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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 6 • Date Nov. 1999

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Displaying Results 1 - 23 of 23
  • 1999 Index IEEE transactions on systems, man, and cybernetics Part A: Systems and humans Vol. 29

    Page(s): 1 - 11
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    Freely Available from IEEE
  • Fusion of fixation and odometry for vehicle navigation

    Page(s): 593 - 603
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    This paper deals with the problem of determining the position and orientation of an autonomous guided vehicle (AGV) by fusing odometry with the information provided by a vision system. The main idea is to exploit the ability of pointing a camera in different directions, to fixate on a point of the environment while the AGV is moving. By fixating on a landmark, one can improve the navigation accuracy even if the scene coordinates of the landmark are unknown. This is a major improvement over previous methods which assume that the coordinates of the landmark are known, since any point of the observed scene can be selected as a landmark, and not just pre-measured points. This work argues that fixation is basically a simpler procedure than previously mentioned methods. The simplification comes from the fact that only one point needs to be tracked as opposed to multiple points in other methods. This disposes of the need to be able to identify which of the landmarks is currently being tracked, through a matching algorithm or by other means. We support our findings with both experimental and simulation results View full abstract»

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  • Hybrid control for a class of underactuated mechanical systems

    Page(s): 649 - 654
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    This paper considers a stabilizing hybrid scheme to control a class of underactuated mechanical systems. The hybrid controller consists of a collection of state feedback controllers plus a discrete-event supervisor. When the continuous-state hits a switching boundary, a new controller is applied to the plant. Lyapunov theory is used to determine the switching boundaries and to guarantee the stability of the closed-loop hybrid system. This approach is applied to the well-known swing up and balancing control problem of the inverted pendulum View full abstract»

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  • Stability switches and bifurcation analysis of a neural network with continuously delay

    Page(s): 692 - 696
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    A continuously delayed neural network with strong kernel is investigated. We found that a switch from stability to instability may occur for certain range of system parameters and must then be followed by a switch back to stability. We also investigate bifurcation phenomena of this model. Using the mean time delay as a bifurcation parameter, we prove that Hopf bifurcation occurs, i.e., a family of periodic solutions bifurcates from the equilibrium when the bifurcation parameter passes through a critical value. Stability criteria for the bifurcating periodic solutions are obtained. Some computer simulations illustrate correctness of the results View full abstract»

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  • A hierarchical constraint satisfaction approach to product selection for electronic shopping support

    Page(s): 525 - 532
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    The development of advanced information and telecommunications technologies has established more convenient ways of interorganizational business transactions. Especially, various forms of electronic trading systems are introduced, which replicate, and often improve, functions of physical market places. We propose a product selection mechanism for such an electronic marketplace, which is viewed as a satisfaction problem of hierarchically organized constraints over product attributes. The proposed approach is more expressively powerful and flexible than product selection based on a single product taxonomy hierarchy View full abstract»

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  • Human shape recognition performance for 3D tactile display

    Page(s): 637 - 644
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    The paper describes the relationship between the pin-matrix density of a tactile display and the recognition performance of displayed 3D shapes. Three types of pin-matrix tactile display, that generate 3D shapes, were used for the experiment. The pitch of pins was 2 mm, 3 mm, 5 mm each. We assumed that surfaces, edges, and vertices were primitive 3D shape information, so tested shapes were classified into these three categories. We assumed two types of finger touching mode: 1) fingertip-only, allowed full use of spatial shape information given to the fingertip; and 2) allowed tracing of the object. Recognition time and the classified error rate were measured. We obtained results on the relationship between pin pitch and recognition performance data. Regression curves for pin pitch and recognition time were plotted. A significance test of recognition time versus pin pitch was done. The error rate of identification versus pin pitch was described. Our results provide basic knowledge for developing tactile presentation devices View full abstract»

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  • Stochastic optimization over continuous and discrete variables with applications to concept learning under noise

