A fault detection and isolation (FDI) system for monitoring the stator current and voltage sensors of a doubly-fed induction generator (DFIG) for wind energy applications is presented. The FDI system is based on the m...
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A fault detection and isolation (FDI) system for monitoring the stator current and voltage sensors of a doubly-fed induction generator (DFIG) for wind energy applications is presented. The FDI system is based on the model of the balanced three-phase signals, that is used to design a residual generator resting on the so-called Generalized Observer Scheme (GOS). Next, a decision system made of a combination of vector CUSUM (Cumulative Sum) algorithms is used in order to process the residual vector and achieve detection and isolation of incipient additive faults. The approach is validated via simulations of the DFIG controlled by a Linear Quadratic Gaussian (LQG) regulator.
This paper is concerned with system level energy management in wireless sensor networks. The network is required to conduct certain tasks which require information from individual sensors to be sent to a base station....
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This paper is concerned with system level energy management in wireless sensor networks. The network is required to conduct certain tasks which require information from individual sensors to be sent to a base station. Sensors cease functioning when they deplete their energy reserves or may fail abruptly due to random malfunctions. Sensor selection refers to the number of times sensors are interrogated, while sensor scheduling refers to the sequence in which these interrogations are conducted. A sensor management layer that isolates the system objectives from selection/scheduling is proposed. It is shown that sensor selection reduces to integer linear programming. Sensor scheduling is necessary when random sensor failures are considered or when the task definition is not stationary. Some general principles emerge. If all sensors are equally reliable, the optimal policy is to use the most energetic sensors first. If all sensors are equally energetic, the optimal policy is to use the least reliable sensor first.
Using induced L2-norm minimization, a robust controller was developed for insulin delivery in Type I diabetic patients. The high-complexity nonlinear diabetic patient Sorensen-model was considered and Linear Parameter...
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In spite of the multiple advantages that multi-robot systems offer, to turn them into a realistic option and to get their proliferation, they must be economically attractive. Multi-robot systems are composed of severa...
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In this paper a Wells turbine control is presented. For this purpose, a control scheme for the flow coefficient is derived based on the addition of external resistances in series with the rotor winding of the inductio...
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ISBN:
(纸本)9781424442515
In this paper a Wells turbine control is presented. For this purpose, a control scheme for the flow coefficient is derived based on the addition of external resistances in series with the rotor winding of the induction generator connected to the turbine. Due to the stalling behaviour, the generator increases its velocity as the flow coefficient of the turbine approaches the critical point at which the turbine losses power. The proposed controlsystem does appropriately adapt the rotor resistance according to the entry pressure drop. To do so, the control implements a continuous resistance switching depending on the pressure drop and it will be demonstrated that the average power of the turbine and generator are significantly higher in the controlled case than in the uncontrolled one. It is stated that there exist an optimal value of external resistances for each specific range of pressure drop and it is verified that greater input pressure drop does not imply higher power output unless the stalling behaviour is avoided.
Abstract Nuclear fusion has the potential to produce unlimited, clean energy, which presents itself as a reliable energy supply but it also helps to stop the threat of climate change that faces the world nowadays. How...
Abstract Nuclear fusion has the potential to produce unlimited, clean energy, which presents itself as a reliable energy supply but it also helps to stop the threat of climate change that faces the world nowadays. However, to sustain the pulse duration long enough to produce the necessary energy, new controls have to be developed, composing a new application area of controlengineering, with new and interesting challenges for the control community. In this sense, this paper deals with the modeling of tokamak nuclear fusion reactors. In order to control the creation of unstable modes in fusion processes, it is necessary to derive numerical models suitable for control strategies. The model presented in this paper addresses flux and energy conservation issues, discussing the mechanisms behind the creation of uncontrollable modes. The dynamics of the system is given by means of the energy functions which are solved for the currents in the structure, plasma current and plasma position. Thus, the equations for the state variables are derived based on the Hamiltonian equation of motion. In order to solve this system numerically, this model is linearized around an operation point by taking a Newton-Raphson step. Besides, the system output is completed by considering the equations for the flux and the poloidal field. Finally, the resulting low-order linear model is modified so as to obtain the corresponding state-space model which is verified by means of numerical experiments.
Techniques for optimal control of hybrid systems have to consider the complex interaction of continuous and discrete dynamics and are required to limit the computational complexity arising from the corresponding searc...
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Techniques for optimal control of hybrid systems have to consider the complex interaction of continuous and discrete dynamics and are required to limit the computational complexity arising from the corresponding search spaces. This contribution proposes an approach to computing hybrid optimal control trajectories based on an iterative model-abstraction and refinement scheme. The hybrid automaton is mapped to an abstract representation which is enriched by cost information gained from graph. Candidate solutions are computed on the abstract level and are mapped back to the level of the hybrid model, where they are validated. A refinement step guides the search for (sub-) optimal hybrid control trajectories. The proposed approach is implemented for the optimization of the start-up procedure for a chemical reactor.
A variety of problems arising in communication networks, computer networks, automated manufacturing plants, etc. can be described by min-max-plus system models. Output feedback stabilization for the nonlinear, non-aut...
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This work presents a strategy to track and describe the boundary of an environmental surface using a sequence of incomplete boundary images coming from an UAV with a camera onboard. The algorithm uses all captured ima...
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This work presents a strategy to track and describe the boundary of an environmental surface using a sequence of incomplete boundary images coming from an UAV with a camera onboard. The algorithm uses all captured images to feed the trajectory, which drives the UAV towards the next point to take the next shot, until the identification is completed. The multiple patterns of the input image make the problem difficult. Our approach orders the points of the image to identify the existent edges, and computes the trajectory as a minimization problem using a multi-objective function that gathers information about the boundary and the polynomial that fit in these edges.
Scale-free network and consensus among multiple agents have both drawn quite much attention. To investigate the consensus speed over scale-free networks is the main topic in this paper. Given a set of different values...
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Scale-free network and consensus among multiple agents have both drawn quite much attention. To investigate the consensus speed over scale-free networks is the main topic in this paper. Given a set of different values for the power-law distribution parameter γ, and a set of different values for the minimum degree ( d min ) for the nodes, the algebraic connectivity (λ 2 ) of the network topology is studied, as well as the time ( t c ) (or iteration ( k c ), for discrete algorithm) taken to reach consensus. The results exhibit that λ 2 decreases while γ increases. The λ 2 increases monotonically as d min grows, and they fit very well in a linear relationship. t c (or k c ) decreases as γ reduces and d min increases. Via observing the behavior of the largest eigenvalue (λ n ) of the Laplacian of the network topology, we draw the conclusion that the robustness over time delays declines while the robustness over node-failures and edge-failures increases.
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