313 resultados para ANPSP control model


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This paper presents a distributed communication based active power curtailment (APC) control scheme for grid connected photovoltaic (PV) systems to address voltage rise. A simple distribution feeder model is presented and simulated using MATLAB. The resource sharing based control scheme proposed is shown to be effective at reducing voltage rise during times of peak generation and low load. Simulations also show the even distribution of APC using simple communications. Simulations demonstrate the versatility of the proposed control method under major communication failure conditions. Further research may lead to possible applications in coordinated electric vehicle (EV) charging.

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The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

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This thesis presents novel techniques for addressing the problems of continuous change and inconsistencies in large process model collections. The developed techniques treat process models as a collection of fragments and facilitate version control, standardization and automated process model discovery using fragment-based concepts. Experimental results show that the presented techniques are beneficial in consolidating large process model collections, specifically when there is a high degree of redundancy.

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Temporary Traffic Control Plans (TCP’s), which provide construction phasing to maintain traffic during construction operations, are integral component of highway construction project design. Using the initial design, designers develop estimated quantities for the required TCP devices that become the basis for bids submitted by highway contractors. However, actual as-built quantities are often significantly different from the engineer’s original estimate. The total cost of TCP phasing on highway construction projects amounts to 6–10% of the total construction cost. Variations between engineer estimated quantities and final quantities contribute to reduced cost control, increased chances of cost related litigations, and bid rankings and selection. Statistical analyses of over 2000 highway construction projects were performed to determine the sources of variation, which later were used as the basis of development for an automated-hybrid prediction model that uses multiple regressions and heuristic rules to provide accurate TCP quantities and costs. The predictive accuracy of the model developed was demonstrated through several case studies.

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Motion control systems have a significant impact on the performance of ships and marine structures allowing them to perform tasks in severe sea states and during long periods of time. Ships are designed to operate with adequate reliability and economy, and in order to achieve this, it is essential to control the motion. For each type of ship and operation performed (transit, landing a helicopter, fishing, deploying and recovering loads, etc.), there are not only desired motion settings, but also limits on the acceptable (undesired) motion induced by the environment. The task of a ship motion control system is therefore to act on the ship so it follows the desired motion as closely as possible. This book provides an introduction to the field of ship motion control by studying the control system designs for course-keeping autopilots with rudder roll stabilisation and integrated rudder-fin roll stabilisation. These particular designs provide a good overview of the difficulties encountered by designers of ship motion control systems and, therefore, serve well as an example driven introduction to the field. The idea of combining the control design of autopilots with that of fin roll stabilisers, and the idea of using rudder induced roll motion as a sole source of roll stabilisation seems to have emerged in the late 1960s. Since that time, these control designs have been the subject of continuous and ongoing research. This ongoing interest is a consequence of the significant bearing that the control strategy has on the performance and the issues associated with control system design. The challenges of these designs lie in devising a control strategy to address the following issues: underactuation, disturbance rejection with a non minimum phase system, input and output constraints, model uncertainty, and large unmeasured stochastic disturbances. To date, the majority of the work reported in the literature has focused strongly on some of the design issues whereas the remaining issues have been addressed using ad hoc approaches. This has provided an additional motivation for revisiting these control designs and looking at the benefits of applying a contemporary design framework, which can potentially address the majority of the design issues.

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This chapter presents a novel control strategy for trajectory tracking of underwater marine vehicles that are designed using port-Hamiltonian theory. A model for neutrally buoyant underwater vehicles is formulated as a PHS, and then the tracking controller is designed for the horizontal plane-surge, sway and yaw. The control design is done by formulating the error dynamics as a set-point regulation port-Hamiltonian control problem. The control design is formulated in two steps. In the first step, a static-feedback tracking controller is designed, and the second step integral action is added. The global asymptotic stability of the closed loop system is proved and the performance of the controller is illustrated using a model of an open-frame offshore underwater vehicle.

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In Chapters 1 through 9 of the book (with the exception of a brief discussion on observers and integral action in Section 5.5 of Chapter 5) we considered constrained optimal control problems for systems without uncertainty, that is, with no unmodelled dynamics or disturbances, and where the full state was available for measurement. More realistically, however, it is necessary to consider control problems for systems with uncertainty. This chapter addresses some of the issues that arise in this situation. As in Chapter 9, we adopt a stochastic description of uncertainty, which associates probability distributions to the uncertain elements, that is, disturbances and initial conditions. (See Section 12.6 for references to alternative approaches to model uncertainty.) When incomplete state information exists, a popular observer-based control strategy in the presence of stochastic disturbances is to use the certainty equivalence [CE] principle, introduced in Section 5.5 of Chapter 5 for deterministic systems. In the stochastic framework, CE consists of estimating the state and then using these estimates as if they were the true state in the control law that results if the problem were formulated as a deterministic problem (that is, without uncertainty). This strategy is motivated by the unconstrained problem with a quadratic objective function, for which CE is indeed the optimal solution (˚Astr¨om 1970, Bertsekas 1976). One of the aims of this chapter is to explore the issues that arise from the use of CE in RHC in the presence of constraints. We then turn to the obvious question about the optimality of the CE principle. We show that CE is, indeed, not optimal in general. We also analyse the possibility of obtaining truly optimal solutions for single input linear systems with input constraints and uncertainty related to output feedback and stochastic disturbances.We first find the optimal solution for the case of horizon N = 1, and then we indicate the complications that arise in the case of horizon N = 2. Our conclusion is that, for the case of linear constrained systems, the extra effort involved in the optimal feedback policy is probably not justified in practice. Indeed, we show by example that CE can give near optimal performance. We thus advocate this approach in real applications.

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In order to execute, study, or improve operating procedures, companies document them as business process models. Often, business process analysts capture every single exception handling or alternative task handling scenario within a model. Such a tendency results in large process specifications. The core process logic becomes hidden in numerous modeling constructs. To fulfill different tasks, companies develop several model variants of the same business process at different abstraction levels. Afterwards, maintenance of such model groups involves a lot of synchronization effort and is erroneous. We propose an abstraction technique that allows generalization of process models. Business process model abstraction assumes a detailed model of a process to be available and derives coarse-grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. We propose to learn insignificant process elements from supplementary model information, e.g., task execution time or frequency of task occurrence. Finally, we discuss a mechanism for user control of the model abstraction level – an abstraction slider.

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Process models provide companies efficient means for managing their business processes. Tasks where process models are employed are different by nature and require models of various abstraction levels. However, maintaining several models of one business process involves a lot of synchronization effort and is erroneous. Business process model abstraction assumes a detailed model of a process to be available and derives coarse grained models from it. The task of abstraction is to tell significant model elements from insignificant ones and to reduce the latter. In this paper we argue that process model abstraction can be driven by different abstraction criteria. Criterion choice depends on a task which abstraction facilitates. We propose an abstraction slider - a mechanism that allows user control of the model abstraction level. We discuss examples of combining the slider with different abstraction criteria and sets of process model transformation rules.

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In moderate to high sea states, the effectiveness of ship fin stabilizers can severely deteriorate due to nonlinear effects arising from unsteady hydrodynamic characteristics of the fins: dynamic stall. These nonlinear effects take the form of a hysteresis, and they become very significant when the effective angle of attack of the fins exceeds a certain threshold angle. Dynamic stall can result in a complete loss of control action depending on how much the fins exceed the threshold angle. When this is detected, it is common to reduce the gain of the controller that commands the fins. This approach is cautious and tends to reduce performance when the conditions leading to dynamic stall disappear. An alternative approach for preventing the effects while keeping high performance, consists of estimating the effective angle of attack and set a conservative constraint on it as part of the control objectives. In this paper, we investigate the latter approach, and propose the use of a model predictive control (MPC) to prevent the development of these nonlinear effects by considering constraints on both the mechanical angle of the fins and the effective angle of attack.

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Parametric roll is a critical phenomenon for ships, whose onset may cause roll oscillations up to +-40 degrees, leading to very dangerous situations and possibly capsizing. Container ships have been shown to be particularly prone to parametric roll resonance when they are sailing in moderate to heavy head seas. A Matlab/Simulink parametric roll benchmark model for a large container ship has been implemented and validated against a wide set of experimental data. The model is a part of a Matlab/Simulink Toolbox (MSS, 2007). The benchmark implements a 3rd-order nonlinear model where the dynamics of roll is strongly coupled with the heave and pitch dynamics. The implemented model has shown good accuracy in predicting the container ship motions, both in the vertical plane and in the transversal one. Parametric roll has been reproduced for all the data sets in which it happened, and the model provides realistic results which are in good agreement with the model tank experiments.

