Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

Innate-like control of human iNKT cell autoreactivity via the hypervariable CDR3beta loop

Invariant Natural Killer T cells (iNKT) are a versatile lymphocyte subset with important roles in both host defense and immunological tolerance. They express a highly conserved TCR which mediates recognition of the non-polymorphic, lipid-binding molecule CD1d. The structure of human iNKT TCRs is unique in that only one of the six complementarity determining region (CDR) loops, CDR3beta, is hypervariable. The role of this loop for iNKT biology has been controversial, and it is unresolved whether it contributes to iNKT TCR:CD1d binding or antigen selectivity. On the one hand, the CDR3beta loop is dispensable for iNKT TCR binding to CD1d molecules presenting the xenobiotic alpha-galactosylceramide ligand KRN7000, which elicits a strong functional response from mouse and human iNKT cells. However, a role for CDR3beta in the recognition of CD1d molecules presenting less potent ligands, such as self-lipids, is suggested by the clonal distribution of iNKT autoreactivity. We demonstrate that the human iNKT repertoire comprises subsets of greatly differing TCR affinity to CD1d, and that these differences relate to their autoreactive functions. These functionally different iNKT subsets segregate in their ability to bind CD1d-tetramers loaded with the partial agonist alpha-linked glycolipid antigen OCH and structurally different endogenous beta-glycosylceramides. Using surface plasmon resonance with recombinant iNKT TCRs and different ligand-CD1d complexes, we demonstrate that the CDR3beta sequence strongly impacts on the iNKT TCR affinity to CD1d, independent of the loaded CD1d ligand. Collectively our data reveal a crucial role for CDR3beta for the function of human iNKT cells by tuning the overall affinity of the iNKT TCR to CD1d. This mechanism is relatively independent of the bound CD1d ligand and thus forms the basis of an inherent, CDR3beta dependent functional hierarchy of human iNKT cells.

Closed-loop control of mean arterial blood pressure during surgery with alfentanil: clinical evaluation of a novel model-based predictive controller

BACKGROUND: In contrast to hypnosis, there is no surrogate parameter for analgesia in anesthetized patients. Opioids are titrated to suppress blood pressure response to noxious stimulation. The authors evaluated a novel model predictive controller for closed-loop administration of alfentanil using mean arterial blood pressure and predicted plasma alfentanil concentration (Cp Alf) as input parameters. METHODS: The authors studied 13 healthy patients scheduled to undergo minor lumbar and cervical spine surgery. After induction with propofol, alfentanil, and mivacurium and tracheal intubation, isoflurane was titrated to maintain the Bispectral Index at 55 (+/- 5), and the alfentanil administration was switched from manual to closed-loop control. The controller adjusted the alfentanil infusion rate to maintain the mean arterial blood pressure near the set-point (70 mmHg) while minimizing the Cp Alf toward the set-point plasma alfentanil concentration (Cp Alfref) (100 ng/ml). RESULTS: Two patients were excluded because of loss of arterial pressure signal and protocol violation. The alfentanil infusion was closed-loop controlled for a mean (SD) of 98.9 (1.5)% of presurgery time and 95.5 (4.3)% of surgery time. The mean (SD) end-tidal isoflurane concentrations were 0.78 (0.1) and 0.86 (0.1) vol%, the Cp Alf values were 122 (35) and 181 (58) ng/ml, and the Bispectral Index values were 51 (9) and 52 (4) before surgery and during surgery, respectively. The mean (SD) absolute deviations of mean arterial blood pressure were 7.6 (2.6) and 10.0 (4.2) mmHg (P = 0.262), and the median performance error, median absolute performance error, and wobble were 4.2 (6.2) and 8.8 (9.4)% (P = 0.002), 7.9 (3.8) and 11.8 (6.3)% (P = 0.129), and 14.5 (8.4) and 5.7 (1.2)% (P = 0.002) before surgery and during surgery, respectively. A post hoc simulation showed that the Cp Alfref decreased the predicted Cp Alf compared with mean arterial blood pressure alone. CONCLUSION: The authors' controller has a similar set-point precision as previous hypnotic controllers and provides adequate alfentanil dosing during surgery. It may help to standardize opioid dosing in research and may be a further step toward a multiple input-multiple output controller.

