DEVS representation of dynamical systems: event-based intelligentcontrol

It is shown how systems can be advantageously represented as discrete event models by using DEVS (discrete event system specification), set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based control paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems     

Control-Relevant Demand Forecasting for Tactical Decision-Making in Semiconductor Manufacturing Supply Chain Management

Forecasting highly uncertain demand signals is an important component for successfully managing inventory in semiconductor supply chains. We present a control-relevant approach to the problem that tailors a forecasting model to its end-use purpose, which is to provide forecast signals for a tactical inventory management policy based on model predictive control (MPC). The success of the method hinges on a control-relevant prefiltering operation applied to demand estimation data that emphasizes a goodness-of-fit in regions of time and frequency most important for achieving desired levels of closed-loop performance. A multiobjective formulation is presented that allows the supply-chain planner to generate demand forecasts that minimize inventory deviation, starts change variance, or their weighted combination when incorporated in an MPC decision policy. The benefits obtained from this procedure are demonstrated on a case study drawn from the final stage of a semiconductor manufacturing supply chain.      

Modeling, analysis, simulation, scheduling, and control ofsemiconductor manufacturing systems: A Petri net approach

This paper presents a Petri net approach to modeling, analysis, simulation, scheduling, and control of semiconductor manufacturing systems. These systems can be characterized as discrete event systems that exhibit sequential, concurrent, and conflicting relations among the events and operations. Their evolution is dynamic over time. The system complexity is tremendous owing to the complex semiconductor manufacturing processes and test procedures. A formal approach such as Petri nets enables one to describe such complex discrete event systems precisely and thus allows one to perform both qualitative and quantitative analysis, scheduling and discrete-event control of them. This paper also serves as a tutorial paper. It briefly reviews applications of Petri nets in semiconductor manufacturing automation. It then introduces definitions and concepts of Petri nets. It proceeds with a discussion of basic Petri net modules in system modeling, a modeling method and a practical system's modeling example. Next, the paper presents their properties and their implications in manufacturing systems, as well as their analysis methods. Timed Petri nets are introduced for system simulation, performance evaluation, and scheduling purposes. An application-oriented case study is presented. Finally, the paper concludes with the active research areas in applying Petri nets to design of semiconductor manufacturing systems     

Statistical Wavelet Subband Characterization Based on Generalized Gamma Density and Its Application in Texture Retrieval

The modeling of image data by a general parametric family of statistical distributions plays an important role in many applications. In this paper, we propose to adopt the three-parameter generalized Gamma density $({rm G}Gamma{rm D})$ for modeling wavelet detail subband histograms and for texture image retrieval. The advantage of ${rm G}Gamma{rm D}$ over the existing generalized Gaussian density (GGD) is that it provides more flexibility to control the shape of model which is critical for practical histogram-based applications. To measure the discrepancy between ${rm G}Gamma{rm Ds}$, we use the symmetrized Kullback-Leibler distance (SKLD) and derive a closed form for the SKLD between ${rm G}Gamma{rm Ds}$. Such a distance can be computed directly and effectively via the model parameters, making our proposed scheme particularly suitable for image retrieval systems with large image database. Experimental results on the well-known databases reveal the superior performance of our proposed method compared with the current existing approaches.      

Extensions and performance/robustness tradeoffs of the EWMArun-to-run controller by using the internal model control structure

We consider the run-to-run (RtR) correction of input recipes for semiconductor manufacturing processes using measurement information from previous runs. A RtR control algorithm that has been experimentally tested by industry and academia is the EWMA (exponentially weighted moving average) RtR controller. In this paper we provide extensions to this algorithm to address some of its drawbacks and also provide a rigorous theoretical analysis of its properties based on discrete control theory. By formulating the RtR control problem in the internal model control (IMC) structure used in feedback process control, we are able to extend the algorithm to completely eliminate offsets due to unmodeled process drifts, which is a common problem in semiconductor manufacturing. We also develop conditions for robustness with respect to modeling error and measurement delays. Tradeoffs between robustness guarantees and fast RtR response as well as handling of measurement noise are developed and presented in the form of plots that can be used for tuning the parameters of the RtR-IMC controller to accomplish the objectives set by the process engineer. The results are illustrated through several simulations including control of film deposition uniformity in an epitaxial reactor and tungsten deposition rate in a tungsten CVD reactor     