    Page(s): 542 - 553
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    We consider optimization problems where the objective function is defined over some continuous and some discrete variables, and only noise corrupted values of the objective function are observable. Such optimization problems occur naturally in PAC learning with noisy samples. We propose a stochastic learning algorithm based on the model of a hybrid team of learning automata involved in a stochastic game with incomplete information to solve this optimization problem and establish its convergence properties. We then illustrate an application of this automata model in learning a class of conjunctive logic expressions over both nominal and linear attributes under noise View full abstract»

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  • Multimodal decision-level fusion for person authentication

    Page(s): 674 - 680
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    The use of clustering algorithms for decision-level data fusion is proposed. Person authentication results coming from several modalities (e.g., still image, speech), are combined by using fuzzy k-means (FKM) and fuzzy vector quantization (FVQ) algorithms, and a median radial basis function (MRBF) network. The quality measure of the modalities data is used for fuzzification. Two modifications of the FKM and FVQ algorithms, based on a fuzzy vector distance definition, are proposed to handle the fuzzy data and utilize the quality measure. Simulations show that fuzzy clustering algorithms have better performance compared to the classical clustering algorithms and other known fusion algorithms. MRBF has better performance especially when two modalities are combined. Moreover, the use of the quality via the proposed modified algorithms increases the performance of the fusion system View full abstract»

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  • Kinematic modeling of head-neck movements

    Page(s): 604 - 615
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    The main objective is to generate kinematic models for the head and neck movements. The motivation comes from our study of individuals with quadriplegia and the need to design rehabilitation aiding devices such as robots and teletheses that can be controlled by head-neck movements. It is then necessary to develop mathematical models for the head and neck movements. Two identification methods have been applied to study the kinematics of head-neck movements of able-body as well as neck-injured subjects. In particular, sagittal plane movements are well modeled by a planar two-revolute-joint linkage. In fact, the motion in joint space seems to indicate that sagittal plane movements may be classified as a single DOF motion. Finally, a spatial three-revolute-joint system has been employed to model 3D head-neck movements View full abstract»

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  • Fuzzy logic based set-point weight tuning of PID controllers

    Page(s): 587 - 592
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    A methodology, based on fuzzy logic, for the tuning of proportional-integral-derivative (PID) controllers is presented. A fuzzy inference system is adopted to determine the value of the weight that multiplies the set-point for the proportional action, based on the current output error and its time derivative. In this way, both the overshoot and the rise time in set-point following can be reduced. The values of the proportional gain and the integral and derivative time constant are determined according to the well-known Ziegler-Nichols formula so that a good load disturbance attenuation is also assured. The methodology is shown to be effective for a large range of processes and is valuable for industrial settings since it is intuitive, it requires only a small extra computational effort, and it is robust with regard to parameter variations. The tuning of the parameters of the fuzzy module can be easily done by hand or by means of an autotuning procedure based on genetic algorithms View full abstract»

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  • Diagnosis of continuous valued systems in transient operating regions

    Page(s): 554 - 565
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    The complexity of present day embedded systems (continuous processes controlled by digital processors), and the increased demands on their reliability motivate the need for monitoring and fault isolation capabilities in the embedded processors. This paper develops monitoring, prediction, and fault isolation methods for abrupt faults in complex dynamic systems. The transient behavior in response to these faults is analyzed in a qualitative framework using parsimonious topological system models. Predicted transient effects of hypothesized faults are captured in the form of signatures that specify future faulty behavior as higher order time-derivatives. The dynamic effects of faults are analyzed by a progressive monitoring scheme till transient analysis mechanisms have to be suspended in favor of steady state analysis. This methodology has been successfully applied to monitoring of the secondary sodium cooling loop of a fast breeder reactor View full abstract»

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  • Constrained SPSA controller for operations processes

    Page(s): 645 - 649
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    Continuous quality improvement calls for employing methodologies that assist in continual reduction of variations in process performance characteristics around their target values. The study considers a case in which some of the operations process parameters/inputs are required to take values in pre-specified ranges. To improve the process performance while accounting for these requirements, the study employs a neural network-based model-free controller along with the penalty function. Simultaneous perturbation stochastic gradient approximation method is used to iteratively estimate the weights of neural network and as a result to estimate the control values. Furthermore, the study uses a special cause control chart to monitor the performance of the controller in reducing the process variations and to signal the change in the process dynamics. Simulation findings indicate that the neural network model-free provides control values that result in fewer nonconforming outputs than when the requirements are not incorporated in optimization process View full abstract»

