plant call for hydrogen cooling system (HCS) at generating end. Purity in hydrogen (H2) improves its ability to dissipate heat within generators. Therefore, there is an essential requirement of a highly reliable and efficient process control and monitoring system of H2 cooling. This paper presents development and implementation of supervisory control and data acquisition (SCADA) based process control and monitoring system. It proposes a novel six stage standby redundant structured (S3RS) HCS for generators cooling in typical thermal power plant. The entire process control and monitoring of HCS has been developed and simulated on RSViewSE, a real-time industrial automation platform by Allen Bradley–Rockwell Automation. And, the system reliability of proposed S3RS process model is implemented using MATLAB. This process model satisfies the requirement of IEEE Std. C37.1™-2007, the standard for SCADA and Automation Systems. It also follows IEEE Std. 493™-1997, the standard for design of reliable industrial and commercial power systems, and IEC 60034-3, the standard for rotating electrical machines.

Dynamic and collective analysis of membrane protein interaction network based on gene regulatory network model

Membrane protein interactions are vitally important for every process in a living cell. Information about these interactions can improve our understanding of diseases and provide the basis to revolutionize therapeutic treatments. However, current experimental techniques for large-scale detection of protein–protein interactions are biased against membrane proteins, it is necessary to develop novel tools to deal with this kind of bio-network. To realize this, we construct membrane protein interaction network based on gene regulatory network model. Three model forms, basic form, non-dimensionalization form, and more complex form, are proposed to understand the dynamic and collective control of developmental process and the characters of membrane protein interaction network, including small-world network, scale free distributing and robustness, and its significance for biology. Four simulation examples are presented to illustrate the usefulness and flexibility of the GRN model method for the study of membrane protein interaction network. The results show that the proposed approach holds a high potential to become a useful tool in prediction of membrane protein interactions. Moreover, it has biological significance and value for biology and pharmacology.

Study on Storey Dynamic Control of Laser 3D Deposition Process Based on PMAC

The purpose of this study is to implement the dynamic control of single-storey height by adding hight detection devices based on PMAC in the existing three-dimensional laser processing systems.In order to overcome the rough topography of the forming parts and eliminate the phenomenon of jagged edge,it is important to ensure consistency between single-storey height- h and Z axis single-upgrade- Z.

Intelligent control of braking process

Intelligent modeling, prediction and control of the braking process are not an easy task if using classical modeling techniques, regarding its complexity. In this paper, the new approach has been proposed for easy and effective monitoring, modeling, prediction, and control of the braking process i.e. the brake performance during a braking cycle. The context based control of the disc brake actuation pressure was used for improving the dynamic control of braking process versus influence of the previous and current values of the disc brake actuation pressure, the vehicle speed, and the brake interface temperature. For these purposes, two different dynamic neural models have been developed and integrated into the microcontroller. Microcontrollers are resource intensive and cost effective platforms that offer possibilities to associate with commonly used artificial intelligence techniques. The neural models, based on recurrent dynamic neural networks, are implemented in 8-bit CMOS microcontroller for control of the disc brake actuation pressure during a braking cycle. The first neural model was used for modeling and prediction of the braking process output (braking torque). Based on such acquired knowledge about the real brake operation, the inverse neural model has been developed which was able to predict the brake actuation pressure needed for achieving previously selected (desired) braking torque value in accordance with the previous and current influence of the pressure, speed, and the brake interface temperature. Both neural models have had inherent abilities for on-line learning and prediction during each braking cycle and an intelligent adaptation to the change of influences of pressure, speed, and temperature on the braking process.

Control of Quantum Dynamical Processes

Control of Quantum Dynamical Processes

Predicting Team Performance in a Dynamic Environment

Teams that operate in complex and dynamic environments must maintain a certain level of cognitive readiness among team members to ensure high levels of performance in response to potentially uncertain and time sensitive situations. In the current study, the authors sought to identify a physiological measure that could help predict team performance during a complex and dynamic task. Specifically, they examined whether measuring team members’ autonomic nervous system activity could predict subsequent performance on a dynamic process control task. Thirty-four teams of two (35 males, 33 females) completed a processing plant simulation during four varying levels of individual and team difficulty. Sympathetic and parasympathetic nervous system activity was measured throughout the task with an electrocardiogram and an impedance cardiogram and was combined to create a measure of team autonomic activity. Regression analyses showed that team autonomic activity accounted for 10% of the variance in team performance scores. In conclusion, the current study showed that team performance can be predicted from team autonomic activity, which supports the argument that a team’s physiological state could serve as an indicator of cognitive readiness.