Modeling and simulation of an electronic component manufacturingsystem using hybrid Petri nets

Modelling and analysis for the design and operation of manufacturing systems is a vital need. For semiconductor manufacturing systems, which are large scale systems, discrete Petri nets do not constitute an adequate tool for modeling and analysis. In fact, use of discrete Petri nets is confronted with tile state explosion and the high cost of simulation. In this paper, hybrid Petri nets are presented as powerful tools for modeling and simulation of semiconductor manufacturing systems. This model has been used for modeling and simulation of a real life electronic components manufacturing system. It provides an accurate and first simulation of this system     

SPICE Optimization of Organic FET Models Using Charge Transport Elements

We report on a modeling technique that uses charge transport equations to calculate channel current in organic field effect transistors (OFETs) by numerical solution in the SPICE simulation program. SPICE is also used to optimize the model and achieve a fit to measured characteristics within 5% error. The overall modeling technique is a bridge between physical models of charge transport and a SPICE model useful in circuit simulation without requiring a closed-form drain-current equation. The automatic optimization of the simulation to measured curves will also allow, in the future, the empirical weighing of various charge transport effects in search of physical device operation, given sufficient empirical data. This modeling technique was applied to the measured characteristics of an OFET using pentacene in which the mobility was dependent on the voltage in the channel. The accuracy of the fit was better than 5% for $hbox{40} hbox{V} ≫ V_{rm DS} ≫ hbox{7} hbox{V}$ and better than 20% for $V_{rm DS} ≪ hbox{7} hbox{V}$. Simulation was completed within 3 min for this optimization on a modern personal computer.      

Precision Threshold Current Measurement for Semiconductor Lasers Based on Relaxation Oscillation Frequency

The soft turn-on of semiconductor lasers leads to uncertainty in defining and measuring the laser threshold injection current, ${I}_{rm th}$. Previously, practical calculation algorithms have been developed to achieve high-accuracy measurement of a clearly defined and reproducible quantity which is called ${I}_{rm th}$. We demonstrate a new and higher accuracy measurement of ${I}_{rm th}$ using the dependency of the relaxation oscillation frequency on injection current, as compared to the existing standardized approaches. Further, if it is accepted that relaxation oscillations do not occur below laser threshold, this may be regarded as a more fundamentally based definition and measurement method to determine the laser threshold injection current in a semiconductor laser. The method may also be applicable to other types of lasers.      

Performance evaluation of a MPPT controller with model predictive control for a photovoltaic system

ABSTRACT

Efficiency has been a major factor in the growth of photovoltaic (PV) systems. Different control techniques have been explored to extract maximum power from PV systems under varying environmental conditions. This paper evaluates the performance of a new improved control technique known as model predictive control (MPC) in power extraction from PV systems. Exploiting the ability of MPC to predict future state of controlled variables, MPC has been implemented for tacking of maximum power point (MPP) of a PV system. Application of MPC for maximum power point tracking (MPPT) has been found to result into faster tracking of MPP under continuously varying atmospheric conditions providing an efficient system. It helps in reducing unwanted oscillations with an increase in tracking speed. A detailed step by step process of designing a model predictive controller has been discussed. Here, MPC has been applied in conjunction with conventional perturb and observe (P&O) method for controlling the dc-dc boost converter switching, harvesting maximum power from a PV array. The results of MPC controller has been compared with two widely used conventional methods of MPPT, viz. incremental conductance method and P&O method. The MPC controller scheme has been designed, implemented and tested in MATLAB/Simulink environment and has also been experimentally validated using a laboratory prototype of a PV system.     

Optimal automatic control of multistage production processes

Today's high-tech industries produce complicated products involving many processing steps. The usual approach of modeling and controlling each of these steps in isolation is re-evaluated. This work develops a data model of synchronized observations collected from several stages of a multistage manufacturing process, and proposes an across-stage automatic control scheme for adjusting nonstationary process drifts. The proposed controller applies dynamic programming tools to optimize multiple goals specified for individual process stages and possible mismatch between stages. Several examples and simulation studies demonstrate that the proposed method is a valuable tool for improving semiconductor manufacturing quality.     