Control of muscle relaxation during anesthesia: a novel approach for clinical routine

During general anesthesia drugs are administered to provide hypnosis, ensure analgesia, and skeletal muscle relaxation. In this paper, the main components of a newly developed controller for skeletal muscle relaxation are described. Muscle relaxation is controlled by administration of neuromuscular blocking agents. The degree of relaxation is assessed by supramaximal train-of-four stimulation of the ulnar nerve and measuring the electromyogram response of the adductor pollicis muscle. For closed-loop control purposes, a physiologically based pharmacokinetic and pharmacodynamic model of the neuromuscular blocking agent mivacurium is derived. The model is used to design an observer-based state feedback controller. Contrary to similar automatic systems described in the literature this controller makes use of two different measures obtained in the train-of-four measurement to maintain the desired level of relaxation. The controller is validated in a clinical study comparing the performance of the controller to the performance of the anesthesiologist. As presented, the controller was able to maintain a preselected degree of muscle relaxation with excellent precision while minimizing drug administration. The controller performed at least equally well as the anesthesiologist.

Adaptive control of sinusoidal brushless DC motor actuators

Electrical Power Assisted Steering system (EPAS) will likely be used on future automotive power steering systems. The sinusoidal brushless DC (BLDC) motor has been identified as one of the most suitable actuators for the EPAS application. Motor characteristic variations, which can be indicated by variations of the motor parameters such as the coil resistance and the torque constant, directly impart inaccuracies in the control scheme based on the nominal values of parameters and thus the whole system performance suffers. The motor controller must address the time-varying motor characteristics problem and maintain the performance in its long service life. In this dissertation, four adaptive control algorithms for brushless DC (BLDC) motors are explored. The first algorithm engages a simplified inverse dq-coordinate dynamics controller and solves for the parameter errors with the q-axis current (iq) feedback from several past sampling steps. The controller parameter values are updated by slow integration of the parameter errors. Improvement such as dynamic approximation, speed approximation and Gram-Schmidt orthonormalization are discussed for better estimation performance. The second algorithm is proposed to use both the d-axis current (id) and the q-axis current (iq) feedback for parameter estimation since id always accompanies iq. Stochastic conditions for unbiased estimation are shown through Monte Carlo simulations. Study of the first two adaptive algorithms indicates that the parameter estimation performance can be achieved by using more history data. The Extended Kalman Filter (EKF), a representative recursive estimation algorithm, is then investigated for the BLDC motor application. Simulation results validated the superior estimation performance with the EKF. However, the computation complexity and stability may be barriers for practical implementation of the EKF. The fourth algorithm is a model reference adaptive control (MRAC) that utilizes the desired motor characteristics as a reference model. Its stability is guaranteed by Lyapunov’s direct method. Simulation shows superior performance in terms of the convergence speed and current tracking. These algorithms are compared in closed loop simulation with an EPAS model and a motor speed control application. The MRAC is identified as the most promising candidate controller because of its combination of superior performance and low computational complexity. A BLDC motor controller developed with the dq-coordinate model cannot be implemented without several supplemental functions such as the coordinate transformation and a DC-to-AC current encoding scheme. A quasi-physical BLDC motor model is developed to study the practical implementation issues of the dq-coordinate control strategy, such as the initialization and rotor angle transducer resolution. This model can also be beneficial during first stage development in automotive BLDC motor applications.

Experiences on using closed-loop control systems for smoke control

The main objective of ventilation systems in case of fire is the reduction of the possible consequences by achieving the best possible conditions for the evacuation of the users and the intervention of the emergency services. In the last years, the required quick response of the ventilation system, from normal to emergency mode, has been improved by the use of automatic and semi-automatic control systems, what reduces the response times through the support to the operators decision taking, and the use of pre-defined strategies. A further step consists on the use of closedloop algorithms, which takes into account not only the initial conditions but their development (air velocity, traffic situation, etc), optimizing the quality of the smoke control process

Modelling and Control of Stepper Motors for High Accuracy Positioning Systems Used in Radioactive Environments

