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This paper is concerned with the identification of static nonlinear components in a complex interconnected system. These nonlinear components are treated nonparametrically, in the sense that no natural parameterization is assumed to be available. A unified framework based on linear fractional transformations for exploring these identification problems is developed. Two key assumptions are made: the linear components of the interconnection are known, and the inputs to all the nonlinear components are available. Under these assumptions, a novel identification algorithm is offered. This algorithm estimates the nonlinear components by minimizing a quadratic cost function. A critical component of this cost function is the inclusion of a dispersion function that captures the requirement that the estimated nonlinearities be static. It is shown that the estimated nonlinearities converge asymptotically to their "true" values under certain identifiability and persistence of excitation conditions. Computable tests for identifiability and sufficient conditions for persistence of excitation are offered. The results in this paper strongly suggest that the most tractable identification problems for nonlinear interconnected systems are those where the inputs to all the nonlinear blocks are measured. Index Terms--Identification, interconnected systems, nonlinear systems.

Interface motion and equilibrium were studied within the setting of a one-dimensional chain of harmonic oscillators. The interface demarcates regions of differing elastic stiffness and accretes through isothermal fluctuation theory, while the motion of each mass is governed by a simple force balance.

This paper details work in applying stereo vision for the enhancement of safety and productivity in the operation of a load--haul--dump (LHD) vehicle in underground mining. The primary goal of this portion of the research is to provide three--dimensional (3-D) models of the LHD's environment. Availability of these models facilitates performance of automated or teleoperated loading tasks and enhances safety through identification and location of humans in the path of the vehicle. Generation of an accurate 3-D model of the immediate surroundings of the LHD is accomplished through processing of stereo visual imagery. Stereo video is acquired using a pair of digital cameras mounted above the cab of the LHD. The video data are processed into a dense depth map plus confidence information. These depths and the stereo rig calibration data are then used to construct a 3-D surface model. We demonstrate useful models obtained under both well-illuminated and low-light conditions. Index Terms--Machine vision, mining, modeling, stereo.

A new technique for estimating postprandial glucose flux profiles without the use of glucose tracers is proposed. A sparse vector space representation is first found for the space of plausible glucose flux profiles using sparse encoding. A Lasso formulation is then used to estimate the glucose fluxes that combines (1) known patient model parameters; (2) the vector space of plausible glucose flux profiles; (3) continuous glucose monitor measurements taken during the meal; (4) amount of insulin injected; (5) amount of meal carbohydrates; and (6) an estimate of the initial conditions. Three glucose fluxes are then estimated, namely; glucose rate of appearance from the intestine; endogenous glucose production from the liver; insulin dependent glucose utilization; and other important state variables. The simulation results show that the technique is capable of estimating the glucose fluxes with high accuracy, even for complex meal scenarios. The experimental results indicate that the technique is capable of reproducing the triple tracer measurements for three T1DM undergoing the triple tracer protocol while estimating the missing measurements for a certain model parameter selection. [ABSTRACT FROM AUTHOR]

The present paper seeks to extract, analyze, and interpret the electrochemical impedance spectra of a LiFePO4-Li4Ti5O12 battery to supplement state-of-charge estimation. A particular challenge in determining the state-of-charge of a LiFePO4-Li4Ti5O12 cell is that the open-circuit voltage is flat over a large range of states of charge. Because the voltage in standard batteries is typically used to inform state-of-charge estimation, a different corrective factor needs to be determined for this cell chemistry. Instead of using the battery voltage, the present study uses the battery's dynamic response to assist state of charge estimation. The present work includes at least three novel contributions: 1) the electrochemical impedance of the LiFePO4-Li4Ti5O12 cell is shown to be strongly history dependent, 2) a novel system-identification technique is implemented to extract the EIS in-situ, and 3) a signature electrochemical impedance spectra attribute is identified that is a strong function of battery state of charge. [ABSTRACT FROM AUTHOR]

A two-dimensional Potts model is used to simulate the motion of a laser spot on a polycrystalline thin film. The model is used to demonstrate the feasibility of reshaping individual grain boundaries by either dragging grain boundaries or by repositioning triple junctions. [ABSTRACT FROM AUTHOR]

