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Automation Science and Engineering, IEEE Transactions on

Issue 3 • Date July 2012

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  • Table of contents

    Page(s): C1
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  • IEEE Transactions on Automation Science and Engineering publication information

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  • Editorial: A Secret to Advancing Research and Increasing Citations to Your Papers

    Page(s): 457
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  • Theory and Performance Evaluation of Group Coding of RFID Tags

    Page(s): 458 - 466
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1431 KB) |  | HTML iconHTML  

    Radio frequency identification (RFID) is an automatic identification technology which identifies physical objects individually according to their unique identifiers (ID) recorded in each RFID tag. Many business processes require the integrity verification of a group of objects in addition to individual object identification. This paper proposes “group coding” of RFID tags with which we can verify the integrity of groups of objects by writing parity check data to the memory of RFID tags. It was revealed by simulations and experiments that we could determine the number of missing RFID tags up to 10 with accuracy over 99% when we write 96 bits of the checksum data to 20 RFID tags. The whole duration of group decoding measured in the experiment was approximately 2 to 3 s. The time to compute group encoding and decoding was in the order of several milliseconds and thus negligible. The RFID inventory accounts for the majority of the duration. Note to Practitioners-Current RFID features fast identification of many physical objects. However, the integrity check of a group of objects is usually done by looking up a packaging list or a shipment list in EDI, which requires a network connection. Our proposed “group coding” of RFID tags can perform the group integrity check without a network connection. In addition, when the integrity of the group is infringed, the group coding can determine the number of RFID tags missing from the group. These features of group coding can reduce the cost of looking up shipment lists and locate missing RFID tags. The accuracy of the determination is controlled by adjusting the size of data written in each RFID tag. Adopters of group coding can select the optimal performance of group coding from the requirements of the accuracy and constraints like memory consumption of RFID tags. View full abstract»

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  • Open Software Platform for Robotic Services

    Page(s): 467 - 481
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1762 KB) |  | HTML iconHTML  

    In this paper, an efficient development environment for vertical integration of many tasks involved with robot programming, called Open software Platform for Robotic Services (OPRoS), is presented. It covers from the control of hardware (HW) devices to the execution of complicated application programs. Based on general software (SW) architecture, standardized components with design patterns, frameworks, and servers are offered for developing robot SW applications easily and efficiently. Specially, an easy and one-stop Integrated Development Environment (IDE) and simulation tools are provided to make the management and debugging easier, and to check performance in advance. For an all-level development environment, the IDE of OPRoS supports development from low-level device controls to high-level contents composition, and hence, many programs ranging from HW device programs to complicated applications can be developed and integrated in a single development environment. Additionally, OPRoS makes all modules and components undergo the proper evaluation and test, which avoids potential errors due to incomplete coding. As a comprehensive platform for robot SW applications, OPRoS provides convenient environments for all development steps from editing through verification to execution. View full abstract»

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  • A Concurrent Approach to Reducing Environmental Impact of Product Development at the System Design Stage

    Page(s): 482 - 495
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    This paper presents a computational framework for reducing environmental impact of product development in consideration of product design, manufacturing, and the supply chain concurrently. This framework incorporates a number of factors that ecologically influence the product lifecycle activities into product architecture design. They allow a systematic variation of manufacturing bill of materials. CAD-based functions are developed to ensure that the variation results satisfy product functional requirements and are interference-free during assembly. A cradle-to-gate lifecycle assessment is conducted on the bill of materials. Optimization schemes are integrated with the variation process to search for optimal results. This work realizes sustainable product development by offering a tool of ecological decision making in the system design stage. View full abstract»

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  • Energy Savings in Metropolitan Railway Substations Through Regenerative Energy Recovery and Optimal Design of ATO Speed Profiles

    Page(s): 496 - 504
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1024 KB) |  | HTML iconHTML  

