First Riccati equation with matrix variable coefficients, arising in optimal and robust control approach, is considered. An analytical approximation of the solution of nonlinear differential Riccati equation is investigated using the Adomian decomposition method. An application in optimal control is presented. The solution in different order of approximations and different methods of approximat...

In the case of widely-uncertain non-linear system control design, it was very difficult to design a single controller to overcome control design specifications in all of its dynamical characteristics uncertainties. To resolve these problems, a new design method of robust fuzzy control proposed. The solution offered was by creating multiple soft-switching with Takagi-Sugeno fuzzy model for optim...

Modeling of fermentation processes is so complicated and uncertain; therefore it is necessary to provide a robust and appropriate dynamic optimization method. In order to obtain the maximum amount of yeast (Saccharomyces cerevisiae), the bioreactor must be operated under optimal conditions. To determine substrate feeding in a fed-batch bioreactor, a simulated annealing (SA) approach was examine...

in this paper, we consider a flow shop scheduling problem with availability constraints (fsspac) for the objective of minimizing the makespan. in such a problem, machines are not continuously available for processing jobs due to preventive maintenance activities. we proposed a mixed-integer linear programming (milp) model for this problem which can generate non-permutation schedules. furthermor...

In this paper, we consider the robust optimal portfolio selection problem where the return mean and covariance are supposed to be uncertain comparing to Markowitz’s model. The return mean is uncertain changing in intervals, and we introduce the cuts of fuzzy number to build the uncertain intervals for covariance. We report on empirical tests in which we compare the robust model with the classic...

The growth-optimal portfolio is designed to have maximum expected log-return over the next rebalancing period. Thus, it can be computed with relative ease by solving a static optimization problem. The growthoptimal portfolio has sparked fascination among finance professionals and researchers because it can be shown to outperform any other portfolio with probability 1 in the long run. In the sho...

Qualitatively, a filter is said to be “robust” if its performance degradation is acceptable for distributions close to the one for which it is optimal, that is, the one for which it has been designed. This paper adapts the signal-processing theory of optimal robust filters to classifiers. The distribution (class conditional distributions) to which the classifier is to be applied is parameterize...

We study the problem of estimating the position and orientation of a calibrated camera from an image of a known scene. A common problem in camera pose estimation is the existence of false correspondences between image features and modeled 3D points. Existing techniques such as ransac to handle outliers have no guarantee of optimality. In contrast, we work with a natural extension of the L∞ norm...