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Analysis and practical aspects of implementing developed in the control theory robust control methods in studying economic systems is carried out. The main emphasis is placed on studying results obtained for dynamical systems with structured uncertainty. Practical aspects of implementing such results in control of economic systems on the basis of dynamical models with uncertain parameters and perturbations (stabilization of price on the oil market and inflation in macroeconomic systems) are discussed. With the help of specially constructed aggregate model of oil price dynamics studied the problem of finding control which provides minimal deviation of price from desired levels over middle range period. The second real problem considered in the article consists in determination of stabilizing control providing minimal deviation of inflation from desired levels (on the basis of constructed aggregate macroeconomic model of the USA over middle range period).

Upper levels of parameters uncertainty and control laws guaranteeing stabilizability of the real considered economic systems have been found using the robust method of control with structured uncertainty. At the same time we have come to the conclusion that received estimates of parameters uncertainty upper levels are conservative. Monte-Carlo experiments carried out for the article made it possible to analyze dynamics of oil price and inflation under received limit levels of models parameters uncertainty and under implementing found robust control laws for the worst and the best scenarios. Results of these experiments show that received robust control laws may be successfully used under less stringent uncertainty constraints than it is guaranteed by sufficient conditions of stabilization.

In this paper, we consider two variants of the concept of sharp minimum for mathematical programming problems with quasiconvex objective function and inequality constraints. It investigated the problem of describing a variant of a simple subgradient method with switching along productive and non-productive steps, for which, on a class of problems with Lipschitz functions, it would be possible to guarantee convergence with the rate of geometric progression to the set of exact solutions or its vicinity. It is important that to implement the proposed method there is no need to know the sharp minimum parameter, which is usually difficult to estimate in practice. To overcome this problem, the authors propose to use a step adjustment procedure similar to that previously proposed by B. T. Polyak. However, in this case, in comparison with the class of problems without constraints, it arises the problem of knowing the exact minimal value of the objective function. The paper describes the conditions for the inexactness of this information, which make it possible to preserve convergence with the rate of geometric progression in the vicinity of the set of minimum points of the problem. Two analogs of the concept of a sharp minimum for problems with inequality constraints are considered. In the first one, the problem of approximation to the exact solution arises only to a pre-selected level of accuracy, for this, it is considered the case when the minimal value of the objective function is unknown; instead, it is given some approximation of this value. We describe conditions on the inexact minimal value of the objective function, under which convergence to the vicinity of the desired set of points with a rate of geometric progression is still preserved. The second considered variant of the sharp minimum does not depend on the desired accuracy of the problem. For this, we propose a slightly different way of checking whether the step is productive, which allows us to guarantee the convergence of the method to the exact solution with the rate of geometric progression in the case of exact information. Convergence estimates are proved under conditions of weak convexity of the constraints and some restrictions on the choice of the initial point, and a corollary is formulated for the convex case when the need for an additional assumption on the choice of the initial point disappears. For both approaches, it has been proven that the distance from the current point to the set of solutions decreases with increasing number of iterations. This, in particular, makes it possible to limit the requirements for the properties of the used functions (Lipschitz-continuous, sharp minimum) only for a bounded set. Some computational experiments are performed, including for the truss topology design problem.

In this paper, we discuss the procedure for finding nominal trajectories of the planar five-link bipedal robot with point contact. To this end we use a virtual constraints method that transforms robot’s dynamics to a lowdimensional zero manifold; we also use a nonlinear optimization algorithms to find virtual constraints parameters that minimize robot’s cost of transportation. We analyzed the effect of the degree of Bezier polynomials that approximate the virtual constraints and continuity of the torques on the cost of transportation. Based on numerical results we found that it is sufficient to consider polynomials with degrees between five and six, as further increase in the degree of polynomial results in increased computation time while it does not guarantee reduction of the cost of transportation. Moreover, it was shown that introduction of torque continuity constraints does not lead to significant increase of the objective function and makes the gait more implementable on a real robot.

We propose a two step procedure for finding minimum of the considered optimization problem with objective function in the form of cost of transportation and with high number of constraints. During the first step we solve a feasibility problem: remove cost function (set it to zero) and search for feasible solution in the parameter space. During the second step we introduce the objective function and use the solution found in the first step as initial guess. For the first step we put forward an algorithm for finding initial guess that considerably reduced optimization time of the first step (down to 3–4 seconds) compared to random initialization. Comparison of the objective function of the solutions found during the first and second steps showed that on average during the second step objective function was reduced twofold, even though overall computation time increased significantly.

In this paper, we address the mathematical modeling of robots based on tensegrity structures. The pivotal property of such structures is the forming elements working only for compression or tension, which allows the use of materials and structural solutions that minimize the weight of the structure while maintaining its strength.

Tensegrity structures hold several properties important for collaborative robotics, exploration and motion tasks in non-deterministic environments: natural compliance, compactness for transportation, low weight with significant impact resistance and rigidity. The control of such structures remains an open research problem, which is associated with the complexity of describing the dynamics of such structures.

We formulate an approach for describing the dynamics of such structures, based on second-order dynamics of the Cartesian coordinates of structure elements (rods), first-order dynamics for angular velocities of rods, and first-order dynamics for quaternions that are used to describe the orientation of rods. We propose a numerical method for solving these dynamic equations. The proposed methods are implemented in the form of a freely distributed mathematical package with open source code.

Further, we show how the provided software package can be used for modeling the dynamics and determining the operating modes of tensegrity structures. We present an example of a tensegrity structure moving in zero gravity with three rigid rods and nine elastic elements working in tension (cables), showing the features of the dynamics of the structure in reaching the equilibrium position. The range of initial conditions for which the structure operates in the normal mode is determined. The results can be directly used to analyze the nature of passive dynamic movements of the robots based on a three-link tensegrity structure, considered in the paper; the proposed modeling methods and the developed software are suitable for modeling a significant variety of tensegrity robots.

The aim of the work is to study a monotone finite-difference scheme of the second order of accuracy, created on the basis of a generalization of the one-dimensional Z-scheme. The study was carried out for model equations of the transfer of an incompressible medium. The paper describes a two-dimensional generalization of the Z-scheme with nonlinear correction, using instead of streams oblique differences containing values from different time layers. The monotonicity of the obtained nonlinear scheme is verified numerically for the limit functions of two types, both for smooth solutions and for nonsmooth solutions, and numerical estimates of the order of accuracy of the constructed scheme are obtained.

The constructed scheme is absolutely stable, but it loses the property of monotony when the Courant step is exceeded. A distinctive feature of the proposed finite-difference scheme is the minimality of its template. The constructed numerical scheme is intended for models of plasma instabilities of various scales in the low-latitude ionospheric plasma of the Earth. One of the real problems in the solution of which such equations arise is the numerical simulation of highly nonstationary medium-scale processes in the earth’s ionosphere under conditions of the appearance of the Rayleigh – Taylor instability and plasma structures with smaller scales, the generation mechanisms of which are instabilities of other types, which leads to the phenomenon F-scattering. Due to the fact that the transfer processes in the ionospheric plasma are controlled by the magnetic field, it is assumed that the plasma incompressibility condition is fulfilled in the direction transverse to the magnetic field.

Changes in abundance for emerging populations can develop according to several dynamic scenarios. After rapid biological invasions, the time factor for the development of a reaction from the biotic environment will become important. There are two classic experiments known in history with different endings of the confrontation of biological species. In Gause’s experiments with ciliates, the infused predator, after brief oscillations, completely destroyed its resource, so its $r$-parameter became excessive for new conditions. Its own reproductive activity was not regulated by additional factors and, as a result, became critical for the invader. In the experiments of the entomologist Uchida with parasitic wasps and their prey beetles, all species coexisted. In a situation where a population with a high reproductive potential is regulated by several natural enemies, interesting dynamic effects can occur that have been observed in phytophages in an evergreen forest in Australia. The competing parasitic hymenoptera create a delayed regulation system for rapidly multiplying psyllid pests, where a rapid increase in the psyllid population is allowed until the pest reaches its maximum number. A short maximum is followed by a rapid decline in numbers, but minimization does not become critical for the population. The paper proposes a phenomenological model based on a differential equation with a delay, which describes a scenario of adaptive regulation for a population with a high reproductive potential with an active, but with a delayed reaction with a threshold regulation of exposure. It is shown that the complication of the regulation function of biotic resistance in the model leads to the stabilization of the dynamics after the passage of the minimum number by the rapidly breeding species. For a flexible system, transitional regimes of growth and crisis lead to the search for a new equilibrium in the evolutionary confrontation.

Eco-epidemiological models provide insights into factors influencing disease transmission and host population stability. This study developed two eco-epidemiological models to investigate the impacts of prey refuge availability and an Allee effect on dynamics. Model A incorporated these mechanisms, while model B did not. Both models featured predator – prey and disease transmission and were analyzed mathematically and via simulation. Model equilibrium states were examined locally and globally under differing parameter combinations representative of environmental scenarios. Model A and B demonstrated globally stable conditions within certain parameter ranges, signalling refuge and Allee effect terms promote robustness. Moreover, model A showed a higher potential toward extinction of the species as a result of incorporating the Allee effect. Bifurcation analyses revealed qualitative shifts in behavior triggered by modifications like altered predation mortality. Model A manifested a transcritical bifurcation indicating critical population thresholds. Additional bifurcation types were noticed when refuge and Allee stabilizing impacts were absent in model B. Findings showed disease crowding effect and that host persistence is positively associated with refuge habitat, reducing predator – prey encounters. The Allee effect also calibrated stability via heightened sensitivity to small groups. Simulations aligned with mathematical predictions. Model A underwent bifurcations at critical predator death rates impacting prey outcomes. This work provides a valuable framework to minimize transmission given resource availability or demographic alterations, generating testable hypotheses.

This article is dedicated to a comparison analysis of optimization methods, in order to perform an interval estimation of electrical energy technical losses in distribution networks of voltage 6–20 kV. The issue of interval evaluation is represented as a multi-dimensional conditional minimization/maximization problem with implicit target function. A number of numerical optimization methods of first and zero orders is observed, with the aim of determining the most suitable for the problem of interest. The desired algorithm is BOBYQA, in which the target function is replaced with its quadratic approximation in some trusted region.

The article presents the results of computer simulations aimed to assess the influence of tree spatial locations (planting schemes) on the productivity and the dynamics of soil fertility in forest plantations. The growth of aspen (Populus tremula L.) in plantations with short rotation (30 years) was simulated in the EFIMOD system of models with the soil and climatic data matching forested lands in the Mari El Republic. The outcome reveals that higher biomass rates, increase in soil organic matter stocks, and the minimal loss of soil nitrogen can be obtained when the distance between trees in the row equals 1–4 m and 4–6 м in aisles.

Technical diagnosis’ current trends are connected to application of FEM computer simulation, which allows, to some extent, replace real experiments, reduce costs for investigation and minimize risks. Computer simulation, just at the stage of research and development, allows carrying out of diagnostics of equipment to detect permissible fluctuations of parameters of equipment’s work. Peculiarity of diagnosis of rolling equipment is that functioning of rolling equipment is directly tied with manufacturing of product with required quality, including accuracy. At that design of techniques of technical diagnosis and diagnostical modelling is very important. Computer simulation of cold rolling of strip was carried out. At that upper working roll was doing vibrations in horizontal direction according with published data of experiments on continuous 1700 rolling mill. Vibration of working roll in a stand appeared due to gap between roll’s craft and guide in a stand and led to periodical fluctuations of strip’s thickness. After computer simulation with the help of DEFORM software strip with longitudinal and transversal thickness variation was gotten. Visualization of strip’s geometrical parameters, according with simulation data, corresponded to type of inhomogeneity of surface of strip rolled in real. Further analysis of thickness variation was done in order to identify, on the basis of simulation, sources of periodical components of strip’s thickness, whose reasons are malfunctions of equipment. Advantage of computer simulation while searching the sources of forming of thickness variation is that different hypothesis concerning thickness formations may be tested without conducting real experiments and costs of different types may be reduced. Moreover, while simulation, initial strip’s thickness will not have fluctuations as opposed to industrial or laboratorial experiments. On the basis of spectral analysis of random process, it was established that frequency of changing of strip’s thickness after rolling in one stand coincides with frequency of working roll’s vibration. Results of computer simulation correlate with results of the researches for 1700 mill. Therefore, opportunity to apply computer simulation to find reasons of formation of thickness variation of strip on the industrial rolling mill is shown.