543 resultados para Control framework


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This dissertation is based on theoretical study and experiments which extend geometric control theory to practical applications within the field of ocean engineering. We present a method for path planning and control design for underwater vehicles by use of the architecture of differential geometry. In addition to the theoretical design of the trajectory and control strategy, we demonstrate the effectiveness of the method via the implementation onto a test-bed autonomous underwater vehicle. Bridging the gap between theory and application is the ultimate goal of control theory. Major developments have occurred recently in the field of geometric control which narrow this gap and which promote research linking theory and application. In particular, Riemannian and affine differential geometry have proven to be a very effective approach to the modeling of mechanical systems such as underwater vehicles. In this framework, the application of a kinematic reduction allows us to calculate control strategies for fully and under-actuated vehicles via kinematic decoupled motion planning. However, this method has not yet been extended to account for external forces such as dissipative viscous drag and buoyancy induced potentials acting on a submerged vehicle. To fully bridge the gap between theory and application, this dissertation addresses the extension of this geometric control design method to include such forces. We incorporate the hydrodynamic drag experienced by the vehicle by modifying the Levi-Civita affine connection and demonstrate a method for the compensation of potential forces experienced during a prescribed motion. We present the design method for multiple different missions and include experimental results which validate both the extension of the theory and the ability to implement control strategies designed through the use of geometric techniques. By use of the extension presented in this dissertation, the underwater vehicle application successfully demonstrates the applicability of geometric methods to design implementable motion planning solutions for complex mechanical systems having equal or fewer input forces than available degrees of freedom. Thus, we provide another tool with which to further increase the autonomy of underwater vehicles.

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Effective strategies for the design of effi cient and environmentally sensitive buildings require a close collaboration between architects and engineers in the design of the building shell and environmental control systems at the outset of projects. However, it is often not practical for engineers to be involved early on in the design process. It is therefore essential that architects be able to perform preliminary energy analyses to evaluate their proposed designs prior to the major building characteristics becoming fi xed. Subsequently, a need exists for a simplifi ed energy design tool for architects. This paper discusses the limitations of existing analysis software in supporting early design explorations and proposes a framework for the development of a tool that provides decision support by permitting architects to quickly assess the performance of design alternatives.

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This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

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Recent perceptual-motor studies have revealed variations in learning trajectories of novices. Despite such observation, relatively little attention has been paid to studying individual differences in experienced performers’ perceptual-motor behaviors. The present study examined individual differences for a visual anticipation task. Experienced association football goalkeepers attempted to intercept penalty kicks taken with deceptive and non-deceptive kicking actions. Data revealed that differences in the action capabilities of goalkeepers affected the timing and accuracy of movement response behaviors. Faster goalkeepers tended to wait until later before initiating movement in comparison with slower goalkeepers. The study of affordances in sport environments offers a theoretical framework with which to overcome some of the reported methodological limitations in the visual anticipation literature.

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The ultimate goal of an authorisation system is to allocate each user the level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting because on one hand employees need enough access to perform their tasks, while on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally through carelessness, losing the information or being socially engineered to give access to an adversary. With the goal of developing a more dynamic authorisation model, we have adopted a game theoretic framework to reason about the factors that may affect users’ likelihood to misuse a permission at the time of an access decision. Game theory provides a useful but previously ignored perspective in authorisation theory: the notion of the user as a self-interested player who selects among a range of possible actions depending on their pay-offs.

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Linking real-time schedulability directly to the Quality of Control (QoC), the ultimate goal of a control system, a hierarchical feedback QoC management framework with the Fixed Priority (FP) and the Earliest-Deadline-First (EDF) policies as plug-ins is proposed in this paper for real-time control systems with multiple control tasks. It uses a task decomposition model for continuous QoC evaluation even in overload conditions, and then employs heuristic rules to adjust the period of each of the control tasks for QoC improvement. If the total requested workload exceeds the desired value, global adaptation of control periods is triggered for workload maintenance. A sufficient stability condition is derived for a class of control systems with delay and period switching of the heuristic rules. Examples are given to demonstrate the proposed approach.