Hybrid Stepper Motors are widely used in open-loop position applications. They are the choice of actuation for the collimators in the Large Hadron Collider, the largest particle accelerator at CERN. In this case the positioning requirements and the highly radioactive operating environment are unique. The latter forces both the use of long cables to connect the motors to the drives which act as transmission lines and also prevents the use of standard position sensors. However, reliable and precise operation of the collimators is critical for the machine, requiring the prevention of step loss in the motors and maintenance to be foreseen in case of mechanical degradation. In order to make the above possible, an approach is proposed for the application of an Extended Kalman Filter to a sensorless stepper motor drive, when the motor is separated from its drive by long cables. When the long cables and high frequency pulse width modulated control voltage signals are used together, the electrical signals difer greatly between the motor and drive-side of the cable. Since in the considered case only drive-side data is available, it is therefore necessary to estimate the motor-side signals. Modelling the entire cable and motor system in an Extended Kalman Filter is too computationally intensive for standard embedded real-time platforms. It is, in consequence, proposed to divide the problem into an Extended Kalman Filter, based only on the motor model, and separated motor-side signal estimators, the combination of which is less demanding computationally. The efectiveness of this approach is shown in simulation. Then its validity is experimentally demonstrated via implementation in a DSP based drive. A testbench to test its performance when driving an axis of a Large Hadron Collider collimator is presented along with the results achieved. It is shown that the proposed method is capable of achieving position and load torque estimates which allow step loss to be detected and mechanical degradation to be evaluated without the need for physical sensors. These estimation algorithms often require a precise model of the motor, but the standard electrical model used for hybrid stepper motors is limited when currents, which are high enough to produce saturation of the magnetic circuit, are present. New model extensions are proposed in order to have a more precise model of the motor independently of the current level, whilst maintaining a low computational cost. It is shown that a significant improvement in the model It is achieved with these extensions, and their computational performance is compared to study the cost of model improvement versus computation cost. The applicability of the proposed model extensions is demonstrated via their use in an Extended Kalman Filter running in real-time for closed-loop current control and mechanical state estimation. An additional problem arises from the use of stepper motors. The mechanics of the collimators can wear due to the abrupt motion and torque profiles that are applied by them when used in the standard way, i.e. stepping in open-loop. Closed-loop position control, more specifically Field Oriented Control, would allow smoother profiles, more respectful to the mechanics, to be applied but requires position feedback. As mentioned already, the use of sensors in radioactive environments is very limited for reliability reasons. Sensorless control is a known option but when the speed is very low or zero, as is the case most of the time for the motors used in the LHC collimator, the loss of observability prevents its use. In order to allow the use of position sensors without reducing the long term reliability of the whole system, the possibility to switch from closed to open loop is proposed and validated, allowing the use of closed-loop control when the position sensors function correctly and open-loop when there is a sensor failure. A different approach to deal with the switched drive working with long cables is also presented. Switched mode stepper motor drives tend to have poor performance or even fail completely when the motor is fed through a long cable due to the high oscillations in the drive-side current. The design of a stepper motor output fillter which solves this problem is thus proposed. A two stage filter, one devoted to dealing with the diferential mode and the other with the common mode, is designed and validated experimentally. With this ?lter the drive performance is greatly improved, achieving a positioning repeatability even better than with the drive working without a long cable, the radiated emissions are reduced and the overvoltages at the motor terminals are eliminated.

Personalized rule-based closed-loop control algorithm for type 1 diabetes

Type 1 diabetes-mellitus implies a life-threatening absolute insulin deficiency. Artificial pancreas (CGM sensor, insulin pump and control algorithm) is promising to outperform current open-loop therapies.

On the role of global flow instability analysis in closed loop flow control

Control of linear flow instabilities has been demonstrated to be an effective theoretical flow control methodology, capable of modifying transitional flows on canonical geometries such as the plane channel and the flat-plate boundary layer. Extending the well-developed theoretical flow control techniques to flows over or through complex geometries requires addressing the issue of efficient capturing of the leading members of the global eigenspectrum pertinent to such flows. The present contribution describes state-of-the-art modal global instability analysis methodologies recently developed in our group, based on matrix formation and time-stepping, respectively. The relative performance of these algorithms is assessed on the recovery of BiGlobal and TriGlobal eigenspectra in the spanwise periodic and the cubic lid-driven cavity, respectively; the adjoint eigenspectrum in the latter flow is recovered for the first time. For three-dimensional flows without any homogeneous spatial direction, the time-stepping methodology was found to outperform the matrix-forming approach and permit recovering the leading TriGlobal eigenmodes in an three-dimensional open cavity of aspect ratio L : D : W = 5 : 1 : 1; theoretical flow control of this configuration is underway.

On the role of global flow instability analysis in closed loop flow control

Control of linear flow instabilities has been demonstrated to be an effective theoretical flow control methodology, capable of modifying transitional flow on canonical geometries such as the plane channel and the flat-plate boundary layer.