Adaptive Sliding-Mode Neuro-Fuzzy Control of the Two-Mass Induction Motor Drive Without Mechanical Sensors

In this paper, the concept of a model reference adaptive control of a sensorless induction motor (IM) drive with elastic joint is proposed. An adaptive speed controller uses fuzzy neural network equipped with an additional option for online tuning of its chosen parameters. A sliding-mode neuro-fuzzy controller is used as the speed controller, whose connective weights are trained online according to the error between the estimated motor speed and the speed given by the reference model. The speed of the vector-controlled IM is estimated using the $hbox{MRAS}^{rm CC}$ rotor speed and a flux estimator. Such a control structure is proposed to damp torsional vibrations in a two-mass system in an effective way. It is shown that torsional oscillations can be successfully suppressed in the proposed control structure, using only one basic feedback from the motor speed given by the proposed speed estimator. Simulation results are verified by experimental tests over a wide range of motor speed and drive parameter changes.      

On the stability of MIMO EWMA run-to-run controllers with metrology delay

As production requirements in semiconductor manufacturing continue to escalate, it is rarely possible to perform quality measurements on a product before subsequent process operations are performed. This delay between manufacturing and metrology coupled with inaccurate process models can lead to closed-loop instabilities. This paper investigates the effect of metrology delay on the closed-loop stability of a multiple input-multiple output exponentially weighted moving average run-to-run controller. The generalized Routh-Hurwitz stability criteria are used to derive the necessary and sufficient conditions for stability. A sufficient condition for stability is then derived for systems with any length of metrology delay. This condition states that if all of the eigenvalues of a model-mismatch matrix fall inside a circle with unit radius and centered at {1,0} on the complex plane, then the closed-loop system is stable.     

System of Systems Approach to Formal Modeling of CPS for Simulation‐Based Analysis

This paper presents a system‐of‐systems (SoS) approach to the formal modeling of a cyber‐physical system (CPS) for simulation‐based analysis. The approach is based on a convergence technology for modeling and simulation of a highly complex system in which SoS modeling methodology, hybrid systems modeling theory, and simulation interoperation technology are merged. The methodology maps each constituent system of a CPS to a disparate model of either continuous or discrete types. The theory employs two formalisms for modeling of the two model types with formal specification of interfaces between them. Finally, the technology adapts a simulation bus called DEVS BUS whose protocol synchronizes time and exchange messages between subsystems simulation. Benefits of the approach include reusability of simulation models and environments, and simulation‐based analysis of subsystems of a CPS in an inter‐relational manner.     

Design of a 770-MHz, 70-mW, 8-bit Subranging ADC Using Reference Voltage Precharging Architecture

This paper describes a high-speed, low-power CMOS subranging analog-to-digital converter (ADC). A reference voltage precharging architecture and the introduction of a comparator with a built-in threshold voltage in the fine ADC are proposed to reduce the settling time of the reference voltage. A T/H circuit with a body-bias control circuit is employed to reduce distortion at a high sampling rate. Moreover, a $V_{rm TH}$ generator using a replica of the original comparator is also proposed to compensate for $V_{rm TH}$ deviation due to the process variations. A test chip was fabricated using 90-nm CMOS technology, and showed a high-sampling rate of 770 MS/s and a low-power consumption of 70 mW.      

High-Performance Metal/High-$k$ n- and p-MOSFETs With Top-Cut Dual Stress Liners Using Gate-Last Damascene Process on (100) Substrates

Newly proposed mobility-booster technologies are demonstrated for metal/high- $k$ gate-stack n- and pMOSFETs. The process combination of top-cut SiN dual stress liners and damascene gates remarkably enhances local channel stress particularly for shorter gate lengths in comparison with a conventional gate-first process. Dummy gate removal in the damascene gate process induces high channel stress, because of the elimination of reaction force from the dummy gate. PFETs with top-cut compressive stress liners and embedded SiGe source/drains are performed by using atomic layer deposition TiN/$ hbox{HfO}_{2}$ gate stacks with $T_{rm inv} = hbox{1.4} hbox{nm}$ on (100) substrates. On the other hand, nFETs with top-cut tensile stress liners are obtained by using $hbox{HfSi}_{x}/hbox{HfO}_{2}$ gate stacks with $T_{rm inv} = hbox{1.4} hbox{nm}$. High-performance n- and pFETs are achieved with $I_{rm on} = hbox{1300}$ and 1000 $muhbox{A}/muhbox{m} hbox{at} I_{rm off} = hbox{100} hbox{nA}/mu hbox{m}$, $V_{rm dd} = hbox{1.0} hbox{V}$, and a gate length of 40 nm, respectively.      

