12 resultados para nonlinear phase matching

em Deakin Research Online - Australia


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Bangladesh exemplifies the complex challenges facing densely populated coastal regions. The
pressures on the country are immense: around 145 million people live within an area of just 145,000 sq-km at
the confluence of three major river systems: the Ganges, the Brahmaputra and the Meghna. While progress
has been made, poverty remains widespread, with around 39% of children under five malnourished. Most of
its land-mass lies below 10m above sea level with considerable areas at sea level, leading to frequent and
prolonged flooding during the monsoons. Sea level rise is leading to more flooding as storm surges rise off
higher sea levels, pushing further inland. Higher sea levels also result in salt-water intrusion into freshwater
coastal aquifers and estuaries, contaminating drinking water and farmland. Warmer ocean waters are also
expected to lead to an increase in the intensity of tropical storms.
Bangladesh depends on the South Asian summer monsoon for most of its rainfall which is expected to
increase, leading to more flooding. Climate scientists are also concerned about the stability of monsoon and
the potential for it to undergo a nonlinear phase shift to a drier regime. Bangladesh faces an additional
hydrological challenge in that the Ganges and Brahmaputra rivers both rise in the Himalaya-Tibetan Plateau
region, where glaciers are melting rapidly. The Intergovernmental Panel on Climate Change (IPCC)
concluded that rapid melting is expected to increase river flows until around the late-2030s, by which time
the glaciers are expected to have shrunk from their 1995 extent of 500,000 sq-km to an expected 100,000 sqkm.
After the 2030s, river flows could drop dramatically, turning the great glacier-fed rivers of Asia into
seasonal monsoon-fed rivers. The IPCC concluded that as a result, water shortages in Asia could affect more
than a billion people by the 2050s. Over the same period, crop yields are expected to decline by up to 30% in
South Asia due to a combination of drought and crop heat stress. Bangladesh is therefore likely to face
substantial challenges in the coming decades.
In order to adequately understand the complex, dynamic, spatial and nonlinear challenges facing Bangladesh,
an integrated model of the system is required. An agent-based model (ABM) permits the dynamic
interactions of the economic, social, political, geographic, environmental and epidemiological dimensions of
climate change impacts and adaptation policies to be integrated via a modular approach. Integrating these
dimensions, including nonlinear threshold events such as mass migrations, or the outbreak of conflicts or
epidemics, is possible to a far greater degree with an ABM than with most other approaches.
We are developing a prototype ABM, implemented in Netlogo, to examine the dynamic impacts on poverty,
migration, mortality and conflict from climate change in Bangladesh from 2001 to 2100. The model employs
GIS and sub-district level census and economic data and a coarse-graining methodology to allow model
statistics to be generated on a national scale from local dynamic interactions. This approach allows a more
realistic treatment of distributed spatial events and heterogeneity across the country. The aim is not to
generate precise predictions of Bangladesh’s evolution, but to develop a framework that can be used for
integrated scenario exploration. This paper represents an initial report on progress on this project. So far the
prototype model has demonstrated the desirability and feasibility of integrating the different dimensions of
the complex adaptive system and, once completed, is intended to be used as the basis for a more detailed
policy-oriented model.

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This paper presents a robust nonlinear controller design for a three-phase grid-connected photovoltaic (PV) system to control the current injected into the grid and the dc-link voltage for extracting maximum power from PV units. The controller is designed based on the partial feedback linearization approach, and the robustness of the proposed control scheme is ensured by considering structured uncertainties within the PV system model. An approach for modeling the uncertainties through the satisfaction of matching conditions is provided. The superiority of the proposed robust controller is demonstrated on a test system through simulation results under different system contingencies along with changes in atmospheric conditions. From the simulation results, it is evident that the robust controller provides excellent performance under various operating conditions. © 2014 IEEE.