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A trend in design and implementation of modern industrial automation systems is to integrate computing, communication and control into a unified framework at different levels of machine/factory operations and information processing. These distributed control systems are referred to as networked control systems (NCSs). They are composed of sensors, actuators, and controllers interconnected over communication networks. As most of communication networks are not designed for NCS applications, the communication requirements of NCSs may be not satisfied. For example, traditional control systems require the data to be accurate, timely and lossless. However, because of random transmission delays and packet losses, the control performance of a control system may be badly deteriorated, and the control system rendered unstable. The main challenge of NCS design is to both maintain and improve stable control performance of an NCS. To achieve this, communication and control methodologies have to be designed. In recent decades, Ethernet and 802.11 networks have been introduced in control networks and have even replaced traditional fieldbus productions in some real-time control applications, because of their high bandwidth and good interoperability. As Ethernet and 802.11 networks are not designed for distributed control applications, two aspects of NCS research need to be addressed to make these communication networks suitable for control systems in industrial environments. From the perspective of networking, communication protocols need to be designed to satisfy communication requirements for NCSs such as real-time communication and high-precision clock consistency requirements. From the perspective of control, methods to compensate for network-induced delays and packet losses are important for NCS design. To make Ethernet-based and 802.11 networks suitable for distributed control applications, this thesis develops a high-precision relative clock synchronisation protocol and an analytical model for analysing the real-time performance of 802.11 networks, and designs a new predictive compensation method. Firstly, a hybrid NCS simulation environment based on the NS-2 simulator is designed and implemented. Secondly, a high-precision relative clock synchronization protocol is designed and implemented. Thirdly, transmission delays in 802.11 networks for soft-real-time control applications are modeled by use of a Markov chain model in which real-time Quality-of- Service parameters are analysed under a periodic traffic pattern. By using a Markov chain model, we can accurately model the tradeoff between real-time performance and throughput performance. Furthermore, a cross-layer optimisation scheme, featuring application-layer flow rate adaptation, is designed to achieve the tradeoff between certain real-time and throughput performance characteristics in a typical NCS scenario with wireless local area network. Fourthly, as a co-design approach for both a network and a controller, a new predictive compensation method for variable delay and packet loss in NCSs is designed, where simultaneous end-to-end delays and packet losses during packet transmissions from sensors to actuators is tackled. The effectiveness of the proposed predictive compensation approach is demonstrated using our hybrid NCS simulation environment.

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This paper considers the problem of building a software architecture for a human-robot team. The objective of the team is to build a multi-attribute map of the world by performing information fusion. A decentralized approach to information fusion is adopted to achieve the system properties of scalability and survivability. Decentralization imposes constraints on the design of the architecture and its implementation. We show how a Component-Based Software Engineering approach can address these constraints. The architecture is implemented using Orca – a component-based software framework for robotic systems. Experimental results from a deployed system comprised of an unmanned air vehicle, a ground vehicle, and two human operators are presented. A section on the lessons learned is included which may be applicable to other distributed systems with complex algorithms. We also compare Orca to the Player software framework in the context of distributed systems.

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The elastic task model, a significant development in scheduling of real-time control tasks, provides a mechanism for flexible workload management in uncertain environments. It tells how to adjust the control periods to fulfill the workload constraints. However, it is not directly linked to the quality-of-control (QoC) management, the ultimate goal of a control system. As a result, it does not tell how to make the best use of the system resources to maximize the QoC improvement. To fill in this gap, a new feedback scheduling framework, which we refer to as QoC elastic scheduling, is developed in this paper for real-time process control systems. It addresses the QoC directly through embedding both the QoC management and workload adaptation into a constrained optimization problem. The resulting solution for period adjustment is in a closed-form expressed in QoC measurements, enabling closed-loop feedback of the QoC to the task scheduler. Whenever the QoC elastic scheduler is activated, it improves the QoC the most while still meeting the system constraints. Examples are given to demonstrate the effectiveness of the QoC elastic scheduling.

