State-space approach to nonlinear predictive generalized minimum variance control

A Nonlinear Predictive Generalized Minimum Variance (NPGMV) control algorithm is introduced for the control of nonlinear discrete-time multivariable systems. The plant model is represented by the combination of a very general nonlinear operator and also a linear subsystem which can be open-loop unstable and is represented in state-space model form. The multi-step predictive control cost index to be minimised involves both weighted error and control signal costing terms. The solution for the control law is derived in the time-domain using a general operator representation of the process. The controller includes an internal model of the nonlinear process but because of the assumed structure of the system the state observer is only required to be linear. In the asymptotic case, where the plant is linear, the controller reduces to a state-space version of the well known GPC controller

Improvement of the branch and bound algorithm for solving the knapsack linear integer problem

The paper presents a new reformulation approach to reduce the complexity of a branch and bound algorithm for solving the knapsack linear integer problem. The branch and bound algorithm in general relies on the usual strategy of first relaxing the integer problem into a linear programing (LP) model. If the linear programming optimal solution is integer then, the optimal solution to the integer problem is available. If the linear programming optimal solution is not integer, then a variable with a fractional value is selected to create two sub-problems such that part of the feasible region is discarded without eliminating any of the feasible integer solutions. The process is repeated on all variables with fractional values until an integer solution is found. In this approach variable sum and additional constraints are generated and added to the original problem before solving. In order to do this the objective bound of knapsack problem is quickly determined. The bound is then used to generate a set of variable sum limits and four additional constraints. From the variable sum limits, initial sub-problems are constructed and solved. The optimal solution is then obtained as the best solution from all the sub-problems in terms of the objective value. The proposed procedure results in sub-problems that have reduced complexity and easier to solve than the original problem in terms of numbers of branch and bound iterations or sub-problems.The knapsack problem is a special form of the general linear integer problem. There are so many types of knapsack problems. These include the zero-one, multiple, multiple-choice, bounded, unbounded, quadratic, multi-objective, multi-dimensional, collapsing zero-one and set union knapsack problems. The zero-one knapsack problem is one in which the variables assume 0 s and 1 s only. The reason is that an item can be chosen or not chosen. In other words there is no way it is possible to have fractional amounts or items. This is the easiest class of the knapsack problems and is the only one that can be solved in polynomial by interior point algorithms and in pseudo-polynomial time by dynamic programming approaches. The multiple-choice knapsack problem is a generalization of the ordinary knapsack problem, where the set of items is partitioned into classes. The zero-one choice of taking an item is replaced by the selection of exactly one item out of each class of item

On the numerical classification of the singularities of robot manipulators

This paper is concerned with the task to obtain a complete description of the singularity set of any given non-redundant manipulator, including the identification and the precise computation of each constituent singularity class. Configurations belonging to the same class are equivalent in terms of the various types of kinematic and static degeneracy that characterize mechanism singularity. The proposed approach is an extension of recent work on computing singularities using a numerical method based on linear relaxations. Classification is sought by means of a hierarchy of singularity tests, each formulated as a system of quadratic or linear equations, which yields sets of classes to which an identified singularity cannot belong. A planar manipulator exemplifies the process of classification, and illustrates how, while most singularities get completely classified, for some lower-dimensional subsets one can only identify a restricted list of possible singularity classes.Postprint (published version

Coming of age: report on the euro area

This report surveys the economic performance of the euro area and gives recommendations about six policy challenges of major importance for the future of EMU.

Design and performance of the field cage for the XENONnT experiment

The precision in reconstructing events detected in a dual-phase time projection chamber depends on an homogeneous and well understood electric field within the liquid target. In the XENONnT TPC the field homogeneity is achieved through a double-array field cage, consisting of two nested arrays of field shaping rings connected by an easily accessible resistor chain. Rather than being connected to the gate electrode, the topmost field shaping ring is independently biased, adding a degree of freedom to tune the electric field during operation. Two-dimensional finite element simulations were used to optimize the field cage, as well as its operation. Simulation results were compared to 83mKr calibration data. This comparison indicates an accumulation of charge on the panels of the TPC which is constant over time, as no evolution of the reconstructed position distribution of events is observed. The simulated electric field was then used to correct the charge signal for the field dependence of the charge yield. This correction resolves the inconsistent measurement of the drift electron lifetime when using different calibrations sources and different field cage tuning voltages

On the comparison of predictive control and command governor approaches for operational management of drinking water networks: a case study

This paper evaluates the application of command governor (CG) strategy for the operational control of drinking water networks (DWN) given their large-scale and complex nature, the permanent and relevant effect of the disturbances (water demands) and their marginal stability feature. Moreover, the performance improvement offered by CG is compared with the application of model predictive control for the same management purposes and in the same context. The paper also discusses the effectiveness of both strategies and highlights the advantages of each approach. The Barcelona DWN is considered as case study for the undertaken assessment analysis.Peer ReviewedPostprint (author’s final draft