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In this paper, a nonlinear backstepping controller is designed for three-phase grid-connected solar photovoltaic (PV) systems to share active and reactive power. A cascaded control structure is considered for the purpose of sharing appropriate amount of power. In this cascaded control structure, the dc-link voltage controller is designed for balancing the power flow within the system and the current controller is designed to shape the grid current into a pure sinusoidal waveform. In order to balance the power flow, it is always essential to maintain a constant voltage across the dc-link capacitor for which an incremental conductance (IC) method is used in this paper. This approach also ensures the operation of solar PV arrays at the maximum power point (MPP) under rapidly changing atmospheric conditions. The proposed current controller is designed to guarantee the current injection into the grid in such a way that the system operates at a power factor other than unity which is essential for sharing active and reactive power. The performance of the proposed backstepping approach is verified on a three-phase grid-connected PV system under different atmospheric conditions. Simulation results show the effectiveness of the proposed control scheme in terms of achieving desired control objectives.

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With an increasing emphasis on the emerging automatic person identification application, biometrics based, especially fingerprint-based identification, is receiving a lot of attention. This research developed an automatic fingerprint recognition system (AFRS) based on a hybrid between minutiae and correlation based techniques to represent and to match fingerprint; it improved each technique individually. It was noticed that, in the hybrid approach, as a result of an improvement of minutiae extraction algorithm in post-process phase that combines the two algorithms, the performance of the minutia algorithm improved. An improvement in the ridge algorithm that used centre point in fingerprint instead of reference point was also observed. Experiments indicate that the hybrid technique performs much better than each algorithm individually.

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Introduction: A nonlinear dynamic systems model has previously been proposed to explain pacing strategies employed during exercise.

Purpose: This study was conducted to examine the pacing strategies used under varying conditions during the cycle phase of an Ironman triathlon.

Methods: The bicycles of six well-trained male triathletes were equipped with SRM power meters set to record power output, cadence, speed, and heart rate. The flat, three-lap, out-and-back cycle course, coupled with relatively consistent wind conditions (17-30 km·h-1), enabled comparisons to be made between three consecutive 60-km laps and relative wind direction (headwind vs tailwind).

Results: Participants finished the cycle phase (180 km) with consistently fast performance times (5 h, 11 ± 2 min; top 10% of all finishers). Average power output (239 ± 25 to 203 ± 20 W), cadence (89 ± 6 to 82 ± 8 rpm), and speed (36.5 ± 0.8 to 33.1 ± 0.8 km·h-1) all significantly decreased with increasing number of laps (P < 0.05). These variables, however, were not significantly different between headwind and tailwind sections. The deviation (SD) in power output and cadence did not change with increasing number of laps; however, the deviations in torque (6.8 ± 1.6 and 5.8 ± 1.3 N·m) and speed (2.1 ± 0.5 and 1.6 ± 0.3 km·h-1) were significantly greater under headwind compared with tailwind conditions, respectively. The median power frequency tended to be lower in headwind (0.0480 ± 0.0083) compared with tailwind (0.0531 ± 0.0101) sections.

Conclusion:
These data show evidence that a nonlinear dynamic pacing strategy is used by well-trained triathletes throughout various segments and conditions of the Ironman cycle phase. Moreover, an increased variation in torque and speed was found in the headwind versus the tailwind condition.

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A multi-resolution technique for matching a stereo pair of images based on translation invariant discrete multi-wavelet transform is presented. The technique uses the well known coarse to fine strategy, involving the calculation of matching points at the coarsest level with consequent refinement up to the finest level. Vector coefficients of the wavelet transform modulus are used as matching features, where modulus maxima defines the shift invariant high-level features (multiscale edges) with phase pointing to the normal of the feature surface. The technique addresses the estimation of optimal corresponding points and the corresponding 2D disparity maps. Illuminative variation that can exist between the perspective views of the same scene is controlled using scale normalization at each decomposition level by dividing the details space coefficients with approximation space and then using normalized correlation. The problem of ambiguity, explicitly, and occlusion, implicitly, is addressed by using a geometric topological refinement procedure and symbolic tagging.

