The problem of controlling the output of a multidimensional object under conditions of the current uncertainty of the parameters of the object and the action of external uncontrolled disturbance is considered. A solution to the problem is proposed based on the use of an identification-approximation approach, also called as an approach using "simplified” adaptability conditions. It is based on the use of an algorithm for the current parametric identification of the object model, an implicit reference model and approximation of the dynamics of the object. The latter is performed at two levels: a structural approximation, which assumes the use of a sufficiently simple model in the structure of the customizable model in the identification algorithm, as well as a parametric approximation, which assumes the " description” of the model by current parameter estimates that do not coincide with their exact values. In this case, the criterion for the accuracy of approximation for the control synthesis problem is the convergence of the identification discrepancy with some fairly simple requirements for parameter estimates during control. This provision can be interpreted as a refinement of the well-known "certainty equivalence principle,” which requires asymptotically accurate estimation of unknown parameters. An additional advantage is the speed of adaptability and the non-need for a constantly exciting regressor ("richness” of the input signal). The conditions for suboptimality of the control law are also determined. These requirements are simple enough for practical applicability. An example of computer simulation in the Matlab environment is given.

The problems of transforming the original nonlinear system into the special linear system (reducing model) and fault diagnosis are studied. The transformation is realized based on Li derivative, and the model insensitive to the external disturbances is derived. Such a model allows to obtain a linear equation for the error that is important for solving some practical problems. To solve the problem of fault diagnosis, the interval observers are used. The advantage of the interval observer is that they allow to take into account many types of uncertainties: the external disturbances, measurement noise, and parametric uncertainties. The interval observer is based on the reducing model which initially is designed in the identification canonical form, and then it is transformed into the diagonal Jordan canonical form with negative eigenvalues since such a form has properties necessary to design the interval observer. The interval diagnostic observer creates two residuals such that when there are no faults, one residual is non-positive, the second one is non-negative. If zero lies between these residuals, a decision that there are no faults is made. The theoretical results are illustrated by an example of electro actuator model where the value of active resistor of the motor winding is estimated under the assumption that if the resistor is in its tolerance, then the fault is absent. Simulation results based on the package Matlab show the effectiveness of the developed theory.

A possible solution to the problem of monitoring the onset of an earthquake preparation process (EPP) is considered by combining the analysis of seismic-acoustic and seismic signals. In order to conduct experiments to monitor the onset of the earthquake preparation process, a network of stations was built in which shafts of suspended oil wells (1500—5000 m) were used as inverted antennas as a communication channel to obtain seismic and seismic-acoustic information from deep strata of the earth. It is found that when filtering seismic signals using traditional technologies, informative attributes that occur at the onset of the earthquake preparation process are lost. It is also found that the onset of the EPP is reliably recorded based on estimates of the noise variance and the cross-correlation function between the useful seismic-acoustic signal and its noise. It is also established that over a period of time, it is possible to repeatedly record continuations of the EPP based on the same characteristics of seismic signals. Based on the specified informative attributes about the beginning of the EPP, a hybrid intelligent system is proposed, where, using combinations of stations that respond to seismic processes, information is generated that allows seismologists to use them as a tool to identify the zones of the focus of the expected earthquake. The importance of the study is that the results obtained have been experimentally confirmed over a long period of time. It was found that informative attributes that emerge at the beginning of the earth-quake preparation process are lost during the filtering of seismic signals by traditional seismic stations.

Robot swarm control is one of the most important tasks in the field of unmanned vehicles. The paper presents an architecture of semi-centralized system that allows one to control an entire robot swarm as a single entity with a single remote controller. The proposed system integrates intragroup communication, Local Voting Protocol-based algorithm for formation m aintenance, a method to overcome noises and communication breaks between some of the robots and the remote controller. Conducted experiments demonstrate the efficiency of the proposed system even in complex and unpredictable environments.

To improve the speed control of brushless DC motors (BLDCs), a method for tuning the PID-controller parameters based on the metaheuristic algorithm 3S Optimizer (3SO) is proposed. BLDCs are worthy competitors to AC drives due to the absence of brushes and a commutator. Electronic commutation of the motor ensures high operating speed, and the behavior is controlled by digital systems. The accuracy of BLDC speed control is of paramount importance to ensure the efficient operation of equipment, devices and products in which the motor is built. PID-controllers are widely used in industrial applications due to their efficiency, simplicity and versatility. However, empirical strategies for tuning PID-controller parameters are not always optimal. Ma ny methods based on metaheuristic algorithms have been proposed for fine-tuning, allowing the control system to learn and adjust parameters in real time, effectively responding to environmental changes. The method proposed in this paper is based on the recently proposed metaheuristic algorithm 3S Optimizer. The method solves the problems of slow convergence and low accuracy, which are typical for traditional PID-controllers. The integral of the squared error is chosen as the objective function of optimization. The following parameters are chosen as constraints: overshoot, transient time, and rise time. Constraints are included in the objective function as penalties. Thus, the problem of minimizing a function with constraints is reduced to the problem of finding the minimum of a function without constraints. The PID-controller optimization program is implemented in the MATLAB environment. For modeling, the Permanent Magnet Synchronous Machine BLDC motor blocks and the Universal Bridge inverter block, available in Simulink, were used. The experiments conducted, which involved a PID-controller with non-optimized parameters and controllers optimized by the 3SO algorithm and a genetic algorithm, showed the superiority of our method.

This study provides a review of existing scientific works on the problem of scheduling heterogeneous orbital constellations. The relevance of planning the operation of such constellations is driven by several factors related to the rapid development of space technologies and the increasing number of satellites in orbit. Modern orbital constellations consist of spacecraft of various types designed to perform different tasks: Earth remote sensing, communications, navigation, and others. These satellites may belong to different opera tors and have varying technical specifications, which makes their efficient utilization extremely complex and labor-intensive. Furthermore, the planning of heterogeneous constellations is particularly relevant in the context of the growing number of commercial and government satellites, creating high competition for space resources. Rational planning enables minimizing costs, improving the quality of services provided, and enhancing the safety of spacecraft operations. In this regard, there has been a rapid increase recently in the number of spacecraft scheduling methods that can effectively account for the heterogeneity of orbital constellations and ensure their coordinated operation. This work continues the previously conducted review of publications released up to 2019 and focuses on the development of methods over the last five years, from 2019 to 2024. The study formulates the task of creating a digital platform that manages orbital constellations from different manufacturers to fulfill requests from users. An analysis of existing approaches to planning spacecraft constellations is carried out, highlighting their advantages and disadvantages, as well as evaluating their practical feasibility for solving the stated task. Based on the results of the analysis, conclusions are drawn regarding the need to develop a new approach to scheduling the operation of orbital constellations. Proposals are made for further research and development of methods and tools for spacecraft scheduling.