Handling single node failures using agents in computer clusters

The work reported in this paper is motivated towards handling single node failures for parallel summation algorithms in computer clusters. An agent based approach is proposed in which a task to be executed is decomposed to sub-tasks and mapped onto agents that traverse computing nodes. The agents intercommunicate across computing nodes to share information during the event of a predicted node failure. Two single node failure scenarios are considered. The Message Passing Interface is employed for implementing the proposed approach. Quantitative results obtained from experiments reveal that the agent based approach can handle failures more efficiently than traditional failure handling approaches.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks

An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.

Microprocessor systems: an introduction

The aim of this book is to provide and introduction to microprocessor systems, their operation and design. It covers those topics needed by engineers and computer scientists who are interested in applying microprocessors in practical situations, namely computer hardware including logic and interfacing, software, in particular high level and assembly language programming, and the design and testing of such systems. The fundamental principles of micrprocessor systems are described and these are illustrated with reference to two microprocessors, the 32-bit MC68020 from Motorola and a single chip microcomputer, the 8051 from Intel; and in addition, interfacing to the general purpose STE bus is described. The details of the processors and the bus are concentrated in three chapters, thus allowing the presentation of the material to be independent of the microprocessors if that is desired, and permitting the specific details to be found easily.

A CAD-based computer vision system

A vision system for recognizing rigid and articulated three-dimensional objects in two-dimensional images is described. Geometrical models are extracted from a commercial computer aided design package. The models are then augmented with appearance and functional information which improves the system's hypothesis generation, hypothesis verification, and pose refinement. Significant advantages over existing CAD-based vision systems, which utilize only information available in the CAD system, are realized. Examples show the system recognizing, locating, and tracking a variety of objects in a robot work-cell and in natural scenes.

Cancellation of residual ghost VSB components from video IIR deghoster systems

Certain deghosters suffer from the presence of distortion caused by the quadrature forming nature of the IF VSB filter operating on a ghosted IF signal. By analysing this a priori effect, a specific deghoster solution is found by using the phase quadrature detected IF signal to cancel the VSB induced ghost quadrature distortions from the detected inphase signal before deghosting takes place.

Remote control systems laboratory

Control systems theory can be a discipline difficult to learn without some laboratory help. With the help of focused laboratories this discipline turns to be very interesting to the students involved. The main problem is that laboratories aren't always available to students, and sometimes, when they are available, aren't big enough to a growing student population. Thus, with computer networks growing so fast, why don't create remote control labs that can be used by a large number of students? Why don't create remote control labs using Internetⓒ Copyright ?2001 IFAC Keywords: Remote Control, Computer Networks, Database, Educational Aids, Laboratory Education, Communication Control Applications.

Cooperative task support for the control room

The National Grid Company plc. owns and operates the electricity transmission network in England and Wales, the day to day running of the network being carried out by teams of engineers within the national control room. The task of monitoring and operating the transmission network involves the transfer of large amounts of data and a high degree of cooperation between these engineers. The purpose of the research detailed in this paper is to investigate the use of interfacing techniques within the control room scenario, in particular, the development of an agent based architecture for the support of cooperative tasks. The proposed architecture revolves around the use of interface and user supervisor agents. Primarily, these agents are responsible for the flow of information to and from individual users and user groups. The agents are also responsible for tackling the synchronisation and control issues arising during the completion of cooperative tasks. In this paper a novel approach to human computer interaction (HCI) for power systems incorporating an embedded agent infrastructure is presented. The agent architectures used to form the base of the cooperative task support system are discussed, as is the nature of the support system and tasks it is intended to support.

HCI issues in power systems

With the advance of information technology capabilities, and the importance of human computer interfaces within society there has been a significant increase in research activity within the field of human computer interaction (HCI). This paper summarizes some of the work undertaken to date, paying particular attention to methods applicable to on-line control and monitoring systems such as those employed by The National Grid Company plc.

The role of closed ecological systems in carbon cycle modelling

Acquiring a mechanistic understanding of the role of the biotic feedbacks on the links between atmospheric CO2 concentrations and temperature is essential for trustworthy climate predictions. Currently, computer based simulations are the only available tool to estimate the global impact of the biotic feedbacks on future atmospheric CO2 and temperatures. Here we propose an alternative and complementary approaches by using materially closed and energetically open analogue/physical models of the carbon cycle. We argue that there is potential in using a materially closed approach to improve our understanding of the magnitude and sign of many biotic feedbacks, and that recent technological advance make this feasible. We also suggest how such systems could be designed and discuss the advantages and limitations of establishing physical models of the global carbon cycle.

Multiple haptic targets for motion-impaired computer users

Although a number of studies have reported that force feedback gravity wells can improve performance in "point-and-click" tasks, there have been few studies addressing issues surrounding the use of gravity wells for multiple on-screen targets. This paper investigates the performance of users, both with and without motion-impairments, in a "point-and-click" task when an undesired haptic distractor is present. The importance of distractor location is studied explicitly. Results showed that gravity wells can still improve times and error rates, even on occasions when the cursor is pulled into a distractor. The greatest improvement is seen for the most impaired users. In addition to traditional measures such as time and errors, performance is studied in terms of measures of cursor movement along a path. Two cursor measures, angular distribution and temporal components, are proposed and their ability to explain performance differences is explored.

Integrating augmented reality with home systems

Augmented Reality systems overlay computer generated information onto a user's natural senses. Where this additional information is visual, the information is overlaid on the user's natural visual field of view through a head mounted (or “head-up”) display device. Integrated Home Systems provides a network that links every electrical device in the home which provides to a user both control and data transparency across the network.

B-spline neural networks based PID controller for Hammerstein systems

A new PID tuning and controller approach is introduced for Hammerstein systems based on input/output data. A B-spline neural network is used to model the nonlinear static function in the Hammerstein system. The control signal is composed of a PID controller together with a correction term. In order to update the control signal, the multistep ahead predictions of the Hammerstein system based on the B-spline neural networks and the associated Jacobians matrix are calculated using the De Boor algorithms including both the functional and derivative recursions. A numerical example is utilized to demonstrate the efficacy of the proposed approaches.