62 research outputs found
A numerical investigation of using flap control on VAWTs
No full textThe renewable energy need facilitates the development of offshore wind power. The abundant wind resource has pushed the wind farms into deep water sites. The floating VAWT concept is emerges as the times require. This research is part of Deepwind concept development. The project focuses on verifying the feasibility of using flap control to increase the power conversion of a VAWT through the numerical investigation. As a preliminary implementation, only a 2-D section is taken out from the Darrieus rotor as the modeled object. The report concentrates on the purely aerodynamic modeling of a VAWT. All the blades are assumed to be fully rigid in order to exempt the structural response. VAWTs present a distinct aerodynamic pattern from HAWT. To start up, a historical review on the aerodynamic models of VAWTs is performed to recap the critical issues in the aerodynamic modeling. The study mainly emphasizes on the momentum models, covers SST, MST, DMST and Actuator Cylinder (AC) models. AC mainly advantages on including the lateral inductions, and the wake interaction. Its precise prediction was confirmed in the simulation results of the aerodynamic model comparison study [10]. Hence, AC has been chosen as the numerical tool for VAWT modeling, both for the self-developed routine and HAWC2. A promising solution to determine the load-form for optimal power is constructing a uniform distribution so that the power coefficient could reach Betz limit. The normal load distribution on the blade path is the link between the power conversion and the blade force. At the moment of the determination of the load distribution that leads to the optimal power, the required blade force at the different azimuth positions are also settled. The simulations are performed with TSR=2, 3, 4, and 5 to verify the possibility on achieving the ideal power production in order to draw up an optimized control option. The result of the study is presented as a form of different flap angles at discretized azimuth positions. Even though the load-form is universal, the resultant flap variation only works for the specific rotor because of the introduction of airfoil data in the computation. An H-rotor VAWT with aps is set up in HAWC2 to validate the control strategy. As the supplement to AC model, a dynamic stall model called ATEFlap is integrated in HAWC2 to calculate the dynamic stall impact, and the influences from flap detection for the given airfoil. The model is supposed to return the aerodynamic loading of the blades under the dynamic stall. Hence, the deviations between the target load distribution obtained from the quasi-steady environment and the semi-dynamic one is observed as expected. In the end, the aps running with the given function could almost give the desired loading, but the deviations are observed in downwind part. It is mainly the hysteresis of the lift coefficient causes the difference. It is proven to be partly made up by increasing the flap deflections in the downwind side.European Wind Energy Masters (EWEM
A recursively feasible distributed robust MPC algorithm for vehicle platooning
No full textThis paper considers the design of a feedback robust model predictive control (MPC) algorithm for vehicle platooning. A vehicle platoon is modeled by individual simplified longitudinal dynamics which are coupled through the input of preceding vehicles. The coupled input is regarded as a disturbance and the framework of robust MPC proposed by [Goulart et al., 2006] is adopted for controller design. The main contribution is a feedback robust MPC algorithm with recursive feasibility guarantee in the presence of time–varying disturbance bounds. The proposed algorithm may yield a larger feasible region comparing to the decentralized control scheme, especially when the size of the vehicle platoon increases. Simulations results demonstrate the effectiveness of the distributed MPC algorithm
On distributed model predictive control for vehicle platooning with a recursive feasibility guarantee
No full textThis paper proposes a distributed model predictive control algorithm for vehicle platooning and more generally networked systems in a chain structure. The distributed models of the vehicle platoon are coupled through the input of the preceding vehicles. Using the principles of robust model predictive control, the coupled input is regarded as a disturbance and the robust model predictive control algorithm proposed by [Kerrigan, 2001] is employed for every vehicle. Based on this approach, a new distributed model predictive control algorithm is proposed by communicating the inputs among the vehicles, which enlarges the feasible regions of the local controllers while recursive feasibility still holds
Finite-sample analysis of identification of switched linear systems with arbitrary or restricted switching
No full textFor the identification of switched systems with a measured switching signal,
this work aims to analyze the effect of switching strategies on the estimation
error. The data for identification is assumed to be collected from globally
asymptotically or marginally stable switched systems under switches that are
arbitrary or subject to an average dwell time constraint. Then the switched
system is estimated by the least-squares (LS) estimator. To capture the effect
of the parameters of the switching strategies on the LS estimation error,
finite-sample error bounds are developed in this work. The obtained error
bounds show that the estimation error is logarithmic of the switching
parameters when there are only stable modes; however, when there are unstable
modes, the estimation error bound can increase linearly as the switching
parameter changes. This suggests that in the presence of unstable modes, the
switching strategy should be properly designed to avoid the significant
increase of the estimation error
Bioinformatics analysis of the phytoene synthase gene in cabbage (Brassica oleracea var. capitata)
No full textA Behavioral Perspective on Models of Linear Dynamical Networks with Manifest Variables
No full textNetworks of dynamical systems play an important role in various domains and
have motivated many studies on the control and analysis of linear dynamical
networks. For linear network models considered in these studies, it is
typically pre-determined what signal channels are inputs and what are outputs.
These models do not capture the practical need to incorporate different
experimental situations, where different selections of input and output
channels are applied to the same network. Moreover, a unified view of different
network models is lacking. This work makes an initial step towards addressing
the above issues by taking a behavioral perspective, where input and output
channels are not pre-determined. The focus of this work is on behavioral
network models with only external variables. By exploiting the concept of
hypergraphs, novel dual graphical representations, called system graphs and
signal graphs, are introduced for behavioral networks. Moreover, connections
between behavioral network models and structural vector autoregressive models
are established. In addition to their connections in graphical representations,
it is shown that the regularity of interconnections is an essential assumption
when choosing a structural vector autoregressive model
Bioinformatics analysis of the ς-carotene desaturase gene in cabbage (Brassica oleracea var. capitata)
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