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  • Competitiveness of manufacturing firms: an application of fuzzy weighted average

    Page(s): 661 - 667
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    In order to attain a competitive edge in the world marketplace, manufacturing companies must produce high-quality products at low cost. To achieve this, many companies have noticed that in addition to technology, management also plays a vital role. Following some previous studies, this paper devises a competitiveness index based on automation technology and manufacturing management for manufacturing firms. Since most measures are described subjectively by linguistic terms, a fuzzy set approach is adopted, in that the fuzzy measures from different criteria are weighted by their corresponding importance, which are also represented by fuzzy values. The fuzzy weighted average approach produces results which are more informative. To distinguish the superiority of the competitive power of different firms, a fuzzy ranking method is applied. As an illustration, the competitiveness indexes of 15 machinery firms in Taiwan are calculated and ranked View full abstract»

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  • Hierarchical control of end-point impedance and joint impedance for redundant manipulators

    Page(s): 627 - 636
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    This paper proposes an impedance control method for redundant manipulators, which can control not only the end-point impedance using one of the conventional impedance control methods, but the joint impedance which has no effects on the end-point impedance. First, a sufficient condition for the joint impedance controller is derived. Then, the optimal controller for a given desired joint impedance is designed using the least squares method. Finally, computer simulations and experiments using a planar direct-drive robot are performed in order to confirm the validity of the proposed method View full abstract»

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  • A compliant contact model with nonlinear damping for simulation of robotic systems

    Page(s): 566 - 572
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    Contact modeling is an important aspect of simulation of many robotic tasks. In the paper, a compliant contact model with nonlinear damping is investigated, and many previously unknown characteristics of the model are developed. Compliance is used to eliminate many of the problems associated with using rigid body models with Coulomb friction, while the use of nonlinear damping eliminates the discontinuous impact forces and most sticky tensile forces which arise in Kelvin-Voigt linear models. Two of the most important characteristics of the model are the dependence of the coefficient of restitution on velocity and damping in a physically meaningful manner, and its computational simplicity. A full mathematical development for an impact response is given, along with the effects of the system and model parameters on energy loss. A quasistatic analysis gives results which are consistent with energy loss characteristics of a more complex distributed foundation model under sustained contact conditions. A foot contact example for a walking machine is given which demonstrates the applicability of the model for impact on foot placement, sustained contact during the support phase, and the breaking of the contact upon liftoff of the foot View full abstract»

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  • State estimation with biased observations

    Page(s): 681 - 686
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    State estimation is difficult when the system has multiple modes of operation. Modal transitions create discontinuities in the reference point for the local state variables. The uncertain reference point increases the ambiguity in the state measurement. The paper presents an estimation algorithm that can be used in multimodal applications. The algorithm is shown to be superior to the Kalman filter when the state measurement is contaminated with a mode dependent offset. Despite the uncertain reference point in the observation, good estimates of the underlying entire state processes can be generated View full abstract»

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  • Inductive pattern learning

    Page(s): 667 - 674
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    A general (nonheuristic) computational analytical model to tackle the difficult unsupervised inductive learning problem is proposed by making some additions and modifications to an existing metric model so that the model is more elegant and able to handle the unsupervised case. It turns out that it is instructive to treat, in essence, the supervised problem with noise as an unsupervised problem. We demonstrate the success of the new model on the benchmark XOR (exclusive-or) and parity problems by showing how the inductive agent successfully learns the weights in a dynamic manner that would allow it to distinguish between bit-strings of any length and unknown labels View full abstract»

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  • Stochastic ordering of extreme value distributions

    Page(s): 696 - 701
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    We investigate the second-order stochastic ordering of the extreme value distributions within each of three families: the Gumbel distribution, the Frechet distribution, and the Weibull distribution. We give conditions for second-order stochastic dominance, conditional second-order stochastic dominance, and order statistics second-order stochastic dominance within the three families View full abstract»

