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In this paper new results in adaptive (generalized) minimum variance control of packet switching computer networks are presented. New solutions, corresponding to the new inverses of the nonsquare polynomial matrices, can be used for design of robust control of multivariable systems with different number of inputs and outputs. Application of polynomial matrix inverses with arbitrary degrees of freedom creates the possibilities to optimal control of computer networks in terms of usage their maximal bandwidth. Simulation examples made in Matlab environment show big potential of presented approach.

This article addresses the challenge of searching for the optimal location for a newly designed pollutant emitter (new factory or other facility) in relation to the requirements imposed by environmental protection regulations on the concentrations of selected pollutants in a given area, taking into account the currently existing levels of analysed substances. The paper presents the key issues of the dispersion of pollutants in atmospheric air and pollutant dispersion models. The Gaussian model of a plume, based on the Pasquill diffusion equation, is chosen to simulate the dispersion of pollutants in atmospheric air. The key issue within the paper constitutes the research section responsible for using the Monte Carlo global optimisation method in order to find the optimal location. The proposed algorithm is intended to offer measurable and subjective arguments and options to preliminary discussions on choosing a location for new factories, while such discussions choices should be fact-based and ecologically acceptable instead of fulfilling only political or economical goals. The paper is intended to present the need for easily interpretable arguments for discussions and responsible decisions on choosing the lowest-impact location of pollutant emitters to the scientific community.