Inspired from the robust control principle, a robust scheduling method is proposed to solve uncertain scheduling problems. The uncertain scheduling problem is modeled by a set of workflow simulation models, and then a scheduling scheme (solution) is evaluated by the results of workflow simulations that are executed by using the workflow models in the set. A variable neighborhood immune algorith...

We consider an uncertain variant of the knapsack problem in which the weight of the items is not exactly known in advance, but belongs to a given interval, and an upper bound is imposed on the number of items whose weight differs from the expected one. For this problem, we provide a dynamic programming algorithm and present techniques aimed at reducing its space and time complexities. Finally, ...

The aim of this paper is to propose a model-based feedback control strategy for indoor temperature regulation in buildings equipped with underfloor air distribution (UFAD). Supposing distributed sensing and actuation capabilities, a 0D model of the ventilation process is derived, based on the thermodynamics properties of the flow. A state-space description of the process is then inferred, inclu...

This paper deals with the modeling, analysis, design and simulation of a robust control method for a permanent magnet synchronous machine (PMSM) supplied with a PWM inverter based on a LPV (Linear Parameter Variation)  standard controller. Under the influence of uncertainties and external disturbances, by a variation of ±150% of motor parameters from the nominal values, the robust performance c...

This paper is concerned with the problem of design and implementation a robust adaptive control strategy for flexible joint electrically driven robots (FJEDR), while considering to the constraints on the actuator voltage input. The control design procedure is based on function approximation technique, to avoid saturation besides being robust against both structured and unstructured uncertaintie...

In this paper, a new approach is presented to fit arobust fuzzy regression model based on some fuzzy quantities. Inthis approach, we first introduce a new distance between two fuzzynumbers using the kernel function, and then, based on the leastsquares method, the parameters of fuzzy regression model isestimated. The proposed approach has a suitable performance to<b...

This paper deals with the design and evaluation of a robust controller for static VAR compensator (SVC) in remote industrial power systems to enhance the voltage profile for three-phase single cage induction motor (SCIM) loads. The controller design is based on H∞ theory to deal with uncertainties arising in industrial network modelling. &#10The performance of the H∞ controller has been evaluat...

In this paper, a robust local controller has been designed to balance the power for distributed energy resources (DERs) in an islanded microgrid. Three different DER types are considered in this study; photovoltaic systems, battery energy storage systems, and synchronous generators. Since DER dynamics are nonlinear and uncertain, which may destabilize the power system or decrease the performanc...

Uncertainty is a prominent feature of real world problems and more especially financialmarkets; with this in mind, dealing with uncertainty becomes a necessary part of performanceevaluation by means of data envelopment analysis. This paper presents three robust dataenvelopment analysis (DEA) models and their application for performance evaluation inTehran Stock Exchange (TSE). Based on the resu...

In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...