Interfacial layers from the protein HFBII hydrophobin: Dynamic surface tension, dilatational elasticity and relaxation times

The pendant-drop method (with drop-shape analysis) and Langmuir trough are applied to investigate the characteristic relaxation times and elasticity of interfacial layers from the protein HFBII hydrophobin. Such layers undergo a transition from fluid to elastic solid films. The transition is detected as an increase in the error of the fit of the pendant-drop profile by means of the Laplace equation of capillarity. The relaxation of surface tension after interfacial expansion follows an exponential-decay law, which indicates adsorption kinetics under barrier control. The experimental data for the relaxation time suggest that the adsorption rate is determined by the balance of two opposing factors: (i) the barrier to detachment of protein molecules from bulk aggregates and (ii) the attraction of the detached molecules by the adsorption layer due to the hydrophobic surface force. The hydrophobic attraction can explain why a greater surface coverage leads to a faster adsorption. The relaxation of surface tension after interfacial compression follows a different, square-root law. Such behavior can be attributed to surface diffusion of adsorbed protein molecules that are condensing at the periphery of interfacial protein aggregates. The surface dilatational elasticity, E, is determined in experiments on quick expansion or compression of the interfacial protein layers. At lower surface pressures (<11mN/m) the experiments on expansion, compression and oscillations give close values of E that are increasing with the rise of surface pressure. At higher surface pressures, E exhibits the opposite tendency and the data are scattered. The latter behavior can be explained with a two-dimensional condensation of adsorbed protein molecules at the higher surface pressures. The results could be important for the understanding and control of dynamic processes in foams and emulsions stabilized by hydrophobins, as well as for the modification of solid surfaces by adsorption of such proteins.

Fault detection in dynamic processes using a simplified monitoring-specific CVA state space modelling approach

State space models have been successfully used for the modelling, control and monitoring of dynamic processes with several different approaches employed to derive the state variables of the model. Typically, state-space canonical variate analysis (CVA) modelling requires the estimation of five matrices to fully parameterize the model. This paper proposes a simpler CVA state space model defined by three matrices for the specific purpose of process monitoring. A modified definition of the past vector of inputs and output is proposed in order to facilitate efficient estimation of a reduced set of state space matrices. A sequential procedure for accurate selection of the model state vector dimension is also proposed. The proposed method is applied to the benchmark Tennessee Eastman process and the results show that the proposed method gives comparable and in some cases even better performance than the established CVA state space monitoring methods.

Dynamic simulation and control of auto-refrigerated CSTR and tubular reactor for bulk styrene polymerization

Dynamic simulation and control of a two-stage continuous bulk styrene polymerization process is developed to predict the performance of auto-refrigerated CSTR and tubular reactors. The tubular reactor is subdivided into three temperature-control jacket zones. In this paper temperature control of auto-refrigerated continuous stirred tank reactor and tubular reactor are carried out, simultaneously. Two strategies are proposed for the control of tubular reactor. At the first strategy the controlled variable is jacket temperature and in the second strategy the controlled variable is the reactor temperature at the exit of each section. The set points for polymer grade transition are obtained using optimization of reactors temperatures via genetic algorithm (GA). Simulation results show that both of the control strategies are successful but second strategy has better performance in the control of polymer properties in the presence of disturbance and model mismatch.

New approach towards dynamic modelling of dephosphorisation in converter process

A new approach was made to model the dephosphorisation process in a 300 tons basic oxygen furnace converter with three argon gas inlets. The main feature of the new approach was to utilise the velocity vectors obtained by computational fluid dynamics (CFD) simulation in a standalone model. The CFD simulation was carried out using commercial software COMSOL Multiphysics. In the standalone model, the steel melt domain was sliced into 1000 cells. The calculated velocity vector in each cell was assumed constant. Based on the imported velocity vectors from the CFD calculation, the mass transfer of carbon and phosphorus was calculated by taking into account the slag–metal reactions. The mass exchange between slag and metal was considered to be dominated by the metal droplet formation due to the oxygen jet. The convergence of the model calculation and the promising comparison between the model prediction and the industrial data strongly suggested that the proposed approach would be a powerful tool in dynamic process control. As a preliminary step, the model only simulated the process after the formation of slag–metal–gas emulsion. Note that the present work is intended to establish a structure of the model. More precise descriptions of other process aspects need to be included before the model can be practically employed in a dynamic controlling system.

Coordinated Control of Speed during Driving Mode Switches for Parallel Hybrid Electric Vehicles

This paper studies the coordinated control of dynamic process of mode-switches for parallel hybrid electric vehicles (PHEV) during work. PID and fuzzy control algorithms are used to regulate the process of speed coordination in terms of look-up tables obtained from FC2000 testing system. Simulation results illustrate the PID controller has a better response for the dynamic coordinated control of speed in the small range variation of working conditions, so as to ensure the speed stability.

Control of Dynamical Processes in Solution: An Overview and Personal Perspective

AbstractA brief overview of studies of optical control of dynamical processes in solution is presented, with a focus on control of selection of product in a chemical reaction. It is argued that there are circumstances under which adiabatic population transfer in the liquid phase is possible, and that variations of such transfer processes can be used to control dynamical processes in solution.