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This paper presents a robust nonlinear distributed controller design for islanded operation of microgrids in order to maintain active and reactive power balance. In this paper, microgrids are considered as inverter-dominated networks integrated with renewable energy sources (RESs) and battery energy storage systems (BESSs), where solar photovoltaic generators act as RESs and plug-in hybrid electric vehicles as BESSs to supply power into the grid. The proposed controller is designed by using partial feedback linearization and the robustness of this control scheme is ensured by considering structured uncertainties within the RESs and BESSs. An approach for modeling the uncertainties through the satisfaction of matching conditions is also provided in this paper. The proposed distributed control scheme requires information from local and neighboring generators to communicate with each other and the communication among RESs, BESSs, and control centers is developed by using the concept of the graph theory. Finally, the performance of the proposed robust controller is demonstrated on a test microgrid and simulation results indicate the superiority of the proposed scheme under different operating conditions as compared to a linear-quadratic-regulator-based controller.

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The unloading behavior was compared for three different steel grades: a dual-phase steel, a transformation-induced plasticity steel, and a twinning-induced plasticity steel. Steels that harden by phase transformation or deformation twinning exhibited a smaller component of microplastic strain during unloading and a smaller reduction in the chord modulus compared to the conventional hardening steel. As a result, unloading is closer to pure elastic unloading when the TRIP effect or TWIP effect is active.

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Steam-valving and excitation systems play an important role to maintain the transient stability of power systems with synchronous generators when power systems are subjected to large disturbances and sudden load changes. This paper presents a nonlinear adaptive backstepping approach for controlling excitation and steam-valving systems of synchronous generators. In this paper, the proposed excitation and steam-valving controllers are designed in a coordinated manner so that they can work under several and most severe operating conditions. Both excitation and steam-valving controllers are designed by considering some critical parameters as unknown. The effectiveness of the proposed coordinated control scheme is evaluated on a single machine infinite bus system under different operating conditions such as load changes and three-phase short circuit faults at the generator terminal. Finally, performance of the proposed scheme is compared to that of a similar nonlinear adaptive backstepping excitation controller without any coordination and simulation results demonstrate the superiority of the proposed one.

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n this paper, the design of a nonlinear excitation control of a synchronous generator is presented where the generator is connected to a single machine infinite bus (SMIB) system. An adaptive backstepping method is used to design the excitation controller with an objective of enhancing the overall dynamic stability of the SMIB system under different contingencies. In this paper, two types of contingencies are considered- i) unknown parameters and physical quantities during the controller design process and ii) controller performance evaluation under different system configurations such as three-phase short circuit faults. The adaption law, which is mainly based on the formulation of Lyapunov function, is used to estimate the unknown parameters which guarantee the convergence of different physical quantities of synchronous generators, e.g., the relative speed, terminal voltage, etc. The effectiveness of the proposed scheme is evaluated under different system configurations as mentioned in the second contingency and compared to that of an existing adaptive backstepping controller and a conventional power system stabilizer (PSS). Simulation results demonstrate the superiority of the proposed control scheme over the existing controllers.

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This paper presents a nonlinear adaptive excitation control scheme to enhance the dynamic stability of multimachine power systems. The proposed controller is designed based on the adaptive backstepping technique where the mechanical power input to the generators and the damping coefficient of each generator are considered as unknown. These unknown quantities are estimated through the adaption laws. The adaption laws are obtained from the formulation of Lyapunov functions which guarantee the convergence of different physical quantities of generators such as the relative speed, terminal voltage, and electrical power output. The proposed scheme is evaluated by applying a three-phase short-circuit fault at one of the key transmission lines in an 11-bus test power system and compared with an existing backstepping controller and conventional power system stabilizer (CPSS). Simulation results show that the proposed scheme is much more effective than existing controllers.

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This paper presents a nonlinear controller design for vehicle-to-grid (V2G) systems with LCL output filters. The V2G systems are modeled with LCL output filters in order to eliminate harmonics for improving power qualities and the nonlinear controller is designed based on the feedback linearization. The feasibility of using the appropriate feedback linearization approaches, either partial or exact, is also investigated through the feedback linearizability of V2G systems. In this paper, partial feedback linearization is used to design the controller with a capability of sharing both active and reactive power in V2G systems. The performance of the proposed controller controller is evaluated on a single-phase full-bridge converter-based V2G system with an LCL output filter and compared to that of without any filter. Simulation results clearly demonstrate the harmonic elimination capabilities of the proposed V2G structure with the proposed control scheme.