Vol 23, No 3 (2024)

At the preliminary stage of aircraft design, it is usually required to solve the problem of insufficient initial data for applying traditional algoristic-type mathematical programming models. In many cases, numerous input parameters cannot be accurately specified at the time of making design decisions. If the inaccuracy of parameters is not taken into account, the actual values of target functions may differ significantly from the calculated ones when solving optimization problems. In this regard, the issue of current interest is the development of algorithms to improve the reliability of design decisions under conditions of epistemological uncertainty when experts engage in the formation of initial data. The paper considers the problem of selecting aerodynamic characteristics and engine parameters of maneuverable aircraft under conditions of uncertainty associated with inaccuracy of expert data. The applied problem under consideration is further complicated by the necessity to include “black box” models in the algorithms being developed. The paper proposes algorithms that apply the uncertainty theory together with “black box” models that implement optimization calculation techniques derived from previous engineering practice of aircraft design. Using these algorithms, experts are able to set uncertain parameters whereby the lack of data is factored in using uncertainty distribution functions. In cases of monotonicity of uncertain parameters in target functions, application of the uncertainty theory provides a significant reduction in computational costs compared to the method of statistical modeling in optimization calculations. The paper presents the results of computational studies of the developed algorithms. A genetic algorithm (mathematical optimization solver) is used to optimize the search for design solutions. Pareto frontiers are obtained for different confidence levels enabling to make design decisions including values of aerodynamic characteristics and engine parameters of maneuverable aircraft.

The problem of selecting suboptimal parameters of an electric propulsion system as part of a spacecraft, ensuring a geostationary orbit raising mission using a Soyuz-5 launch vehicle at the initial launch stage, is investigated. An expression is obtained for the main optimality criterion – the payload relative mass. An algorithm is obtained for solving the problem of parametric optimization of an electric propulsion system as part of a hybrid transportation system. The task of selecting the optimal electric propulsion engine for launching a spacecraft with an electric propulsion system to a geostationary orbit using the launch vehicle under consideration is solved. A design ballistic calculation and a comparative analysis of the obtained data are performed.

In this paper, a novel algorithm is proposed to accurately estimate pitch acceleration that is crucial for moment coefficient estimation of the mathematical model of aircraft and control design in the presence of measurement noise. The angular velocity of the body as well as the Euler angles provided by the navigation system are used to interpolate the attitude trajectories using an algorithm based on the Hermite-spline polynomial. By differentiating the resultant trajectory function, the angular acceleration can be estimated accurately. This paper also analyzes a well-known method-Poplavski method based on polynomial regression, developed by the Russian scientist B.K. Poplavski to estimate derivatives. The simulation results obtained from the novel algorithm are compared with those obtained using the Poplavski method. The results verified that the novel algorithm that uses both pitch angle and angular velocity provides better accuracy in estimating pitch acceleration than the Poplavski method does, regardless of the sampling rate, which is very important in numerical differentiation and the noise level.

The article describes the possibility of determining the damping coefficient of a support with an elastic ring based on dry friction forces using a special test bench. The forced excitation force is set by the oscillations of a compact speaker installed on top of the oscillating mass through a U-shaped crossbar. The object of the study is a damper with an elastic ring, that is a thin-walled ring with evenly distributed bulges inside and outside, arranged in a checkerboard pattern. The damping coefficient is estimated using a device for simulating a rotor support, an acceleration sensor, an exciter speaker, a controller and a processing station. The amount of damping is estimated according to the width of the peak at the resonant frequency. A comparison is given of the magnitude of the damping coefficient obtained from the analysis of the resonance peak and from the decay rate during the impact experiment.

The article presents the results of the development of means for intelligent robust control of the parameters of a tribotronic rotor-support system with a tapered bearing with a removable bush. The proposed controller is implemented on the basis of deep Q-network reinforcement learning (DQN) synthesized on the basis of a numerical model of a rotor support system. The control strategy involved simultaneous control of the shaft position and friction in the lubrication layer. Methods for control synthesis are presented for both a deterministic system and a system with stochastic parameters. In the latter case, a controller synthesis technique is proposed that takes into account uncertainties in the system at the training stage. Testing of the resulting controllers shows the better ability of a controller trained to take into account uncertainties to cope with variable loads, as well as predict possible changes in the system and proactively transfer the system to more advantageous states.

The problem of finding the fatigue characteristics of a composite material based on test results is considered. The results of endurance tests of unidirectional polymer composite materials with different initial stiffness, breaking stress and working cycle stress were used as the initial data. As a mathematical model of stiffness degradation, a nonlinear ordinary differential equation with five unknown parameters is used, reflecting characteristic changes in the properties of the material. It is required to find such parameter values that the solution of the differential equation should describe the available test results with sufficient accuracy. The solution procedure is reduced to the problem of optimizing the objective function, the value of which characterizes the achieved accuracy. As optimization methods, a method simulating the behavior of a flock of moths and a method of sequential reduction of the search set were used. A step-by-step algorithm for finding unknown model parameters is proposed, and numerical results of processing input data containing information on changing the elasticity modulus of the composite material in the course of applying load cycles are presented.

The article presents the results of optimization of the work process of a single-stage axial turbine in order to increase its efficiency. During optimization, it was necessary to preserve the construction of the original turbine as much as possible. To solve this problem, a parameterization scheme for turbine blades and path contours was developed, taking into account the design and technological limitations. The turbine nozzle blade had an inside baffle. To control the possibility of placing the baffle, a special program was developed that automatically monitors the spatial position of the sections of the blade of the nozzle set. A post-processing program was developed to control the flow parameters at the turbine outlet in height. The efficiency and the vertical deviation of the angle of the outflow from the turbine from the original one were used as optimization criteria. The limitations were the mass flow rate of the working fluid and the total pressure ratio of the turbine. The problem was solved in several stages with different changing variables. As a result of solving the problem, it was possible to increase the turbine efficiency by 0.9%

The authors of the article developed a mathematical model of Stewart platform management. The angles of rotation of the servo shafts were obtained when setting various laws of motion of the mobile platform, in matrix mode. The hardware part of the prototype of the basic module of a scalable robotics system for modeling composite surfaces for dynamic tests was developed. The results of calculations of the maximum permissible load on the shafts of servos are presented. The CubeIDE settings for programming the STM32 microcontroller are given. The results of software development for the control of this prototype were obtained, namely, a library for controlling 6 servo drives under driver control was written. The problems that may arise during the above-described developments by future developers are considered, solutions to these problems are obtained. Detailed design features of this prototype are described, the control code of the servo drive is given; steps for further development of the final robotic system are considered