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  • Dynamic postural control method for biped in unknown environment

    Page(s): 616 - 626
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    We propose a new way to solve the dynamic equilibrium problem of a biped robot under unknown external perturbations. For that, a multichain mechanical model of a human body (called BIPMAN) is proposed with a general architecture. The principle of the dynamic postural control is based on the correction of the trunk center of mass acceleration and on the force distribution exerted by the limbs on the trunk. To ensure a real time dynamic compensation faced to an unknown external perturbation, we have introduced a new approach called real time criteria and constraints adaptation. This is based on a linear programming technique with a general criterion which optimizes the force distribution. The ponderation coefficients and the task constraints notions are introduced in order to specify criteria and constraints adapted to specific task classes in presence of an unknown external perturbation. Many results are presented to demonstrate criteria and constraints influences on the dynamic equilibrium View full abstract»

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  • A structured adaptive supervisory control methodology for modeling the control of a discrete event manufacturing system

    Page(s): 573 - 586
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    Two basic measures, model complexity and model construction efficiency, are usually used to evaluate the implementability of a methodology for modeling the control of a discrete event manufacturing system (DEMS) on the shop floor. Many well-recognized methods are used to represent and analyze the dynamics of DEMs, but not many relevant applications have been found in developing control software for the shop floor due to their shortcomings in satisfying these two measures. The paper explores a methodology for modeling the control of a DEMS, which leads to ease of control software development, rather than a new representational/analytical tool, by significantly reducing the model complexity (in terms of the number of required control states) and improving the model construction efficiency. First, an extended finite machine, called a deterministic finite capacity machine (DFCM) with parallel computing capability is developed. Based on DFCMs, the complexity growth function of a DEMS control model is linear in the number of synthesized control components. Then, an automaton structure of a DFCM control model, called structured adaptive supervisory control (SASC), is developed. By referring to supervisory control theory, an SASC model is created with three function layers: acceptance, adaptive supervision, and execution. The well-defined structure ensures that the control model can be constructed systematically View full abstract»

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  • A neural gain scheduling network controller for nonholonomic systems

    Page(s): 654 - 661
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    We propose a neural gain scheduling network controller (NGSNC) to improve the gain scheduling controller for nonholonomic systems. We derive the neural networks that can approximate the gain scheduling controller arbitrarily well when the sampling frequency satisfies the sampling theorem. We also show that the NGSNC is independent of the sampling time. The proposed NGSNC has the following important properties: 1) same performance as the continuous-parameter gain scheduling controller; 2) less computing time than the continuous-parameter gain scheduling controller; 3) good robustness against the sampling intervals; and 4) straightforward stability analysis. We then show that some of nonholonomic systems can be converted to equivalent linear parameter-varying systems. As a result, the NGSNC can stabilize nonholonomic systems View full abstract»

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  • A heuristic error-feedback learning algorithm for fuzzy modeling

    Page(s): 686 - 691
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    Describes a type of fuzzy system with interpolating capability to extract MISO fuzzy rules from input-output sample data through learning. The proposed model inherits many merits from Sugeno-type models and their variations. A heuristic error-feedback learning algorithm associated with the model is suggested. Based on which, the estimator is shown to have a self-adjusting step when approaching a minimum View full abstract»

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  • Stochastic minimax decision rules for risk of extreme events

    Page(s): 533 - 541
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    We use the theory of order statistics, the concepts of first- and second-order stochastic dominance (FSD and SSD) to develop an order statistics SSD minimax decision rule. It can be used to refine choice within the random variables in the SSD noninferior set. We are able to reduce the size of the SSD noninferior set when we assume that the decision-maker is most concerned about the potential adverse outcomes at the right tail of the probability distribution. In other words, we consider the risk of extreme events and build on order statistics in order to refine the decision rules. In some eases, the order statistics SSD minimax decision rule can provide us with a unique choice from among the SSD noninferior set. We define the concept of conditional second-order stochastic dominance (CSSD) in order to model the risk of extreme events. We also use the concept of CSSD to develop a CSSD minimax decision rule View full abstract»

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Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta