872 resultados para Discontinuous dynamic systems


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We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of system identification is more robust than finding point estimates of a parametric function representation. Our principled filtering/smoothing approach for GP dynamic systems is based on analytic moment matching in the context of the forward-backward algorithm. Our numerical evaluations demonstrate the robustness of the proposed approach in situations where other state-of-the-art Gaussian filters and smoothers can fail. © 2011 IEEE.

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This paper presents an adaptive Sequential Monte Carlo approach for real-time applications. Sequential Monte Carlo method is employed to estimate the states of dynamic systems using weighted particles. The proposed approach reduces the run-time computation complexity by adapting the size of the particle set. Multiple processing elements on FPGAs are dynamically allocated for improved energy efficiency without violating real-time constraints. A robot localisation application is developed based on the proposed approach. Compared to a non-adaptive implementation, the dynamic energy consumption is reduced by up to 70% without affecting the quality of solutions. © 2012 IEEE.

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Urbanisation is the great driving force of the twenty-first century. Cities are associated with both productivity and creativity, and the benefits offered by closely connected and high density living and working contribute to sustainability. At the same time, cities need extensive infrastructure – like water, power, sanitation and transportation systems – to operate effectively. Cities therefore comprise multiple components, forming both static and dynamic systems that are interconnected directly and indirectly on a number of levels, all forming the backdrop for the interaction of people and processes. Bringing together large numbers of people and complex products in rich interactions can lead to vulnerability from hazards, threats and even trends, whether natural hazards, epidemics, political upheaval, demographic changes, economic instability and/or mechanical failures; The key to countering vulnerability is the identification of critical systems and clear understanding of their interactions and dependencies. Critical systems can be assessed methodically to determine the implications of their failure and their interconnectivities with other systems to identify options. The overriding need is to support resilience – defined here as the degree to which a system or systems can continue to function effectively in a changing environment. Cities need to recognise the significance of devising adaptation strategies and processes to address a multitude of uncertainties relating to climate, economy, growth and demography. In this paper we put forward a framework to support cities in understanding the hazards, threats and trends that can make them vulnerable to unexpected changes and unpredictable shocks. The framework draws on an asset model of the city, in which components that contribute to resilience include social capital, economic assets, manufactured assets, and governance. The paper reviews the field, and draws together an overarching framework intended to help cities plan a robust trajectory towards increased resilience through flexibility, resourcefulness and responsiveness. It presents some brief case studies demonstrating the applicability of the proposed framework to a wide variety of circumstances.

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Passive steering systems have been used for some years to control the steering of trailer axles on articulated vehicles. These normally use a 'command steer' control strategy, which is designed to work well in steady-state circles at low speeds, but which generates inappropriate steer angles during transient low-speed maneuvers and at high speeds. In this paper, 'active' steering control strategies are developed for articulated heavy goods vehicles. These aim to achieve accurate path following for tractor and trailer, for all paths and all normal vehicle speeds, in the presence of external disturbances. Controllers are designed to implement the path-following strategies at low and high speeds, whilst taking into account the complexities and practicalities of articulated vehicles. At low speeds, the articulation and steer angles on articulated heavy goods vehicles are large and small-angle approximations are not appropriate. Hence, nonlinear controllers based on kinematics are required. But at high-speeds, the dynamic stability of control system is compromised if the kinematics-based controllers remain active. This is because a key state of the system, the side-slip characteristics of the trailer, exhibits a sign-change with increasing speeds. The low and high speed controllers are blended together using a speed-dependent gain, in the intermediate speed range. Simulations are conducted to compare the performance of the new steering controllers with conventional vehicles (with unsteered drive and trailer axles) and with vehicles with command steer controllers on their trailer axles. The simulations show that active steering has the potential to improve significantly the directional performance of articulated vehicles for a wide range of conditions, throughout the speed range. © VC 2013 by ASME.

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The problem of calculating the minimum lap or maneuver time of a nonlinear vehicle, which is linearized at each time step, is formulated as a convex optimization problem. The formulation provides an alternative to previously used quasi-steady-state analysis or nonlinear optimization. Key steps are: the use of model predictive control; expressing the minimum time problem as one of maximizing distance traveled along the track centerline; and linearizing the track and vehicle trajectories by expressing them as small displacements from a fixed reference. A consequence of linearizing the vehicle dynamics is that nonoptimal steering control action can be generated, but attention to the constraints and the cost function minimizes the effect. Optimal control actions and vehicle responses for a 90 deg bend are presented and compared to the nonconvex nonlinear programming solution. Copyright © 2013 by ASME.

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Urbanisation is one of the great driving forces of the twenty-first century. Cities generate both productivity and creativity, and the benefits offered by high-density living and working contribute to sustainability. Cities comprise multiple components, forming both static and dynamic systems that are interconnected directly and indirectly on a number of levels. Bringing together large numbers of people within a complex system can lead to vulnerability from a wide range of hazards, threats and trends. The key to reducing this vulnerability is the identification of critical systems and determination of the implications of their failure and their interconnectivities with other systems. One emerging approach to these challenges focuses on building resilience – defined here as the degree to which a system can continue to function effectively in a changing environment. This paper puts forward a framework designed to help engineers, planners and designers to support cities in understanding the hazards, threats and trends that can make them vulnerable, and identify focus areas for building resilience into the systems, which allow it to function and prosper. Four case studies of cities whose resilience was tested by recent extreme weather events are presented, seeking to demonstrate the application of the proposed framework.

