By Topic

Systems, Man and Cybernetics, IEEE Transactions on

Issue 12 • Date Dec 1995

Filter Results

Displaying Results 1 - 12 of 12
  • An extended finitely recursive process model for discrete event systems

    Page(s): 1616 - 1627
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1160 KB)  

    In the area of discrete event systems (DES) a growing need is being felt for new classes of models to describe both logical and timed behaviors efficiently. Among the frameworks presented recently, the finitely recursive process model is a powerful one. However it is solely based on a characterization of the event strings generated in the DES. In this work an augmented version of the above model is presented, where the notion of a collection of system related variables, forming the `state-space' of the system, is introduced. A concept of a `silent transition' is introduced for effective modelling of concurrent DES. To allow nonuniqueness of the initial state, an extended process framework is presented and a recursive characterization is made in terms of a collection of constant processes and process operators. A general timed transition model (Ostroff, 1990) is modelled as an extended process to show the describing power of the framework. A model of a robot controller is presented to show the usefulness of its different features in modelling real systems View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Repeatable pseudoinverse control for planar kinematically redundant manipulators

    Page(s): 1657 - 1662
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (584 KB)  

    The necessary and sufficient conditions for repeatable pseudoinverse control are now well known. A very simple example of a configuration for planar manipulators that is conservative is also known. It is also known there is no conservative configuration for the most common definition of joint angles. The question remains whether there exists any other conservative case using other definitions of joint angles, or equivalently, for pseudoinverse control using different, but constant, joint norms. This paper addresses this question using a combination of analytical and numerical methods. Such cases have been found, however, the resulting configurations are the same as previously known View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • How the testing techniques for a decision support system changed over nine years

    Page(s): 1533 - 1542
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1044 KB)  

    A decision support system has been under development since 1985 to help speech clinicians diagnose small children who have begun to stutter. This paper describes how testing of the system evolved during these nine years. Testing included: 1) having an expert use and evaluate it, 2) running test cases, 3) developing a program to detect redundant rules, 4) using the analytic hierarchy process, 5) running a program that checks a knowledge base for consistency and completeness, 6) having five experts independently critique the system, 7) obtaining diagnoses of stuttering from these five experts derived from reports of children who had been evaluated for possible stuttering problems, 8) using the system to expose missing and ambiguous information in 30 clinical reports, and 9) analyzing the dispersion and bias of six experts and the decision support system in diagnosing stuttering. When using the final system, three clinicians with widely differing backgrounds produced diagnostic opinions that evidence little variability and were indistinguishable from those of a panel of five experienced clinicians View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Real-time eye feature tracking from a video image sequence using Kalman filter

    Page(s): 1568 - 1577
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1080 KB)  

    Eye movement analysis is of importance in clinical studies and in research. Monitoring eye movements using video cameras has the advantage of being nonintrusive, inexpensive, and automated. The main objective of this paper is to propose an efficient approach for real-time eye feature tracking from a sequence of eye images. To this end, first the authors formulate a dynamic model for eye feature tracking, which relates the measurements from the eye images to the tracking parameters. In the model, the center of the iris is chosen as the tracking parameter vector and the gray level centroid of the eye is chosen as the measurement vector. In the authors' procedure for evaluating the gray level centroid, the preprocessing step such as edge detection and curve fitting need to be performed only for the first frame of the image sequence. A discrete Kalman filter is then constructed for the recursive estimation of the eye features, while taking into account the measurement noise. Experimental results are presented to demonstrate the accuracy aspects and the real-time applicability of the proposed approach View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • &thetas;(1) time quadtree algorithm and its application for image geometric properties on a mesh connected computer (MCC)

    Page(s): 1640 - 1648
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (844 KB)  

    Quadtree and octree decomposition of multicolored images is often used to solve problems of image processing. This paper describes a θ(1) time algorithm for the decomposition of the images into quadtree and octree on a mesh connected computer. Images are stored in the MCC of the same size, at one pixel per processing element (PE). Certain applications of the algorithm are also described, namely the computation of such geometric properties as the area and perimeter. The complexity of these algorithms depends on the hierarchical data structure. They are carried out in O(log2 m+log m) times on an n×n MCC, where m=n/k, and k is the size of the smallest homogeneous quadrant in the image View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Time-optimal motion of a cooperating multiple robot system along a prescribed path

    Page(s): 1648 - 1657
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (860 KB)  

    This paper deals with a systematic analysis of the time-optimal motion of a multiple robot system carrying an object along a prescribed path. In our approach, the time-optimal motion planning problem is formulated in a concise form by employing a parameter describing the movement along the path and a vector representing the internal force. Various constraints governing the motion yield the so-called admissible region in the phase plane of the parameter. The orthogonal projection technique and the theory of multiple objective optimization make it possible to construct the admissible region, while taking into account the load distribution problem that is coupled with the motion. Furthermore, our approach provides a way of detailed investigation for the admissible region that is not simply connected. The resulting velocity profile of the path parameter and the internal force at every instant determine the optimal actuator torques for each robot. Computer simulation results reinforce the physical interpretation on the characteristics of the optimal actuator torques View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimal supervision of discrete event systems in a temporal logic framework

