177 resultados para closed-loop nash equilibrium

em Queensland University of Technology - ePrints Archive


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This paper proposes a method for designing set-point regulation controllers for a class of underactuated mechanical systems in Port-Hamiltonian System (PHS) form. A new set of potential shape variables in closed loop is proposed, which can replace the set of open loop shape variables-the configuration variables that appear in the kinetic energy. With this choice, the closed-loop potential energy contains free functions of the new variables. By expressing the regulation objective in terms of these new potential shape variables, the desired equilibrium can be assigned and there is freedom to reshape the potential energy to achieve performance whilst maintaining the PHS form in closed loop. This complements contemporary results in the literature, which preserve the open-loop shape variables. As a case study, we consider a robotic manipulator mounted on a flexible base and compensate for the motion of the base while positioning the end effector with respect to the ground reference. We compare the proposed control strategy with special cases that correspond to other energy shaping strategies previously proposed in the literature.

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In this paper, a fixed-switching-frequency closed-loop modulation of a voltage-source inverter (VSI), upon the digital implementation of the modulation process, is analyzed and characterized. The sampling frequency of the digital processor is considered as an integer multiple of the modulation switching frequency. An expression for the determination of the modulation design parameter is developed for smooth modulation at a fixed switching frequency. The variation of the sampling frequency, switching frequency, and modulation index has been analyzed for the determination of the switching condition under closed loop. It is shown that the switching condition determined based on the continuous-time analysis of the closed-loop modulation will ensure smooth modulation upon the digital implementation of the modulation process. However, the stability properties need to be tested prior to digital implementation as they get deteriorated at smaller sampling frequencies. The closed-loop modulation index needs to be considered maximum while determining the design parameters for smooth modulation. In particular, a detailed analysis has been carried out by varying the control gain in the sliding-mode control of a two-level VSI. The proposed analysis of the closed-loop modulation of the VSI has been verified for the operation of a distribution static compensator. The theoretical results are validated experimentally on both single- and three-phase systems.

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This paper describes a vision-based airborne collision avoidance system developed by the Australian Research Centre for Aerospace Automation (ARCAA) under its Dynamic Sense-and-Act (DSA) program. We outline the system architecture and the flight testing undertaken to validate the system performance under realistic collision course scenarios. The proposed system could be implemented in either manned or unmanned aircraft, and represents a step forward in the development of a “sense-and-avoid” capability equivalent to human “see-and-avoid”.

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In this paper, a model-predictive control (MPC) method is detailed for the control of nonlinear systems with stability considerations. It will be assumed that the plant is described by a local input/output ARX-type model, with the control potentially included in the premise variables, which enables the control of systems that are nonlinear in both the state and control input. Additionally, for the case of set point regulation, a suboptimal controller is derived which has the dual purpose of ensuring stability and enabling finite-iteration termination of the iterative procedure used to solve the nonlinear optimization problem that is used to determine the control signal.

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The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.

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Textile waste is a significant contributor to landfill yet the majority of textiles can be recycled, allowing for the energy and fibre to be reclaimed. This chapter examines the open-loop and closed loop recycling of textile products with particular reference to the fashion and apparel context. It describes the fibres used within apparel, the current mechanical and chemical methods for textile recycling, LCA findings for each method, and applications within apparel for each. Barriers for more effective recycling include ease of integration into existing textile and apparel design methods as well as coordinated collection of post-consumer waste. The chapter concludes with a discussion of innovations that point to future trends in both open-loop and closed-loop recycling within the apparel industry.

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Mobile applications are being increasingly deployed on a massive scale in various mobile sensor grid database systems. With limited resources from the mobile devices, how to process the huge number of queries from mobile users with distributed sensor grid databases becomes a critical problem for such mobile systems. While the fundamental semantic cache technique has been investigated for query optimization in sensor grid database systems, the problem is still difficult due to the fact that more realistic multi-dimensional constraints have not been considered in existing methods. To solve the problem, a new semantic cache scheme is presented in this paper for location-dependent data queries in distributed sensor grid database systems. It considers multi-dimensional constraints or factors in a unified cost model architecture, determines the parameters of the cost model in the scheme by using the concept of Nash equilibrium from game theory, and makes semantic cache decisions from the established cost model. The scenarios of three factors of semantic, time and locations are investigated as special cases, which improve existing methods. Experiments are conducted to demonstrate the semantic cache scheme presented in this paper for distributed sensor grid database systems.