    Traffic operation has a significant impact on energy consumption in metro lines and thus it is important to analyze strategies to minimize it. In lines equipped with Automatic Train Operation systems (ATO), traffic regulation system selects one ATO speed profile on line among a preprogrammed set of optimized speed profiles. Previous works only minimize the energy demanded by the train in pantograph without considering energy savings measured at substations due to regenerative energy in detail. The main objective of this work is to design optimal ATO speed profiles of metro trains taking into account the energy recovered from regenerative brake in order to minimize the net energy at substations. A model of a train with an on-board energy storage device as well as a network model for estimating the energy recovered by the train is presented. Different scenarios are analyzed to assess the achievable energy savings due to possible investments such as installing power inverters or storage devices and energy savings due to the optimal design of ATO speed profiles are estimated. A real line of the Madrid Underground has been considered obtaining comparative results to facilitate an evaluation of the most advantageous scenario and possible investment. A future application would be the optimal design of driving for the newest train signaling system communications-based train control (CBTC). The CBTC improves train operation and control, due to continuous communication with each train. However, its features have not been taken full advantage yet to reduce the energy consumption. The proposed method could be applied to design and execute in real time the most energy-efficient driving according to the traffic and electrical situation of the line. View full abstract»

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  • Feasibility of Intelligent Monitoring of Construction Workers for Carbon Monoxide Poisoning

    Page(s): 505 - 515
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (629 KB) |  | HTML iconHTML  

    This paper presents a feasibility study of a wearable computing system to protect construction workers from carbon monoxide poisoning. A pulse oximetry sensor has been integrated into a typical construction helmet to allow continuous and noninvasive monitoring of workers' blood gas saturation levels. To show the feasibility of monitoring for carbon monoxide poisoning without subjecting users to dangerous conditions, a prototype for monitoring blood O2 saturation was constructed and tested during a user study involving typical construction tasks to determine its reliability while undergoing motion. As monitoring for O2 and CO simply differ in the number of wavelengths of light employed, if monitoring O2 is feasible, then monitoring for CO will be feasible as well. Using this equivalency, the results of this initial study show that integrating an oximeter into a construction helmet will warn the user of impending carbon monoxide poisoning with a probability greater than 99%. Note to Practitioners-This work addresses the issue of carbon monoxide exposure on construction sites. A noninvasive blood oxygen saturation sensor, called a pulse oximeter, was integrated into a typical construction helmet to investigate the reliability of continuous monitoring of construction workers. The pulse oximetry sensing technology was shown to be reliable under typical construction tasks such that a worker would be alerted of impending carbon monoxide poisoning before becoming impaired. Additional work is required with more complex tasks as well as isolating the sensor from motion artifacts generated by head movement. View full abstract»

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  • Coalition-Based Approach to Task Allocation of Multiple Robots With Resource Constraints

    Page(s): 516 - 528
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    We propose a coalition-based approach to solve the task allocation problem of multiple robots with resource constraints. The resources required by task execution characterize the robots and tasks. Robots must form coalitions to accomplish the assigned tasks because individually, each robot may not complete the task independently due to resource limitation. We consider both online and offline assignment manners of the task allocation problem. For online assignment, a sequential coalition method is proposed to select efficiently the suitable robots to form coalitions for the assigned task. For offline assignment, a holistic coalition method is proposed for global optimization of all the assigned tasks. Both sequential and holistic coalition methods are compared with existing approaches. Numerous simulations and experiments performed on heterogeneous multiple mobile robots demonstrate the effectiveness of the proposed coalition-based task allocation methods. Note to Practitioners - Task allocation into a group of heterogeneous mobile robots for implementing multiple tasks is a challenge in multirobot applications. To find and organize the most suitable coalition for each task, we need to well organize the coalition for each task to maximize the robot group utility and optimize the task allocation solution. The sequential and holistic coalition methods presented in this paper provide both online and offline solutions for optimal multirobot task allocation. The advantage of the sequential coalition method lies in its efficiency in selecting best-fitted robots during coalition forming, and the advantage of the holistic coalition method lies in its effectiveness in finding the global optimal solution for all tasks. We illustrate the effectiveness of the proposed methods through numerous case studies with comparisons in this paper. View full abstract»

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  • Cyclic Task Scheduling for Multifunction Radar