General cybernetic model for innovation network management

Lately, due to intensive global competition, both academic and market society have paid more attention to concepts such as ‘open innovation’ and ‘innovation network’. To make a constructive literature review, at first, in this paper, theoretical aspects and literature of innovation network and its management are reviewed and examined. This review shows that most studies have limited their investigation and the development of the model to their particular views and applications. In other words, there rarely exist comprehensively and systematically framework developed in the literature. This paper emphasizes on the development of a comprehensive and systematic model for innovation network management. For this purpose, the literature is analysed and the related aspects and factors are classified. This led to the categories consisting of: building blocks of network management, managing innovation, dimensions of relational network, types of innovation and performance. Also, due to the complexity inherent in dynamic systems, management and control processes for innovation networks are often non-linear and hard to observe and control. In addition, knowledge about regulation, control and communication functions in any system is known as ‘cybernetics’ which is closely related to control theory and systems theory subjects. Finally, this paper by using cybernetics and assigning classified theoretical aspects toa general cybernetic model develops a comprehensive innovation network model.

A Novel Optical Method for Real-Time Control of Bolt Tightening

A digital speckle pattern interferometry (DSPI) system is developed for the real-time measurement and monitoring of the out-of-plane surface deformation around a preloaded bolt head or nut. The proposed system is specifically developed for the dynamic control of the bolt tightening process by continuously monitoring the out-of-plane joint surface deformation that will have been independently correlated to the bolt preload. Spatial phase shifting is employed to quantitatively determine the distribution of phase data by introducing a spatial carrier fringe pattern to the speckle interferogram. This is achieved by leading the object and reference beams through two separate apertures. The configuration is also suitable for collecting the real-time surface deformation during bolt tightening. The experimental DSPI system is set-up with optical components on a vibration-isolation table. A MATLAB software is developed for image acquisition and phase data calculations that yield the out-of-plane surface deformation caused by the bolt preload. The test fixture uses an M12 steel fastener and aluminum joint. For miniature screw applications, however, a plastic joint is used.

Experimental control of the transition from Markovian to non-Markovian dynamics of open quantum systems

Realistic quantum mechanical systems are always exposed to an external environment. The presence of the environment often gives rise to a Markovian process in which the system loses information to its surroundings. However, many quantum systems exhibit a pronounced non-Markovian behavior in which there is a flow of information from the environment back to the system, signifying the presence of quantum memory effects [1-5]. The environment is usually composed of a large number of degrees of freedom which are difficult to control, but some sophisticated schemes for modifying the environment have been developed [6]. The physical realization and control of dynamical processes in open quantum systems plays a decisive role, for example, in recent proposals for the generation of entangled states [7-9], for schemes of dissipative quantum computation [10], for the design of quantum memories [11] and for the enhancement of the efficiency in quantum metrology [12]. Here we report an experiment which allows through selective preparation of the initial environmental states to drive the open system from the Markovian to the non-Markovian regime, to control the information flow between the system and the environment, and to determine the degree of non-Markovianity by direct measurements on the open system.

Masterbox: new concept for a dynamic autoclave process control

A new concept for autoclave process control is being presented, which is currently developed in the DLR’s (German Aerospace Centre) project OnQA (Online quality Assurance in Autoclave processing) in the new Centre for Lightweight-Production-Technology in Stade. The concept is based on sensors obtaining quality-relevant process parameters and a real time process simulation able to predict multiple scenarios of different control strategies. The so called MASTERBOX is the centre piece of this new process control concept. It serves as interface between the sensors including the data acquisition, the process simulation and the real autoclave and takes decisions for the process control based on sensor data, simulation results and databases. This intelligent process control will be able to react to process and product deviations leading to an enormous reduction of scrap parts. Also as the process is controlled directly in function of the product’s quality-development, the process time can be reduced dramatically. Due to the fact that the quality-assurance is performed online during the process, the inline or offline part inspection could be reduced as well.

Control processes during selective long-term memory retrieval

In our daily life, we often need to selectively remember information related to the same retrieval cue in a consecutive manner (e.g., ingredients from a recipe). To investigate such selection processes during cued long-term memory (LTM) retrieval, we used a paradigm in which the retrieval demands were systematically varied from trial to trial and analyzed, by means of behavior and slow cortical EEG potentials (SCPs), the retrieval processes in the current trial depending on those of the previous trial. We varied whether the retrieval cue, the type of to-be-retrieved association (feature), or retrieval load was repeated or changed from trial to trial. The behavioral data revealed a benefit of feature repetition, probably due to trial-by-trial feature priming. SCPs further showed an effect of cue change with a mid-frontal maximum, suggesting increased control demands when the cue was repeated, as well as a parietal effect of retrieval-load change, indicating increased activation of posterior neural resources when focusing on a single association after all learned associations had been activated previously, compared to staying with single associations across trials. These effects suggest the existence of two distinct types of dynamic (trial-by-trial) control processes during LTM retrieval: (1) medial frontal processes that monitor or regulate interference within a set of activated associations, and (2) posterior processes regulating attention to LTM representations. The present study demonstrates that processes mediating selective LTM retrieval can be successfully studied by manipulating the history of processing demands in trial sequences.