    Page(s): 1595 - 1605
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1076 KB)  

    Temporal logic models (TLM's) have been recently defined and used for the synthesis of discrete event systems (DES) supervisors. A synthesis procedure was developed by exploring the system state space and by determining the reachable states from a given state. The supervisor selects acceptable paths in the reachability graph of the unsupervised system. In this paper another synthesis problem is addressed: the optimization of a DES supervisor. A sequence of events which drive the system from a given initial state to a given final state is generated by minimizing a cost function index. Introducing definitions regarding measurement spaces and measurement functions it is shown that sufficient conditions are met for the design of the active supervisor. The optimization is then solved by applying the A* algorithm on the reachability graph with the specification restrictions. A heuristic function is considered to help the search. An example of read-write processes illustrates our results and the novelty of this approach View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fuzzy model-reference adaptive control

    Page(s): 1606 - 1615
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (836 KB)  

    This paper proposes a fuzzy model-reference adaptive control (fuzzy-MRAC) to deal with controlling a plant with unknown parameters which are dependent on known variables. The proposed method uses the fuzzy basis function expansion (FBFE) to represent the unknown parameters and change the identification problem from identifying the original unknown parameters to identifying the coefficients of the FBFE. This data representation is substantiated by the Stone Weierstrass theorem which indicates that any continuous function can be represented by the FBFE. With the aid of the FBFE, the unknown parameters can be estimated more precisely and better performance can be expected from the fuzzy-MRAC than the traditional MRAC. Furthermore, the adaptation scheme of the proposed fuzzy-MRAC is based on both the tracking error and the prediction error. Combining these two sources of error information, the proposed fuzzy-MRAC provide more adaptation power than a traditional adaptive control and its stability and convergence properties are preserved. Computer simulations were conducted to show the validity and the performance of the proposed fuzzy-MRAC and its improvements over the traditional MRAC View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A global optimization method for the Stackelberg problem with convex functions via problem transformation and concave programming

    Page(s): 1635 - 1640
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (540 KB)  

    A global optimization method is proposed for solving the Stackelberg problem through problem transformation and concave programming. The proposed method is applicable to a broad class of the Stackelberg problem, in which each function in upper-level is convex or a difference of two convex functions, and that in lower-level is convex View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Direct adaptive regulation of unknown nonlinear dynamical systems via dynamic neural networks

    Page(s): 1578 - 1594
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1220 KB)  

    A direct nonlinear adaptive state regulator, for unknown dynamical systems that are modeled by dynamic neural networks is discussed. In the ideal case of complete model matching, convergence of the state to zero plus boundedness of all signals in the closed loop is ensured. Moreover, the behavior of the closed loop system is analyzed for cases in which the true plant differs from the dynamic neural network model in the sense that it is of higher order, or due to the presence of a modeling error term. In both cases, modifications of the original control and update laws are provided, so that at least uniform ultimate boundedness is guaranteed, even though in some cases the stability results obtained for the ideal case are retained View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Localization uncertainty in area-based stereo algorithms

    Page(s): 1628 - 1634
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (880 KB)  

    A theory for treating uncertainty in localizing 3D objects using local, area-based stereo algorithms is presented. In addition, the resultant implications for practical applications are discussed. First, we propose a phase-based stereo algorithm as a representative of this kind of algorithms. The concept of a receptive field is introduced to describe a region on the target where stimuli with fixed disparity but variable position in the receptive field yield the same disparity response. This positional uncertainty on the targets is transformed into a localization uncertainty existing in the world. Strategies for optimally localizing 3D structure are developed. These considerations also lead to an upper bound for the vergence angle and a fusion strategy for multiple views when employing an active stereo camera system. Finally we show the validity of our approach by experimental results View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Adaptive image segmentation using a genetic algorithm

    Page(s): 1543 - 1567
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2820 KB)  

    We present the first closed loop image segmentation system which incorporates a genetic algorithm to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions such as time of day, time of year, clouds, etc. The segmentation problem is formulated as an optimization problem and the genetic algorithm efficiently searches the hyperspace of segmentation parameter combinations to determine the parameter set which maximizes the segmentation quality criteria. The goals of our adaptive image segmentation system are to provide continuous adaptation to normal environmental variations, to exhibit learning capabilities, and to provide robust performance when interacting with a dynamic environment. We present experimental results which demonstrate learning and the ability to adapt the segmentation performance in outdoor color imagery View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.