    Page(s): 529 - 537
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    A framework and method is presented for developing a cyclic task schedule in a multifunction radar. Rather than assuming the task dwell time to be a fixed value when building the schedule, the task dwell time is modeled as a fuzzy set to allow for increased radar schedule flexibility. An optimization model is developed for the scheduling problem and a heuristic method for its solution is proposed. The heuristic method exploits the fuzzy set model in order to intelligently adjust the task dwell times. This adjustment allows for accommodation of more tasks on the radar timeline, thereby resulting in fewer dropped tasks. Computational results are presented to assess the behavior of the proposed scheduling method. View full abstract»

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  • A Compliant Parallel XY Micromotion Stage With Complete Kinematic Decoupling

    Page(s): 538 - 553
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    This paper presents a novel compliant parallel XY micromotion stage driven by piezoelectric actuators (PZT). With the purpose to obtain complete kinematic decoupling and good stiffness performance, the stage is designed using a symmetric 4-PP structure in which double four-bar flexure is chosen as the prismatic joint. Matrix method is employed to establish the compliance model of the mechanism. Based on the model, dynamic analysis is investigated after static analysis is carried out. The dimensions of the mechanism are optimized using the particle swarm optimization (PSO) algorithm in order to maximize the natural frequencies. Finite-element analysis (FEA) result indicates that the mechanism has an almost linear force-deflection relationship, high first natural frequency (720.52 Hz), and ideal decoupling property. To cope with the nonlinearities such as hysteresis that exists in the PZT, the control system is constructed by a proportional-integral-derivative (PID) feedback controller with a feedforward compensator based on Preisach model. The fabricated prototype has a 19.2 μm × 8.8 μm rectangular workspace with coupling less than 5%. The result of the closed-loop test shows that the XY stage can achieve positioning, tracking and contouring tasks with small errors. View full abstract»

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  • Design and Development of a Flexure-Based Dual-Stage Nanopositioning System With Minimum Interference Behavior

    Page(s): 554 - 563
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1015 KB) |  | HTML iconHTML  

    Dual-servo systems (DSSs) are highly desirable in micro-/nanomanipulation when high positioning accuracy, long stroke motion, and high servo bandwidth are required simultaneously. This paper presents the design and development of a new flexure-based dual-stage nanopositioning system. A coarse voice coil motor (VCM) and a fine piezoelectric stack actuator (PSA) are adopted to provide long stroke and quick response, respectively. A new decoupling design is carried out to minimize the interference behavior between the coarse and fine stages by taking into account actuation schemes as well as guiding mechanism implementations. Both analytical results and finite-element model (FEM) results show that the system is capable of over 10 mm traveling, while possessing a compact structure. To verify the decoupling property, a single-input-single-output (SISO) control scheme is realized on a prototype to demonstrate the performance of the DSS without considering the interference behavior. Experimental results not only confirm the superiority of the dual-servo stage over the standalone coarse stage but reveal the effectiveness of the proposed idea of decoupling design. View full abstract»

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  • Real-Time Scheduling of Single-Arm Cluster Tools Subject to Residency Time Constraints and Bounded Activity Time Variation

    Page(s): 564 - 577
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1249 KB) |  | HTML iconHTML  

    It is very challenging to schedule cluster tools subject to wafer residency time constraints and activity time variation. This work develops a Petri net model to describe the system and proposes a two-level real-time scheduling architecture. At the lower level, a real-time control policy is used to offset the activity time variation as much as possible. At the upper level, a periodical off-line schedule is derived under the normal condition. This work presents the schedulability conditions and scheduling algorithms for an off-line schedule. The schedulability conditions can be analytically checked. If they are satisfied, an off-line schedule can be analytically found. The off-line schedule together with a real-time control policy forms the real-time schedule for the system. It is optimal in terms of cycle time minimization. Illustrative examples are given to show the application of the proposed approach. Note to Practitioners-This paper discusses the real-time scheduling problem of single-arm cluster tools with wafer residency time constraints and bounded activity time variation. With a Petri net model, schedulability is analyzed and schedulability conditions are presented by using analytical expressions. Then, an efficient algorithm is proposed to find a periodical schedule if it is schedulable. Such a schedule is optimal in terms of cycle time and can adapt to bounded activity time variation. Therefore, it is applicable to the scheduling and real-time control of cluster tools in semiconductor manufacturing plants. View full abstract»

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  • Adaptive Hybrid Algorithms for the Sequence-Dependent Setup Time Permutation Flow Shop Scheduling Problem

    Page(s): 578 - 595
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    In this paper, adaptive hybrid genetic algorithms (AHA0 ~ AHA3) are proposed for the sequence-dependent setup times permutation flow shop scheduling problem with the objectives to minimize makespan and total weighted tardiness, both of which will be considered separately. Each job is assigned an introduced inheriting factor, which indicates the probability that the job is copied to the same position of the offspring individual during crossover and is dynamically updated. Good genes and bad genes can be mined by inheriting factors. Probability-based Multi-Point Crossover (PMPC) is constructed to inherit good genes with high probabilities to the offspring and destroy bad genes with high probabilities. Inheriting factors determine such probabilities and the genetic algorithm evolves adaptively and is denoted as AHA0. Three local search methods (LS1, LS2, and LS3) are separately integrated with AHA0 and three hybrid algorithms AHA1 ~ AHA3 are developed. Compared with GA_RMA and CPSO (effective algorithms without integrating any local search), AHA0 is the most effective. Another six hybrid algorithms are extended from IG_RS (the current best algorithm for the two considered problems) and CPSO by integrating with the three local search methods and they are compared with AHA1 ~ AHA3 comprehensively. Experimental results show that for the two considered problems, AHA1 outperforms the other algorithms on small setup-time instances and AHA3 is the most effective algorithm among the compared ones on big setup-time instances, while the computation time of AHA1 is moderate among the LS1 integrated algorithms, so is AHA3. The effects of the key factors or parameters on algorithms are analyzed as well. View full abstract»

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  • Efficient Selection of a Set of Good Enough Designs With Complexity Preference

    Page(s): 596 - 606
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    Many automation or manufacturing systems are large, complex, and stochastic. Since closed-form analytical solutions generally do not exist for such systems, simulation is the only faithful way for performance evaluation. From the practical engineering perspective, the designs (or solution candidates) with low complexity (called simple designs) have many advantages compared with complex designs, such as requiring less computing and memory resources, and easier to interpret and to implement. Therefore, they are usually more desirable than complex designs in the real world if they have good enough performance. Recently, Jia (IEEE Trans. Autom. Sci. Eng., vol. 8, no. 4, pp. 720-732, Oct. 2010) discussed the importance of design simplicity and introduced an adaptive simulation-based sampling algorithm to sequentially screen the designs until one simplest good enough design is found. In this paper, we consider a more generalized problem and introduce two algorithms OCBA-mSG and OCBA-bSG to identify a subset of m simplest and good enough designs among a total of K (K >; m) designs. By controlling the simulation allocation intelligently, our approach intends to find those simplest good enough designs using a minimum simulation time. The numerical results show that both OCBA-mSG and OCBA-bSG outperform some other approaches on the test problems. View full abstract»

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  • Energy Modeling of Machine Tools for Optimization of Machine Setups

    Page(s): 607 - 613
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    In this paper, a new energy model is developed based on the kinematic and dynamic behaviors of a chosen machine tool. One significant benefit of the developed energy model is their inherited relationship to the design variables involved in the manufacturing processes. Without radical changes of the machine tool's structure, the proposed model can be readily applied to optimize process parameters to reduce energy consumption. A new parallel kinematic machine Exechon is used as a case study to demonstrate the modeling procedure. The derived energy model is then used for simulation of drilling operations on aircraft components to verify its feasibility. Simulation results indicate that the developed energy model has led to an optimized machine setup which only consumes less than one-third of the energy of an average machine setup over the workspace. This approach can be extended and applied to other machines to establish their energy models for green and sustainable manufacturing. View full abstract»

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  • Recognition of Curved Surfaces From “One-Dimensional” Tactile Data

    Page(s): 613 - 621
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    This paper presents a method for recognition of 3D objects with curved surfaces from linear tactile data. For every surface model in a given database, a lookup table is constructed to store principal curvatures precomputed at points of discretization on the surface. To recognize an object, a robot hand with touch sensing capability obtains data points on its surface along three concurrent curves. The two principal curvatures estimated at the curve intersection point are used to look up the table associated with each model to locate surface discretization points that have similar local geometries. Local searches are then performed starting at these points to register the tactile data onto the model. The model with the best registration result is recognized. The presented method can recognize closed-form surfaces as well as triangular meshes, as demonstrated through simulation and robot experiments. Potential applications include recognition of (manufactured) home items that are grasped daily, and dexterous manipulation during which recognition is simultaneously performed. View full abstract»

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  • Kalman Filter-Based Coarse-to-Fine Control for Display Visual Alignment Systems

    Page(s): 621 - 628
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    A coarse-to-line two-stage control method is investigated for the display visual alignment systems. The proposed visual servo is with hierarchical loops, where the original line but slow vision loop is necessary for the exact localization of alignment marks while the coarse but fast vision loop of exploiting pruned image data is to compensate for the mask-panel misalignment. The degraded resolution of the reduced images is recovered in terms of the Kalman filter which tracks the mark centroids in near realtime. In order to construct the recursive estimation algorithm, the motion model for the moving alignment marks is determined by solving the forward kinematics of positioning mechanism and the measurements from vision sensors are given by means of the geometric template matching (Kwon and Hwang, “Kinematics, pattern recognition, and motion control of mask-panel alignment system,” Control Eng. Practice, vol. 19, pp. 883-892, 2011). Compared with the conventional alignment methods, this approach enables a fast and line alignment control. Experimental results are followed to validate the proposed control framework. Note to Practitioners-In order to successfully apply the developed alignment control to any display manufacturing equipment, it is necessary to well understand the principle of the geometric template matching (GTM) as an alignment mark specific fast algorithm, the details on which can be consulted in our preceding works (Kwon and Hwang, “Kinematics, pattern recognition, and motion control of mask-panel alignment system,” Control Eng. Practice, vol. 19, pp. 883-892, 2011). The new approach has the goal of updating the pose of an alignment mark as fast as the capturing rate of a frame grabber by utilizing pruned image data but recovering the lost resolution in terms of the Kalman filter. For example, in using a common 30 fps grabber, the reduced image of 320 240 pixels is a proper choice to finish the image processing and Kalm- n filtering within 30 ms under GTM. The proposed algorithm can be implemented in the current industrial display aligners by modifying the control software so that the reference inputs for the distributed joint servos follow the error compensation trajectory in Fig. 4 with the Kalman filter estimates. View full abstract»

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  • Neural-Network-Based Optimal Control for a Class of Unknown Discrete-Time Nonlinear Systems Using Globalized Dual Heuristic Programming

    Page(s): 628 - 634
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    In this paper, a neuro-optimal control scheme for a class of unknown discrete-time nonlinear systems with discount factor in the cost function is developed. The iterative adaptive dynamic programming algorithm using globalized dual heuristic programming technique is introduced to obtain the optimal controller with convergence analysis in terms of cost function and control law. In order to carry out the iterative algorithm, a neural network is constructed first to identify the unknown controlled system. Then, based on the learned system model, two other neural networks are employed as parametric structures to facilitate the implementation of the iterative algorithm, which aims at approximating at each iteration the cost function and its derivatives and the control law, respectively. Finally, a simulation example is provided to verify the effectiveness of the proposed optimal control approach. Note to Practitioners-The increasing complexity of the real-world industry processes inevitably leads to the occurrence of nonlinearity and high dimensions, and their mathematical models are often difficult to build. How to design the optimal controller for nonlinear systems without the requirement of knowing the explicit model has become one of the main foci of control practitioners. However, this problem cannot be handled by only relying on the traditional dynamic programming technique because of the "curse of dimensionality". To make things worse, the backward direction of solving process of dynamic programming precludes its wide application in practice. Therefore, in this paper, the iterative adaptive dynamic programming algorithm is proposed to deal with the optimal control problem for a class of unknown nonlinear systems forward-in-time. Moreover, the detailed implementation of the iterative ADP algorithm through the globalized dual heuristic programming technique is also presented by using neural networks. Finally, the effectiveness of the control strategy is illustrated- via simulation study. View full abstract»

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Aims & Scope

T-ASE will publish foundational research on Automation: scientific methods and technologies that improve efficiency, productivity, quality, and reliability, specifically for methods, machines, and systems operating in structured environments over long periods, and the explicit structuring of environments.

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Editor-in-Chief
Ken Goldberg
University of California, Berkeley