Phase-transformation electrodes have desirable characteristics for lithium-ion batteries. These electrodes have been shown to be abuse resistant, have extended cycle life, and are suitable for fast-charging applications. These new materials have significantly different lithium incorporation behaviors than the more-conventional solid-solution reaction electrodes. This paper explores the implications of phase-transformation physics within a multiparticle electrode that contains a distribution of particle sizes. Phase-transformation physics is such that lithium distributions within the electrode particle ensemble is cycle-path dependent. For example, after charging, any maldistribution of lithium between particles does not naturally redistribute uniformly between all particles, as is the case for solid-solution reaction electrodes. Such maldistribution greatly influences the observed electrochemical impedance spectra. The implications of history-dependent inter-particle lithium distributions is characterized with a mesoscopic model. The model shows how the impedance spectra of a phase-transformation electrode, at a prescribed state of charge, depends on the path history to achieve the state of charge. [ABSTRACT FROM AUTHOR]

A battery's electrochemical impedance response provides great insight about its internal electrochemical dynamics and state-ofhealth. This paper presents amethod to efficiently obtain wide-bandwidth electrochemical impedance spectra using two-level (binary) perturbation sequences. In this study, a physically based battery model's current-voltage response is captured with state-space models using system-identificationmethods. However, any single identified model is accurate only within a specific, limited frequency range. A stitching procedure combines several state-space models to establish a composite state-space model that is accurate over a wide frequency range. A validation study shows excellent agreement between the impedance of the stitched state-space model and the original physically based battery model. The approach is equally applicable to extracting electrochemical impedance spectra from simulation models as for experimental investigations. [ABSTRACT FROM AUTHOR]

Residential air conditioners (ACs), refrigeration units, and forced air heating loads are candidates for providing ancillary services to the grid. Motivated by the need for resources with high ramping rate capability, we investigate the ramping rate flexibility of such loads and show that a collection of residential heating, ventilation, and air conditioning (HVAC) loads can provide regulating reserve service with certain ramping rate bound that is a result of enforcing a no-short-cycling requirement. A load is called short-cycled if it is switched on and off quicker than a certain allowed time. We support our proposed bounds and theorems with illustrative simulations. [ABSTRACT FROM PUBLISHER]

Background: Treatment with oral carbohydrate prior to trauma and hemorrhage confers a survival benefit in small animal models. The impact of fed states on survival in traumatically injured humans is unknown. This work uses regulatory networks to examine the effect of carbohydrate pre-feeding on metabolic response to polytrauma and hemorrhagic shock in a clinically-relevant large animal model. Methods: Male Yorkshire pigs were fasted overnight (n = 64). Pre-fed animals (n = 32) received an oral bolus of Karo\textregistered\syrup before sedation. All animals underwent a standardized trauma, hemorrhage, and resuscitation protocol. Serum samples were obtained at set timepoints. Proton NMR was used to identify and quantify serum metabolites. Metabolic regulatory networks were constructed from metabolite concentrations and rates of change in those concentrations to identify controlled nodes and controlling nodes of the network. Results: Oral carbohydrate pre-treatment was not associated with survival benefit. Six metabolites were identified as controlled nodes in both groups: adenosine, cytidine, glycerol, hypoxanthine, lactate, and uridine. Distinct groups of controlling nodes were associated with controlled nodes; however, the composition of these groups depended on feeding status. Conclusions: A common metabolic output, typically associated with injury and hypoxia, results from trauma and hemorrhagic shock. However, this output is directed by different metabolic inputs depending upon the feeding status of the subject. Nodes of the network that are related to mortality can potentially be manipulated for therapeutic effect; however, these nodes differ depending upon feeding status. [ABSTRACT FROM AUTHOR]

We study output consensus in a network of interconnected non-identical positive real systems cascaded with a single integrator. Assuming undirected, diffusive interconnections, sufficient conditions are provided to ensure output consensus for two cases: (i) the individual systems are weakly strictly positive real systems cascaded with a single integrator, and (ii) the individual systems are positive real systems cascaded with a single integrator. We illustrate our results with the example of a load frequency control network of synchronous generators. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