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In this paper, we consider a passivity-based approach for the design of a control law of multiple ship-roll gyro-stabiliser units. We extend previous work on control of ship roll gyro-stabilisation by considering the problem within a nonlinear framework. In particular, we derive an energy-based model using the port-Hamiltonian theory and then design an active precession controller using passivity-based control interconnection and damping assignment. The design considers the possibility of having multiple gyro-stabiliser units, and the desired potential energy of the system (in closed loop) is chosen to behave like a barrier function, which allows us to enforce constraints on the precession angle of the gyros.

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Objective To determine whether locally applied tobramycin influences the ability of recombinant human bone morphogenetic protein 2 (rhBMP-2) to heal a segmental defect in the rat femur. Methods The influence of tobramycin on the osteogenic differentiation of mesenchymal stem cells was first evaluated in vitro. For the subsequent, in vivo experiments, a 5-mm segmental defect was created in the right femur of each of 25 Sprague-Dawley rats and stabilized with an external fixator and four Kirschner wires. Rats were divided in four groups: empty control, tobramycin (11 mg)/absorbable collagen sponge, rhBMP-2 (11 μg)/absorbable collagen sponge, and rhBMP-2/absorbable collagen sponge with tobramycin. Bone healing was monitored by radiography at 3 and 8 weeks. Animals were euthanized at 8 weeks and the properties of the defect were compared with the intact contralateral femur. Bone formation in the defect region was assessed by dual-energy x-ray absorptiometry, microcomputed tomography, histology, and mechanical testing. Results Tobramycin exerted a dose-dependent inhibition of alkaline phosphatase induction and calcium deposition by mesenchymal stem cells cultured under osteogenic conditions. The inhibition was reversed in the presence of 500 ng/mL of rhBMP-2. Segmental defects in the rat femora failed to heal in the absence of rhBMP-2. Tobramycin exerted no inhibitory effects on the ability of rhBMP-2 to heal these defects and increased the bone area of the defects treated with rhBMP-2. Data obtained from all other parameters of healing, including dual-energy x-ray absorptiometry, microcomputed tomography, histology, and mechanical testing, were unaffected by tobramycin. Conclusions Although our in vitro results suggested that tobramycin inhibits the osteogenic differentiation of mesenchymal stem cells, this could be overcome by rhBMP-2. Tobramycin did not impair the ability of rhBMP-2 to heal critical-sized femoral defects in rats. Indeed, bone area was increased by nearly 20% in the rhBMP-2 group treated with tobramycin. This study shows that locally applied tobramycin can be used in conjunction with rhBMP-2 to enhance bone formation at fracture sites.

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This paper presents a control design for tracking of attitude and speed of an underactuated slender-hull unmanned underwater vehicle (UUV). The control design is based on Port-Hamiltonian theory. The target dynamics (desired dynamic response) is shaped with particular attention to the target mass matrix so that the influence of the unactuated dynamics on the controlled system is suppressed. This results in achievable dynamics independent of uncontrolled states. Throughout the design, insight of the physical phenomena involved is used to propose the desired target dynamics. The performance of the design is demonstrated through simulation with a high-fidelity model.

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Validation is an important issue in the development and application of Bayesian Belief Network (BBN) models, especially when the outcome of the model cannot be directly observed. Despite this, few frameworks for validating BBNs have been proposed and fewer have been applied to substantive real-world problems. In this paper we adopt the approach by Pitchforth and Mengersen (2013), which includes nine validation tests that each focus on the structure, discretisation, parameterisation and behaviour of the BBNs included in the case study. We describe the process and result of implementing a validation framework on a model of a real airport terminal system with particular reference to its effectiveness in producing a valid model that can be used and understood by operational decision makers. In applying the proposed validation framework we demonstrate the overall validity of the Inbound Passenger Facilitation Model as well as the effectiveness of the validity framework itself.