Conversion of Direct to Indirect Bandgap and Optical Response of B Substituted InN for Novel Optical Devices Applications

Optical properties of B$_{rm x}$In$_{1 - {rm x}}$N are calculated as a function of the varying concentration of Boron and Indium. Indium is gradually replaced by Boron and optical properties of the resulting materials are studied. The fractional concentration of Boron is increased gradually from ${rm x} = 0$ to ${rm x} = 1$ in steps of 0.25. The bandgap increases with the increasing Boron concentration, from 0.95 eV for pure InN to 5.6 eV for BN. A unique behavior of BN in zinc-blend phase is observed, that is, it shifts from indirect to direct bandgap semiconductor by the substitution of In on B sites. This behavior can be used to make novel and advanced optical devices. Frequency dependent reflectivity, absorption coefficient, and optical conductivity of B$_{rm x}$In$_{1 - {rm x}}$N are calculated and found to be the constituent's concentration dependent. The region of reflectivity, absorption coefficient and optical conductivity shifts from lower frequency into the higher frequency as the material goes from pure InN to pure BN.      

A 27 GHz, 14 dBm CMOS Power Amplifier Using 0.18 $mu {rm m}$ Common-Source MOSFETs

A Ka-band three-stage CMOS power amplifier was designed and fabricated using 0.18 $mu {rm m}$ gate-length common-source transistors. For low loss and accurate matching networks for the amplifier, a substrate-shielded microstrip-line was used with good modeling accuracy up to 40 GHz. The measured insertion loss was 0.5 dB/mm at 25 GHz. The three-stage amplifier achieved a 14.5 dB small-signal gain, 14 dBm output power, and 13.2% power-added-efficiency at 27 GHz in a compact chip area of 0.84 ${rm mm}^{2}$. The measured gain was the highest for Ka-band power amplifiers using common-source transistors. These results were achieved at a voltage compatible with deep sub-micrometer CMOS technology.      

Simultaneous control of multiple measures of nonuniformity usingsite models and monitor wafer control

Present day semiconductor manufacturing processes are subject to tight specifications. High yields with tight process specifications require drive to target process control. As the size of the wafer in the semiconductor industry increases, nonuniformity across the wafer becomes a crucial yield limiting issue. Modeling nonuniformity in terms of the equipment settings permits calculation of recipes required to achieve the desired nonuniformity. However, models for single measures of nonuniformity, such as standard deviation, or range, do not capture all aspects of the nonuniformity and often do not model well in terms of the equipment settings. This paper describes the use of spatial models to simultaneously quantify multiple measures of nonuniformity, and a controller to keep the nonuniformities within specifications, Use of spatial models in conjunction with a monitor wafer controller (MWC) enables the simultaneous control of multiple nonuniformity measures. The paper presents the results of applying the MWC with spatial models to a plasma enhanced TEOS (PETEOS) deposition process on an Applied Materials Precision 5000 (AMT5000). The controller has been keeping the PETEOS process within specifications for over two years     

RFID-Based Smart Freezer

This paper presents a novel radio-frequency identification (RFID)-based smart freezer using a new inventory-management scheme for extremely low temperature environments. The proposed solution utilizes backpressure inventory control, systematic selection of antenna configuration, and antenna power control. The proposed distributed-inventory-control (DIC) scheme dictates the amount of items transferred through the supply chain. When a high item visibility is ensured, the control scheme maintains the desired level of inventory at each supply-chain echelon. The performance of the DIC scheme is guaranteed using a Lyapunov-based analysis. The proposed RFID antenna-configuration design methodology coupled with locally asymptotically stable distributed power control ensures a 99% read rate of items while minimizing the required number of RFID antennas in the confined cold chain environments with non-RF-friendly materials. The proposed RFID-based smart-freezer performance is verified through simulations of supply chain and experiments on an industrial freezer testbed operating at $-100 ^{circ}hbox{F}$.