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A high-speed path-following controller for long combination vehicles (LCVs) was designed and implemented on a test vehicle consisting of a rigid truck towing a dolly and a semitrailer. The vehicle was driven through a 3.5 m wide lane change maneuver at 80 km/h. The axles of the dolly and trailer were steered actively by electrically-controlled hydraulic actuators. Substantial performance benefits were recorded compared with the unsteered vehicle. For the best controller weightings, performance improvements relative to unsteered case were: lateral tracking error 75% reduction, rearward amplification (RA) of lateral acceleration 18% reduction, and RA of yaw rate 37% reduction. This represents a substantial improvement in stability margins. The system was found to work well in conjunction with the braking-based stability control system of the towing vehicle with no negative interaction effects being observed. In all cases, the stability control system and the steering system improved the yaw stability of the combination. © 2014 by ASME.

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Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid. © 2013 American Chemical Society.

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本文用 Petri 网的一个子类——时间事件图对流水车间型和作业车间型的柔性制造系统(FMS)建模并进行理论分析,给出了可行排序的判定条件及系统中托盘数量配置与系统生产率的关系,对系统的主要性能指标,如生产周期、工件驻留时间、在制品库存等给出了定量描述.这些结果为系统的设计和运行提供了理论依据.

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自动生产线和柔性制造系统是典型的离散事件动态系统,近几年在控制理论界受到极大重视。本文首先对自动生产线的建模与分析的研究概况做了综述,重点放在排队网络模型。然后介绍了柔性制造系统的管理与控制问题。

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Based on the study of sequence stratigraphy, modern sedimentary, basin analysis, and petroleum system in Gubei depression, this paper builds high resolution sequence stratigraphic structure, sedimentary system, sandbody distribution, the effect of tectonic in sequence and sedimentary system evolution and model of tectonic-lithofacies. The pool formation mechanism of subtle trap is developed. There are some conclusions and views as follows. 1.With the synthetic sequence analysis of drilling, seismic, and well log, the highly resolution sequence structure is build in Gubei depression. They are divided two secondary sequences and seven three-order sequences in Shahejie formation. They are include 4 kinds of system traces and 7 kinds of sedimentary systems which are alluvial fan, under water fan, alluvial fan and fan-delta, fan-delta, lacustrine-fan, fluvial-delta-turbidite, lakeshore beach and bar, and deep lake system. Sandbody distribution is show base on third order sequence. 2.Based on a lot of experiment and well log, it is point out that there are many types of pore in reservoir with the styles of corrosion pore, weak cementing, matrix cementing, impure filling, and 7 kinds of diagenetic facies. These reservoirs are evaluated by lateral and profile characteristics of diagenetic facies and reservoir properties. 3.The effect of simultaneous faulting on sediment process is analyzed from abrupt slope, gentle slope, and hollow zone. The 4 kinds of tectonic lithofacies models are developed in several periods in Gubei depression; the regional distribution of subtle trap is predicted by hydro accumulation characteristics of different tectonic lithofacies. 4.There are 4 types of compacting process, which are normal compaction, abnormal high pressure, abnormal low pressure and complex abnormal pressure. The domain type is normal compaction that locates any area of depression, but normal high pressure is located only deep hollow zone (depth more than 3000m), abnormal low pressures are located gentle slope and faulted abrupt slope (depth between 1200~2500m). 5.Two types dynamic systems of pool formation (enclosed and partly enclosed system) are recognized. They are composed by which source rocks are from Es3 and Es4, cap rocks are deep lacustrine shale of Esl and Es3, and sandstone reservoirs are 7 kinds of sedimentary system in Es3 and Es4. According to theory of petroleum system, two petroleum systems are divided in Es3 and Es4 of Gubei depression, which are high or normal pressure self-source system and normal or low pressure external-source system. 6.There are 3 kinds of combination model of pool formation, the first is litholgical pool of inner depression (high or normal pressure self-source type), the second is fault block or fault nose pool in marginal of depression (normal type), the third is fault block-lithological pool of central low lifted block (high or normal pressure type). The lithological pool is located central of depression, other pool are located gentle or abrupt slope that are controlled by lithological, faulting, unconfirmed. 7.This paper raise a new technique and process of exploration subtle trap which include geological modeling, coring description and logging recognition, and well log constrained inversion. These are composed to method and theory of predicting subtle trap. Application these methods and techniques, 6 hydro objects are predicted in three zone of depression.

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This paper explores automating the qualitative analysis of physical systems. It describes a program, called PLR, that takes parameterized ordinary differential equations as input and produces a qualitative description of the solutions for all initial values. PLR approximates intractable nonlinear systems with piecewise linear ones, analyzes the approximations, and draws conclusions about the original systems. It chooses approximations that are accurate enough to reproduce the essential properties of their nonlinear prototypes, yet simple enough to be analyzed completely and efficiently. It derives additional properties, such as boundedness or periodicity, by theoretical methods. I demonstrate PLR on several common nonlinear systems and on published examples from mechanical engineering.