In this paper, a method of thrust allocation based on a linearly constrained quadratic cost function capable of handling rotating azimuths is presented. The problem formulation accounts for magnitude and rate constrai...
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In this paper, a method of thrust allocation based on a linearly constrained quadratic cost function capable of handling rotating azimuths is presented. The problem formulation accounts for magnitude and rate constraints on both thruster forces and azimuth angles. The advantage of this formulation is that the solution can be found with a finite number of iterations for each time step. Experiments with a model ship are used to validate the thrust allocation system.
This paper considers the problem of identifying the control torques associated with the generation of complex movements in an anthropomorphic system. We present a generic motion generation scheme for humanoid robots. ...
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This paper considers the problem of identifying the control torques associated with the generation of complex movements in an anthropomorphic system. We present a generic motion generation scheme for humanoid robots. Then we use the torques estimated from human motion capture and force sensor measurements, to compare with similar movements simulated on a humanoid robot. The general features of movement during a sequence of reaching tasks are analyzed. In particular we compare kinematics-based and dynamics-based movements. Finally, the variation of torques at the different joints are compared and discussed.
Conditional selective inference (SI) has been studied intensively as a new statistical inference framework for data-driven hypotheses. The basic concept of conditional SI is to make the inference conditional on the se...
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Conditional selective inference (SI) has been studied intensively as a new statistical inference framework for data-driven hypotheses. The basic concept of conditional SI is to make the inference conditional on the selection event, which enables an exact and valid statistical inference to be conducted even when the hypothesis is selected based on the data. Conditional SI has mainly been studied in the context of model selection, such as vanilla lasso or generalized lasso. The main limitation of existing approaches is the low statistical power owing to over-conditioning, which is required for computational tractability. In this study, we propose a more powerful and general conditional SI method for a class of problems that can be converted into quadratic parametric programming, which includes generalized lasso. The key concept is to compute the continuum path of the optimal solution in the direction of the selected test statistic and to identify the subset of the data space that corresponds to the model selection event by following the solution path. The proposed parametric programming-based method not only avoids the aforementioned major drawback of over-conditioning, but also improves the performance and practicality of SI in various respects. We conducted several experiments to demonstrate the effectiveness and efficiency of our proposed method.
The possibility of tailoring the quadratic objective function to generate optimal policies which are acceptable to the policy maker is explored with two alternative algorithms. One of these is for objective functions ...
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The possibility of tailoring the quadratic objective function to generate optimal policies which are acceptable to the policy maker is explored with two alternative algorithms. One of these is for objective functions with diagonal Hessians and uses updates of the desired values. The second algorithm proceeds by updating the non-diagonal Hessians. The equivalence of both algorithms are established. The complexity of the algorithms, and thereby of the policy design process, is discussed. The extension to nonlinear constraints is studied. The arbitrariness of shadow prices are established for all quadratic equality constrained optimization problems. Starting initially with linear constraints, it is shown that either one of the algorithms can be used to alter the shadow prices by arbitrarily specified amounts. In one step, the algorithms are able to alter the shadow prices without altering the optimal solution. It is shown that this is also true for nonlinear problems.
Metabolic Flux Analysis was performed to identify the significant metabolic reactions for hybridoma cells during batch and fed-batch culture. Correlation analysis yielded the factors that influence biomass growth and ...
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Metabolic Flux Analysis was performed to identify the significant metabolic reactions for hybridoma cells during batch and fed-batch culture. Correlation analysis yielded the factors that influence biomass growth and productivity and elucidated the nature of the relationship between them. Consequently, an integrated dynamic model expressing the rate of consumption and production of nutrients/metabolites and the biomass growth and decline was developed.
Recycling of paper is typically performed in a chain of processes. An important process is the peroxide bleaching implementing the means to achieve a high brightness quality. As this process step requires consumption ...
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Recycling of paper is typically performed in a chain of processes. An important process is the peroxide bleaching implementing the means to achieve a high brightness quality. As this process step requires consumption of various chemicals, it is quite cost intensive. This paper presents means to optimize the bleaching stage to achieve an (adaptable) trade-off between cost and brightness: First, the time-varying deadtime of the bleaching stage is estimated using a Kalman filter. Second, the bleaching stage is modelled by Gaussian processes aiming to be used for optimization of the bleaching stage by application of a model predictive controller.
The new procedure, in which the minimum annual cost (or investment) is used as the objective function, is presented to optimize looped water distribution network, combining the quadric orthogonal circumrotation regres...
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The new procedure, in which the minimum annual cost (or investment) is used as the objective function, is presented to optimize looped water distribution network, combining the quadric orthogonal circumrotation regression design, the quadratic programming and the linear programming together. First, the flow distribution schemes are set down by means of quadric orthogonal circumrotation regression design. The annual cost of each flow distribution scheme is determined by linear programming and the quadric multiple regression equation between the annual cost and the pipe segment flows is established. Second, the optimal flow distribution scheme in which the quadric multiple regression equation is used as the objective function is determined by the quadratic programming. Finally, the optimal design of looped network is determined by linear programming based on the optimal flow distribution scheme. The procedure can be used to optimize the single resource looped network with pump station and gravity.
“Multifunctionality” emphasizes the benefit externality properties of nonfood products that coincide with agricultural commodity production, some of which also have public-good properties. However, determining the w...
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“Multifunctionality” emphasizes the benefit externality properties of nonfood products that coincide with agricultural commodity production, some of which also have public-good properties. However, determining the willingness to pay for local benefit externalities is seen as necessary but daunting. This paper pursues the idea that the valuation process might first start by estimating the incentives required to supply various levels of a benefit externality. With the use of carbon sequestration through the adoption of no-till cultivation as an example of a multifunctional benefit externality, mathematical programming is used to derive representative price schedules. The implication for incentive prices are examined in light of risk aversion.
A robust version of the output controller design for discrete-time systems is introduced. Instead of a single stable point a stable polytope (or simplex) is preselected in the coefficient space of closed-loop characte...
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A robust version of the output controller design for discrete-time systems is introduced. Instead of a single stable point a stable polytope (or simplex) is preselected in the coefficient space of closed-loop characteristic polynomials. A constructive procedure for generating stable simplexes is given starting from the unit hypercube of reflection coefficients of monic polynomials. This procedure is quite straightforward, because for a special family of polynomials the linear cover of so-called reflection vectors is stable. The root placement of reflection vectors is studied. If a stable target simplex is preselected, then the robust output controller design task is solved by the quadratic programming approach. [ABSTRACT FROM AUTHOR]
ABSTRACTABSTRACTLimited (short-run) supplies of public campground facilities may be allocated on the basis of price or nonprice rationing procedures. The presumption that the demand for campsites is extremely inelasti...
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ABSTRACTABSTRACTLimited (short-run) supplies of public campground facilities may be allocated on the basis of price or nonprice rationing procedures. The presumption that the demand for campsites is extremely inelastic underlies much of the hesitancy to employ price rationing for allocation purposes. This study argues, however, that where substitutes exist, campsite demand may not be price inelastic. This possibility is investigated for a particular campground in Massachusetts and a set of “optimal” short-run prices are derived.
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