The paper considers the control of dynamic systems (DS) in situations with a high level of uncertainty caused by disturbances acting on the DS and interference in information channels during operation. Uncertainty results from the action of various external disturbing factors, uncontrolled changes in the object properties, and equipment failures and malfunctions. A peculiar feature of these control problems is that they are single events. In these conditions, the synthesis of positional control of dynamic systems is considered based on the minimax approach — worst-case design. The mathematical model of processes is characterized by disturbances and measurement errors known with a precision up to sets. The DS state vector is known with a precision up to membership in the information set as a result of solving the estimation problem. The proposed approach combines N. N. Krasovsky’s control concepts under information deficiency and A. A. Krasovsky’s concepts of building self-organizing systems. The “principle of a guaranteed result” was chosen to synthesize DS control. A control problem is solved in two stages in incomplete information. At the first stage, the state vector estimation problem is solved. The paper considers several implementations of estimation algorithms. It also proposes a minimax filtration algorithm based on the use of three filters (minimax filter (MMF), Kalman filter (KF), and guaranteeing filter (GF)) which can increase the estimation accuracy and make the proposed minimax filtration algorithm adaptable. The author discusses the implementation of the proposed algorithm and considers examples. The second part of the paper solves the control problem.

The paper considers the problem of fault estimation (identification) in nonlinear discrete-time stationary systems described by linear dynamic models under external disturbances based on interval observers. To solve the problem, a reduced order model of the original system of minimal dimension than that of the original system insensitive or having minimal sensitivity to the external disturbances is designed. This model is based on diagonal Jordan canonical form allowing obtaining one-dimensional model. Based on this model, the interval observer is designed consisting of two subsystems. The first subsystem generates the lower bound of the set of admissible values of the prescribed function of the system state vector while the second system generates the upper bound. The relations describing such subsystems are derived. The prescribed function is such that forms one component of the system output vector containing the variable which is a result of the fault occurred in the system. This is necessary to introduce a feedback in the interval observer which is created by the estimated system output. Based on the interval observer description, the variable is introduced connecting the lower and upper bounds and real value of the prescribed function which can be measured. Based on the introduced variable, the relation connecting the lower and upper bounds and real value of the prescribed function in neighboring moments of time is constructed. This relation is based for fault estimation. Since measurement noises are absent and the reduced order model is insensitive to the disturbances, all obtained relations are precise, and the resulting formula for fault estimation is precise one as well. The theoretical results are illustrated by an example of electro actuator model where the value of fault is estimated. Simulation results based on the package Matlab show the effectiveness of the developed theory.

The features of the structural and functional construction of an intellectual swarm system due to the specifics of the information interaction of its agents are analyzed. Discussed the following concepts of managing agents are given: individual agents implement individual movement processes and the swarm is considered as an unmanaged cloud formation; a collective movement of agents is performed, in which the swarm is a single controlled entity. The enlarged composition of the technical, information and software of the main components of the swarm system is given: the central control body of the system; local control bodies of overlay leaders; on-board navigation and agent control systems. It is shown that for multi-agent systems, it is fundamentally necessary to organize the flow mode of asynchronous supply of information blocks in the form of digital packets to computing equipment. With this in mind, a generalized scheme for organizing the functioning of asynchronous processes in a swarm system is constructed. This scheme is based on the use of hardware information interruption mechanisms associated with the supervisor of the operating system processes. The tasks of the swarm system supervisor are defined, which are to ensure initialization, priority launch for execution and mutual synchronization of main types of software processes. The essence of the method of pseudorandom adjustment of the operating frequency in the agent’s radio communication is revealed.

Industrial robots performing complex operations often require remote control. The operator must have access to configure the robot behavior, set operations, simulate operation execution before execution, synchronize robot and its digital model state, change the control mode if necessary. Virtual reality interfaces allow to control robots interactively and perform all the operations described above. The article proposes an implementation of a control system based on virtual reality interfaces, which allows real-time control of an industrial robot. The proposed solution has been tested on two robots and includes a universal (iterative) inverse kinematics solver, a trajectory planner, a tasks scheduler, supports work in master-slave and trajectory modes.

The article considers an algorithm for controlling a group of aircraft providing a given location of aircraft in space at a given time. When controlling a group of unmanned aerial vehicles, it is often necessary to bring them to the specified positions at a given time. Reachability areas and optimal control methods can be used to bring aircraft to specified positions. The application of reachability domains for solving problems of controlling a group of aircraft is considered. The article also provides an analysis of the method of calculating the reachability areas and an example of calculating the reachability areas of a rocket. A problem for a group of aircraft is considered, for which reachability domains are used in a group way. Aircraft with specific characteristics and initial parameters are used for modeling. The task is solved in two stages. The reachability regions in the vertical plane are approximated by triangles. The equations were integrated by the Runge-Kutta method with a constant step. For an aircraft whose motion is determined by a system of equations with a control constraint under given initial conditions, it is necessary to define a control program that provides a minimum of functionality. Thus, the optimal control problem is reduced to a boundary value problem: to find a solution to a system of equations whose phase coordinates satisfy the initial conditions and boundary conditions. In addition, according to the maximum principle, the Hamilton function under optimal control should reach a maximum. Moreover, the control must satisfy the restriction. The construction of reachability areas and the choice of programs based on the maximum principle makes it possible to bring a group of aircraft to a given position at a given time.

The problem of generating smooth and achievable trajectories for the center of mass of unmanned wheeled platforms approximating a reference sequence of waypoints considering time is considered. A typical solution consists in spline interpolation of separate route sections with their subsequent stitching. At the same time, the problem of satisfying constraints on robot motion features such as velocity, acceleration, and jerk requires additional algorithmization. In contrast to labor-intensive analytical methods, this paper proposes a fundamentally new approach, simple in computational implementation, which provides dynamic smoothing of primitive trajectories. The principle of organization and method of designing an autonomous dynamic model (tracking differentiator) whose output variables, while tracking a primitive non-smooth trajectory, generate smooth curves whose derivatives do not exceed the design constraints of a particular robot and are achievable reference trajectories for it. Block control principle and smooth and bounded S-shaped sigmoidal local links are used to design the differentiator. The paper presents a procedure for setting up a three-block tracking differentiator, whose variables generate a smooth reference trajectory, as well as its first and second derivatives, in a signal pocoordinate form. It is shown that the developed procedure extends to tracking differentiators of any required order without limitation of generality. In particular, the structure and setting of a single-block tracking differentiator for obtaining express results at the stage of robot or polygon motion planning is specified. Numerical simulation results confirming the efficiency of the designed algorithms are presented.