The adaptive tracking control problem for the linear cascade system consisting of two subsystems is considered. The modification of the Speed bi-gradient method is proposed to improve both the accuracy and the robust property. The considered modification is performed by an extending the dimension of the output subsystem of a cascade system, and forming the information output as the generalized tracking error dynamics, and the virtual control synthesis as the local feedback of an information output. The fourstage design procedure of the indirect adaptive control is proposed. The achievement of the tracking control objective is proved by a Lyapunov method. The finite-time stability of the sliding manifold and the information output is ensured. Identification properties of a control law are investigated. Both the control law design and simulation results for the third order cascade control plant are presented.

The infrastructure required for collecting and distributing open data plays a vital role in the digital economy, serving as a valuable resource for fostering innovation through big data processing and artificial intelligence tech nologies. Unfortunately, several sectors, including the energy industry, lack a well-established ecosystem for implementing such innovations effectively. This paper addresses key challenges associated with the aggregation and utilization of open data in the electric power sector, while exploring potential solutions. Additionally, the paper provides a concise analysis of existing literature on organizing open data in the energy industry and examines the architectural aspects of foreign open data platforms designed for the electric power sector. The paper highlights the considerable focus on open data collection, storage, and provision, as well as the active resolution of both technical and regulatory issues in foreign contexts. Sources of open data in the Russian electric power industry and challenges associated with extracting data from heterogeneous sources are enumerated. The ecosystem approach to organizing an open data platform and the basic data monetization principles are discussed. The paper presents the key stakeholders of the platform and outlines the mechanisms for motivating their involvement. A platform architecture is proposed to meet the needs of stakeholders and ensure accelerated development of innovations in the energy sector. The use of a data lakehouse is recommended for efficient data storage in the platform. An example application on the basis of the open data platform is presented that forecasts peak load hours in regional power systems using machine learning. This application can be integrated into consumer energy management systems. Proposals are stated to refine the organizational and information support of open data of the electric power industry in order to increase the efficiency of their collection, storage, and processing on the basis of the digital platform.

The article deals with investigation of the dynamic characteristics of a four-wheeled mobile robot. The dynamic characteristics have been studied for various variants (configurations) of the arrangement of mecanum wheels when maneuvering along a nonlinear trajectory. Possible configurations for placing mecanum wheels in the robot are determined and their controllability is theoretically assumed by analyzing the state space matrix. An algorithm for controlling a mobile robot along a trajectory with changing initial values of the state matrix is propos ed. The dynamic characteristics of the robot were obtained: dependences of the positioning error, the angle of deviation of the robot body from the initial coordinates, and the angular speeds of the wheels for each variant. A comparative analysis of the obtained modeling results was carried out, as a result of which it was established that symmetric configurations with a full rank of the state matrix have the best controllability, and other configurations may have limited distribution. It is shown that the assessment of the controllability of the mecanum wheels configurations in a four-wheeled robot must be supported by the results of an experiment using a dynamic model of robot motion. As a method for increasing dynamic performance in transient and steady-state modes, it was recommended to use an astatic position loop, and an increase in the quality of regulation of the speed loop of the electric drives of the mecanum wheels can be achieved by using a PID controller, which is valid for any values of the state space matrix.

One of the urgent and key problems of the transport industry is considered. This is the problem of planning the routes of vehicles. The given problem can be described and formalized as the Traveling Salesman Problem (TSP) for many applications.

This problem consists in finding of the optimal route for a traveling salesman passing through the indicated cities at least once and with returning to the source city. In general, when planning such routes, it is necessary to solve the multiple traveling salesman problem (MTSP), which allows for more than one traveling salesman and more than one depot, their base point, where routes begin and end. As a combinatorial optimization problem, MTSP belongs to the class of NP-hard problems. This article presents a heuristic method for its solving on the basis of geospatial clusterization of the initial set of cities. First, an MTSP with a single depot is considered. A two-index mathematical formalization of this problem is given and the Miller-Tucker-Zemlin method is described. It reduced to the problem of integer linear programming. Metaheuristic methods for solving MTSP are discussed. A more complex problem an MTSP with several depots is being considered. A comprehensive two-stage method for solving this problem is described — the CFRS ("Cluster First — Route Second") method, which allows reducing it to the MTSP family with a single depot. Here, at the first stage, geospatial clustering of cities is carried out, for which it is possible to use various clustering methods, including the K-means method. At the second stage, for each built cluster, a depot is selected for its maintenance and routes are built to bypass all cities in this cluster. The clustering methodology is discussed as an effective tool for solving MTSP.

A numerical example of aviation logistics is given — the routing of flights of UAV group.

The paper examines the problem of creating a formation of autonomous underwater vehicles for the coordinated execution of a group mission. The proposed method is based on the construction of a probabilistic functional, which describes the problem of constructing a formation of vehicles and takes into account the possibility of collisions between them; the functional generates an artificial potential field that has a clear interpretation. The creating of the formation is implemented using the gradient principle of sequential optimization of the probabilistic functional. The main assumptions that are made when developing the method are given. In particular, it is assumed that the group of underwater vehicles is homogeneous, and the structure of the creating formation has a "leader-follower" organization. It is believed that all vehicles have access to information about the position and orientation of the leader and other vehicles. The creation of a formation occurs under conditions of continuous movement of the entire group of vehicles. The maximum and non-zero minimum possible speeds of all vehicles are known. In the initial state, before the formation begins, all underwater vehicles are located in arbitrary places in the water area within a certain reasonable distance. In the work, based on standard reasoning, a functional is constructed in general form, which has the meaning of the probability of creating a given formation by a group of vehicles, provided that there are no collisions of the vehicles with each other during the movement. Specific types of probability distributions included in the general functional are introduced and justified. In general, an explicit expression for the gradient of this functional with respect to spatial variables is calculated. A law is derived and a mechanism is given to control the speed of underwater vehicles until the formation is completed. The considered method has a simple software implementation and demonstrates high efficiency, which makes it possible to control the formation of a large group of underwater vehicles in real time. Using the example of a group of 11 underwater vehicles, simulation results are presented that confirm the performance and indicated efficiency of the proposed method.