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This paper reviews some recent results in motion control of marine vehicles using a technique called Interconnection and Damping Assignment Passivity-based Control (IDA-PBC). This approach to motion control exploits the fact that vehicle dynamics can be described in terms of energy storage, distribution, and dissipation, and that the stable equilibrium points of mechanical systems are those at which the potential energy attains a minima. The control forces are used to transform the closed-loop dynamics into a port-controlled Hamiltonian system with dissipation. This is achieved by shaping the energy-storing characteristics of the system, modifying its interconnection structure (how the energy is distributed), and injecting damping. The end result is that the closed-loop system presents a stable equilibrium (hopefully global) at the desired operating point. By forcing the closed-loop dynamics into a Hamiltonian form, the resulting total energy function of the system serves as a Lyapunov function that can be used to demonstrate stability. We consider the tracking and regulation of fully actuated unmanned underwater vehicles, its extension to under-actuated slender vehicles, and also manifold regulation of under-actuated surface vessels. The paper is concluded with an outlook on future research.

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In this paper, we address the problem of stabilisation of robots subject to nonholonommic constraints and external disturbances using port-Hamiltonian theory and smooth time-invariant control laws. This should be contrasted with the commonly used switched or time-varying laws. We propose a control design that provides asymptotic stability of an manifold (also called relative equilibria)-due to the Brockett condition this is the only type of stabilisation possible using smooth time-invariant control laws. The equilibrium manifold can be shaped to certain extent to satisfy specific control objectives. The proposed control law also incorporates integral action, and thus the closed-loop system is robust to unknown constant disturbances. A key step in the proposed design is a change of coordinates not only in the momentum, but also in the position vector, which differs from coordinate transformations previously proposed in the literature for the control of nonholonomic systems. The theoretical properties of the control law are verified via numerical simulation based on a robotic ground vehicle model with differential traction wheels and non co-axial centre of mass and point of contact.

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In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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In this thesis, a new technique has been developed for determining the composition of a collection of loads including induction motors. The application would be to provide a representation of the dynamic electrical load of Brisbane so that the ability of the power system to survive a given fault can be predicted. Most of the work on load modelling to date has been on post disturbance analysis, not on continuous on-line models for loads. The post disturbance methods are unsuitable for load modelling where the aim is to determine the control action or a safety margin for a specific disturbance. This thesis is based on on-line load models. Dr. Tania Parveen considers 10 induction motors with different power ratings, inertia and torque damping constants to validate the approach, and their composite models are developed with different percentage contributions for each motor. This thesis also shows how measurements of a composite load respond to normal power system variations and this information can be used to continuously decompose the load continuously and to characterize regarding the load into different sizes and amounts of motor loads.

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This paper is concerned with choosing image features for image based visual servo control and how this choice influences the closed-loop dynamics of the system. In prior work, image features tend to be chosen on the basis of image processing simplicity and noise sensitivity. In this paper we show that the choice of feature directly influences the closed-loop dynamics in task-space. We focus on the depth axis control of a visual servo system and compare analytically various approaches that have been reported recently in the literature. The theoretical predictions are verified by experiment.

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This paper considers the question of designing a fully image based visual servo control for a dynamic system. The work is motivated by the ongoing development of image based visual servo control of small aerial robotic vehicles. The observed targets considered are coloured blobs on a flat surface to which the normal direction is known. The theoretical framework is directly applicable to the case of markings on a horizontal floor or landing field. The image features used are a first order spherical moment for position and an image flow measurement for velocity. A fully non-linear adaptive control design is provided that ensures global stability of the closed-loop system. © 2005 IEEE.

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This paper examines the feasibility of automation of dragline bucket excavators used to strip over-burden from open cut mines. In particular the automatic control of bucket carry angle and bucket trajectory are addressed. Open-loop dynamics of a 1:20 scale model dragline bucket are identified, through measurement of frequency response between carry angle and drag motor input voltage. A strategy for automatic control of carry angle is devised and implemented using bucket angle and rate feedback. System compensation and tuning are explained and closed loop frequency and time responses are measured.

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One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.