It is widely accepted that thermostatically controlled loads (TCLs) can be used to provide regulation reserve to the grid. We first argue that the aggregate flexibility offered by a collection of TCLs can be succinctly modeled as a stochastic battery with dissipation. We next characterize the power limits and energy capacity of this battery model in terms of TCL parameters and random exogenous variables such as ambient temperature and user-specified set-points. We then describe a direct load control architecture for regulation service provision. Here, we use a priority-stack-based control framework to select which TCLs to control at any time. The control objective is for the aggregate power deviation from baseline to track an automatic generation control signal supplied by the system operator. Simulation studies suggest the practical promise of our methods. [ABSTRACT FROM PUBLISHER]

Run-to-run control is a major tool used in semiconductor manufacturing to keep the unit processes within the required manufacturing constraints. Typically, the difference or bias between the desired and actual result of processing a particular wafer is affected by not only the particular product being produced, but also the prior processing path. Each unique combination of effects is called a thread, and in threaded run-to-run control a separate exponentially weighted moving average controller is applied for each thread. One of the challenges of threaded control is the initialization of the bias estimate for a new thread. Automated initialization methods prevent the cost of manual initialization or utilizing a pilot run, but at the risk of producing outliers in the initialized runs. On the other hand, the manual initialization or using pilot runs incur an extra expense. In this paper, we study a new approach for initialization of the threads by combining the threaded and nonthreaded control strategies. This method avoids the cost associated with manual initialization methods and improves the efficiency of automated methods. Finally, the simulation results will demonstrate the efficiency of the proposed method in comparison with other techniques. [ABSTRACT FROM AUTHOR]

Semiconductor processing consists of many different unit operations that are combined in a sequence to create the finished product. Many of these unit operations utilize run to run control in order to keep the process within the required manufacturing constraints. Typically, the difference, or bias, between the desired and actual result of processing a particular wafer is affected by not only the particular product being produced, but the prior processing path. Each possible effect is called a context category, and the particular context items relevant for a wafer is called a thread. Because of frequent changes and updates in semiconductor products as well as a large number of product lines, run to run control must deal with a high-mix environment of products, and a large number of threads. Previously, several authors have discussed a method of describing the bias for a particular thread as a sum of context item biases and using a Kalman Filter to estimate these biases. However, two issues with previous implementations have been the observability of the state realization of the bias model, and the computational cost of the Kalman filter. In this paper, we introduce a model formulation that does not require model reduction or the specification of special reference threads, thus easily allowing new threads to be added and old threads removed. In addition, we describe how the problem structure allows the information form of the Kalman filter to be much more computationally efficient. Simulation results illustrate the proposed method. [ABSTRACT FROM AUTHOR]

This paper considers a state estimation problem where the nominal system is linear but the sensor has a time-varying gain component, giving rise to a bilinear output equation. This is a general sensor self-calibration problem and is of particular interest in the problem of estimating wafer thickness and etch rate during semiconductor manufacturing using reflectometry. We explore the use of a least squares estimate for this nonlinear estimation problem and give several approximate recursive algorithms for practical realization. Stability results for these algorithms are also given. Simulation results compare the new algorithms with the Extended Kalman Filter (EKF) and Iterated Kalman Filter (IKF). Index Terms - Calibration, estimation, nonlinear systems, observers.

Shrinking process windows in very large scale integration semiconductor manufacturing have already necessitated the development of control systems capable of addressing sub-lot-level variation. Within-wafer control is the next milestone in the evolution of advanced process control from lot-based and wafer-based control. In order to adequately comprehend and control within-wafer spatial variation, inline measurements must be performed at multiple locations across the wafer. At the same time, economic pressures prompt a reduction in metrology, for both capital and cycle-time reasons. This paper explores the use of modeling and minimum-variance prediction as a method to select the sites for measurement on each wafer. The models are developed using the standard statistical tools of principle component analysis and canonical correlation analysis. The proposed selection method is validated using real manufacturing data, and results indicate that it is possible to significantly reduce the number of measurements with little loss in the information obtained for the process control systems. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes a systematic method for developing model-based controllers for solid-oxide fuel cell (SOFC) systems. To enhance the system efficiency and to avoid possible damages, the system must be controlled within specific operating conditions, while satisfying a load requirement. Model predictive control (MPC) is a natural choice for control implementation. However, to implement MPC, a low-order model is needed that captures the dominant dynamic behavior over the operating range. A linear parameter varying (LPV) model structure is developed and applied to obtain a control-oriented dynamic model of the SOFC stack. This approach effectively reduces a detailed physical model to a form that is compatible with MPC. The LPV structure includes nonlinear scheduling functions that blend the dynamics of locally linear models to represent nonlinear dynamic behavior over large operating ranges. Alternative scheduling variables are evaluated, with cell current being shown to be an appropriate choice. Using the reduced-order model, an MPC controller is designed that can respond to the load requirement over a wide range of operation changes while maintaining input–output variables within specified constraints. To validate the approach, the LPV-based MPC controller is applied to the high-order physical model. [ABSTRACT FROM AUTHOR]