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It is not uncommon for enterprises today to be faced with the demand to integrate and incor- porate many different and possibly heterogeneous systems which are generally independently designed and developed, to allow seamless access. In effect, the integration of these systems results in one large whole system that must be able, at the same time, to maintain the local autonomy and to continue working as an independent entity. This problem has introduced a new distributed architecture called federated systems. The most challenging issue in federated systems is to find answers for the question of how to efficiently cooperate while preserving their autonomous characteristic, especially the security autonomy. This thesis intends to address this issue. The thesis reviews the evolution of the concept of federated systems and discusses the organisational characteristics as well as remaining security issues with the existing approaches. The thesis examines how delegation can be used as means to achieve better security, especially authorisation while maintaining autonomy for the participating member of the federation. A delegation taxonomy is proposed as one of the main contributions. The major contribution of this thesis is to study and design a mechanism to support dele- gation within and between multiple security domains with constraint management capability. A novel delegation framework is proposed including two modules: Delegation Constraint Man- agement module and Policy Management module. The first module is designed to effectively create, track and manage delegation constraints, especially for delegation processes which require re-delegation (indirect delegation). The first module employs two algorithms to trace the root authority of a delegation constraint chain and to prevent the potential conflict when creating a delegation constraint chain if necessary. The first module is designed for conflict prevention not conflict resolution. The second module is designed to support the first module via the policy comparison capability. The major function of this module is to provide the delegation framework the capability to compare policies and constraints (written under the format of a policy). The module is an extension of Lin et al.'s work on policy filtering and policy analysis. Throughout the thesis, some case studies are used as examples to illustrate the discussed concepts. These two modules are designed to capture one of the most important aspects of the delegation process: the relationships between the delegation transactions and the involved constraints, which are not very well addressed by the existing approaches. This contribution is significant because the relationships provide information to keep track and en- force the involved delegation constraints and, therefore, play a vital role in maintaining and enforcing security for transactions across multiple security domains.

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We develop and test a theoretically-based integrative framework of key proximal factors (orientation, pressure, and control) that helps to explain the effects of more general factors (the organisation's strategy, structure, and environment) on intentions to adopt an innovation one year later. Senior managers from 134 organizations were surveyed and confirmatory factor analyses showed that these hypothesized core factors provided a good fit to the data, indicating that our framework can provide a theoretical base to the previous, largely a theoretical, literature. Moreover, in a subgroup of 63 organizations, control mediated the effects of organizational strategy and centralisation on organizational innovation adoption intentions one year later. We suggest this model of core factors enables researchers to understand why certain variables are important to organisational innovation adoption and promotes identification of fertile research areas around orientation, pressure and control, and it enables managers to focus on the most proximal triggers for increasing innovation adoption.

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This workshop provides an ergonomic framework and design rules for the design of automotive controls, considering anthropometric design, physiologic design, biomechanic design and information design.

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Whereas many good examples can be found of the study of urban morphology informing the design of new residential areas in Europe, it is much more difficult to find examples relating to other land uses and outside of Europe. This paper addresses a particular issue, the control and coordination of large and complex development schemes within cities, and, in doing so, considers commercial and mixed-use schemes outside of Europe. It is argued that urban morphology has much to offer for both the design of such development and its implementation over time. Firstly, lessons are drawn from the work of Krier and Rossi in Berlin, the form-based guidance developed in Chelmsford, UK, and the redesign and coordination of the Melrose Arch project in Johannesburg, SA. A recent development at Boggo Road in Brisbane, Australia, is then subjected to a more detailed examination. It is argued that the scheme has been unsatisfactory in terms of both design and implementation. An alternative framework based on historical morphological studies is proposed that would overcome these deficiencies. It is proposed that this points the way to a general approach that could be incorporated within the planning process internationally.

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This article provides a tutorial introduction to visual servo control of robotic manipulators. Since the topic spans many disciplines our goal is limited to providing a basic conceptual framework. We begin by reviewing the prerequisite topics from robotics and computer vision, including a brief review of coordinate transformations, velocity representation, and a description of the geometric aspects of the image formation process. We then present a taxonomy of visual servo control systems. The two major classes of systems, position-based and image-based systems, are then discussed in detail. Since any visual servo system must be capable of tracking image features in a sequence of images, we also include an overview of feature-based and correlation-based methods for tracking. We conclude the tutorial with a number of observations on the current directions of the research field of visual servo control.

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Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.