Essays on farm household credit constraint, productivity and consumption inequality in Malawi

Credit has proven to be a necessary tool for economic development affecting positively the welfare of households and individuals. However, one major area in which rural households lack is access to financial markets including credit. The studies included in this thesis contribute to the access to credit literature and the credit constraint/unconstraint impact on some welfare outcomes. The first empirical study examined farm households' access to credit in rural Malawi. Unlike previous empirical studies, particular attention is given to discouraged borrowers who are mostly ignored in such studies. Using the 2010/2011 household survey data from Malawi the study determines the demographic and socio-economic characteristics that distinguish farm households who need credit, who are the discouraged borrowers and who are rejected applicants. A three-step sequential estimation model following a trivariate probit model with double sample selection was adopted. The findings revealed that there were over 7 times more discouraged borrowers than denied applicants. Women were more likely to be discouraged from applying for credit but, if they applied, they were more likely to be successful in obtaining credit than males. This shows that when examining farm households' access to credit discouraged borrowers should be given special consideration. Capturing discouraged borrowers as also credit constrained, the second empirical study employed a switching model to estimate the impact of credit constraint status on farm productivity for each credit constraint regime. The study further compared the expected production under actual and counterfactual conditions for a household being credit constrained or unconstrained. The findings suggest that a household that is constrained is less productive than a randomly selected household from the sample would but that for the unconstrained household is inconclusive, however, the counterfactual arguments as seen from the analysis shows that being credit unconstrained was beneficial to the increase in productivity. Studies have shown that undeveloped financial markets have been a major contributing factor increasing inequality, especially in developing countries. The third empirical study examined the impact of household credit constraint on the consumption inequality of rural households in Malawi. Factors that explain the within and between credit constrained and unconstrained status of consumption inequality were examined. The General Entropy (GE) Index and the Regression-Based Inequality Decomposition Methods, Field's (2003) and Blinder-Oaxaca Decomposition were employed. The findings show that inequality was more prominent within the groups than between them. Also, the size of households and the value of assets were the major contributors to the within-group inequalities for credit constrained and unconstrained households. Further, only the endowment component was important in explaining the consumption inequality gap between the credit constrained and unconstrained households. Adjusting the level of endowments of constrained households to that of the unconstrained households increased their welfare by 15.7 percent

The Quadratic Assignment Problem : Some New Result and Generalization

The Quadratic assignment problem is a combinatorial problem ofdeciding the placement of facilities in specified locations in such a wayas to minimize an function expressed in terms of distances betweenlocations and flows between facilities. The approach presented in thispaper is to treat is as a large quadratic programming problem withinteger resfictions on the variables. The integer requirements areinitially relaxed, and the nearest feasible solutions in then sought.schemes for accomplishing this are described, and their applicability tomore general problems is discussed

An assessment of individual and institutional research utilization by policy-makers and programme managers at state and national levels in Nigeria

This report undertakes a systematic assessment of the need for evidence by decision-makers working on HIV and AIDS funding and policymaking, and implementing organizations at the national and subnational levels in Nigeria. The assessment identifies barriers and constraints to data use, identifies best practices, and offers recommendations for the design and prioritization of strategic approaches to address barriers and constraints in data use and production. Tools to monitor the adoption of evidence in policy and practice are also offered. The need for evidence-based practice in the national response to HIV and AIDS has been widely acknowledged and incorporated into policy guidance, the National Strategic Plan, and the National Research Agenda on HIV and AIDS. The political will for more evidence exists, yet this has not translated into the prioritization and financing of research. Likewise, many stakeholders have limited engagement in the design, coordination, dissemination, and utilization of research. To address these objectives, a literature review of knowledge production and utilization was conducted, along with a series of workshops to investigate policymaker and practitioner perspectives on data uses

On the expected number of equilibria in a multi-player multi-strategy evolutionary game

In this paper, we analyze the mean number $E(n,d)$ of internal equilibria in a general $d$-player $n$-strategy evolutionary game where the agents' payoffs are normally distributed. First, we give a computationally implementable formula for the general case. Next we characterize the asymptotic behavior of $E(2,d)$, estimating its lower and upper bounds as $d$ increases. Two important consequences are obtained from this analysis. On the one hand, we show that in both cases the probability of seeing the maximal possible number of equilibria tends to zero when $d$ or $n$ respectively goes to infinity. On the other hand, we demonstrate that the expected number of stable equilibria is bounded within a certain interval. Finally, for larger $n$ and $d$, numerical results are provided and discussed.Comment: 26 pages, 1 figure, 1 table. revised versio