When only a single composition sensor is available for a multi-zone co-evaporation process, it can be difficult to determine the relative amount of material deposited in each zone. In this paper, a method of estimating the deposition-rate ratio between zones using small signal perturbation sequences is presented that exploits the exponential dependence of deposition rate on the temperature of the molten metal. A quality metric for the ratio estimate is presented, which can be easily calculated. Then, in order to determine the best perturbation sequence that meets all manufacturing constraints, a constrained optimization problem is described that is shown to be convex. An interesting feature of the solution is the importance of correlations between purturbation inputs. Experimental and simulation results are presented to validate the method. [ABSTRACT FROM AUTHOR]

Purpose – The purpose of this research is to develop closed-loop control of robotic welding processes. Design/methodology/approach – The approach being developed is the creation of three-dimensional models of the weld pool using stereo imagining. These models will be used in a model-based feedback control system. Fusion of more than one sensor type in the controller is used. Findings – Three-dimensional images can be produced from stereo images of GMAW-p weld pools. This requires coordinating the image capture with the arc pulse to allow observation of the pool. Research limitations/implications – This is a work in progress. The imaging is not being done in real time at this point in time. Future work will address this issue. Also, how the image information is to be used to make corrections within the controller is future work. Practical implications – Closing the loop on GMAW welding will allow robotic automation of welding to proceed to a much broader degree of application. Originality/value – This paper demonstrates that stereo imaging of out-of-position GMAW-p weld pools is possible and the useful information can be obtained from these images. It also provides insights into the analysis required within the model-based controller if one is to close the loop on the process specifically with regard to weld pool stability. [ABSTRACT FROM AUTHOR]

Thin-film etching and deposition using low-pressure plasma reactors is an integral part of the fabrication of very-largescale integrated (VLSI) circuits. Standard operation of plasma reactors uses an RF power source with constant average power to excite a plasma in the vacuum chamber. Recently, several researchers have shown empirically that operation of plasma reactors with a periodic power input has the promise to increase the flexibility of plasma processing, in the sense that a greater range of operating conditions is achievable. This paper presents a numerical analysis of a global model for an argon plasma with the aim of answering the following questions: First, can a periodic input achieve effective operating conditions that cannot be achieved using steady-state inputs? Second, if the answer to the first question is yes, what is the shape of the periodic input required to achieve a particular operating point? This technique was utilized to give answers to these questions in one particular case. It was shown that periodic operation of an argon plasma can create variations in the ratio of metastable argon density to ionized argon density beyond that achievable using constant power. In addition, strong evidence is given that arbitrarily shaped modulating waveforms have advantages over simple pulse width modulation. [ABSTRACT FROM AUTHOR]

A new method for registration in augmented reality (AR) was developed that simultaneously tracks the position, orientation, and motion of the user's head, as well as estimating the three-dimensional (3D) structure of the scene. The method fuses data from head-mounted cameras and head-mounted inertial sensors. Two extended Kalman filters (EKFs) are used: one estimates the motion of the user's head and the other estimates the 3D locations of points in the scene. A recursive loop is used between the two EKFs. The algorithm was tested using a combination of synthetic and real data, and in general was found to perform well. A further test showed that a system using two cameras performed much better than a system using a single camera, although improving the accuracy of the inertial sensors can partially compensate for the loss of one camera. The method is suitable for use in completely unstructured and unprepared environments. Unlike previous work in this area, this method requires no a priori knowledge about the scene, and can work in environments in which the objects of interest are close to the user. [ABSTRACT FROM AUTHOR]