Optimal Control Using Feedback Linearization for a Generalized T-S Model

In this paper, a fuzzy feedback linearization is used to control nonlinear systems described by Takagi-Suengo (T-S) fuzzy systems. In this work, an optimal controller is designed using the linear quadratic regulator (LQR). The well known weighting parameters approach is applied to optimize local and global approximation and modelling capability of T-S fuzzy model to improve the choice of the performance index and minimize it. The approach used here can be considered as a generalized version of T-S method. Simulation results indicate the potential, simplicity and generality of the estimation method and the robustness of the proposed optimal LQR algorithm.

AtGRP7, a nuclear RNA-binding protein as a component of a circadian-regulated negative feedback loop in Arabidopsis thaliana

The endogenous clock that drives circadian rhythms is thought to communicate temporal information within the cell via cycling downstream transcripts. A transcript encoding a glycine-rich RNA-binding protein, Atgrp7, in Arabidopsis thaliana undergoes circadian oscillations with peak levels in the evening. The AtGRP7 protein also cycles with a time delay so that Atgrp7 transcript levels decline when the AtGRP7 protein accumulates to high levels. After AtGRP7 protein concentration has fallen to trough levels, Atgrp7 transcript starts to reaccumulate. Overexpression of AtGRP7 in transgenic Arabidopsis plants severely depresses cycling of the endogenous Atgrp7 transcript. These data establish both transcript and protein as components of a negative feedback circuit capable of generating a stable oscillation. AtGRP7 overexpression also depresses the oscillation of the circadian-regulated transcript encoding the related RNA-binding protein AtGRP8 but does not affect the oscillation of transcripts such as cab or catalase mRNAs. We propose that the AtGRP7 autoregulatory loop represents a “slave” oscillator in Arabidopsis that receives temporal information from a central “master” oscillator, conserves the rhythmicity by negative feedback, and transduces it to the output pathway by regulating a subset of clock-controlled transcripts.

Desert dust suppressing precipitation: A possible desertification feedback loop

The effect of desert dust on cloud properties and precipitation has so far been studied solely by using theoretical models, which predict that rainfall would be enhanced. Here we present observations showing the contrary; the effect of dust on cloud properties is to inhibit precipitation. Using satellite and aircraft observations we show that clouds forming within desert dust contain small droplets and produce little precipitation by drop coalescence. Measurement of the size distribution and the chemical analysis of individual Saharan dust particles collected in such a dust storm suggest a possible mechanism for the diminished rainfall. The detrimental impact of dust on rainfall is smaller than that caused by smoke from biomass burning or anthropogenic air pollution, but the large abundance of desert dust in the atmosphere renders it important. The reduction of precipitation from clouds affected by desert dust can cause drier soil, which in turn raises more dust, thus providing a possible feedback loop to further decrease precipitation. Furthermore, anthropogenic changes of land use exposing the topsoil can initiate such a desertification feedback process.

Timing of metamorphosis and the onset of the negative feedback loop between the thyroid gland and the pituitary is controlled by type II iodothyronine deiodinase in Xenopus laevis

Two important features of amphibian metamorphosis are the sequential response of tissues to different concentrations of thyroid hormone (TH) and the development of the negative feedback loop between the pituitary and the thyroid gland that regulates TH synthesis by the thyroid gland. At the climax of metamorphosis in Xenopus laevis (when the TH level is highest), the ratio of the circulating precursor thyroxine (T4) to the active form 3,5,3′-triiodothyronine (T3) in the blood is many times higher than it is in tissues. This difference is because of the conversion of T4 to T3 in target cells of the tadpole catalyzed by the enzyme type II iodothyronine deiodinase (D2) and the local effect (cell autonomy) of this activity. Limb buds and tails express D2 early and late in metamorphosis, respectively, correlating with the time that these organs undergo TH-induced change. T3 is required to complete metamorphosis because the peak concentration of T4 that is reached at metamorphic climax cannot induce the final morphological changes. At the climax of metamorphosis, D2 expression is activated specifically in the anterior pituitary cells that express the genes for thyroid-stimulating hormone but not in the cells that express proopiomelanocortin. Physiological concentrations of T3 but not T4 can suppress thyrotropin subunit β gene expression. The timing and the remarkable specificity of D2 expression in the thyrotrophs of the anterior pituitary coupled with the requirement for locally synthesized T3 strongly support a role for D2 in the onset of the negative feedback loop at the climax of metamorphosis.