A class of dynamical systems with a single nonlinearity considered. The S-synchronizability concept of input introduced. It is shown that S-synchronizability is a condition for the structural identifiability of a nonlinear system. The decisionmaking on structural identifiability based on the properties analysis for a special class of geometric frameworks. Geometric frameworks reflect properties of the nonlinear dynamic system. Requirements for the model allowed us to obtain a geometric structure based on the input and output data considered. The constant excitation effect of input on the structural identifiability of the system is studied. The constant excitation effect of input studied on the structural identifiability of the system. Nonfulfillment the constant excitation condition gives a nonsignificant geometric framework. Various types of structural identifiability based on structure analysis considered. The concept of d-optimality described properties of the geometric structure introduced. Conditions for non-identifiability of nonlinear system structure obtained if the d-optimality of the geometric framework does not hold for the given properties of the input. Methods for estimating identifiability of the system and determining the identifiability area under uncertainty proposed. The proposed approach is generalized to the system having two nonlinearities. Conditions for partial structural identifiability obtained. Structural identifiability features of this class systems noted. The method for estimating the structure of the system proposed when the condition of structural identifiability satisfied. It has shown how the phase portrait used to estimate the system non-identifiability. A method proposed for constructing the structural identifiability domain of the system. Proposed methods and procedures are applied to study systems with Bouc-Wen hysteresis and two nonlinearity.

In this work, for linear stationary one-dimensional control objects, the inverse problem of analytical design of optimal controllers (ADOC) is considered, which consists in determining the weight coefficients of the quadratic functional of the optimality of the control process that provide the closed-loop control system with the specified values of the time of transient processes and overshoot. The time of the transient process (regulation time) of the synthesized system is understood in the sense of the classical theory of automatic control and is determined using a " tube" , the value of which is taken, in contrast to known works, equal to the required (desired) small value of the system overshoot of a few percent (2—5 %). The equality of the percentage values characterizing the " tube" and the desired overshoot of the synthesized system is a necessary condition for the maximum response rate of linear dynamic systems and, accordingly, ensures the unambiguity of the solution of the considered inverse ADOC problem in the class of fast-response systems. The proposed solution method provides for the transformation of the ADOC problem to the canonical form, in which the control object is described by a matrix differential equation in the Frobenius form, and the quality functional is defined as the integral of the sum of the products of the object’s canonical phase coordinates, as well as the square of the control signal with appropriate weight coefficients. It is shown that the solution of the inverse canonical ADOC problem is determined by the values of only three nonzero weight coefficients of the criterion, and one of them has a single value. The values of the other two coefficients are proposed to be found in the process of modeling the synthesized optimal control system from the conditions of providing for it a given control time and a given overshoot. To obtain numerical estimates of the two main weight coefficients of the quadratic quality criterion, the solution of the ADOC problem is considered with the limiting increase in the values of these weight coefficients. By the limiting solution of the ADOC problem, the transfer functions of dynamic systems with the limiting (maximum) speed are determined, which have a given overshoot of 4.321 %. The dynamical systems described by these transfer functions are called modified Butterworth filters due to the fact that the well-known Butterworth filters are obtained as their special case with a zero value of a certain constant. The parameters and indicators of the dynamics of these filters up to the sixth order are presented in the table. Using the indicators of Butterworth filters, numerical estimates of the weight coefficients of the quadratic quality criterion are established. Transfer functions of modified Butterworth filters are recommended to be used as reference transfer functions of synthesized high-speed control systems.

This paper considers comparative evaluation of recent methods for grip point determination for manipulations with objects in the scene. This research is aimed to compare and evaluate the modern approaches of grip point determination, when this process is aided by computer vision. The methods of object gripping, considered in this paper, are employed in connection with depth map composition, backed by neural network model ResNet-50, which allowed to omit application of specific depth sensors in the course of experiments. This research shows dependencies of successful grip probability from the things being manipulated. Probability scores, averaged over different types of objects for the methods GPD, 6-DOF GraspNet, VPG, were, accordingly, 0.690, 0.741, 0.613. The paper also considers dependencies of successful grip probability from object sizes, distances from the capturing camera and target objects in the scene, luminosity levels, as well from the angles of scene inspection along the vertical axis. In terms of the considered methods GPD, 6-DOF GraspNet, VPG, non-linear increasing dependencies are revealed for object type-averaged probabilities of successful grip from luminosity level of the scene. It was also discovered, that the dependencies of successful grip for all the other parameters are non-linear and non-monotonic. The ranges of the values for scene parameters under consideration are defined in this paper, which ensure the highest probability values for object grip in these approaches. Upon the results of the performed experimental evaluation, the 6-DOF GraspNet solution showed the best performance for the vast majority of the considered parameters of the scene. The approach, presented in this paper, is the preferable way for solution of grip point problem, in context of methods, which assume depth map reconstruction without specific equipment.

The paper considers a group of animates (bio-inspired abstract models or technical devices) that use the visual analyzer described by the authors earlier. The visual analyzer recognizes the scene observed by the animat, determines the class of the situation and selects the corresponding behavior. The analyzer is based on the" language of poses" , borrowed from some species of ants, which allows them to visually inform other individuals of their condition. The first proposed algorithm describes a visual memory mechanism that allows an animat to remember seen objects for some time and select its behavior in a more stable way compared to a basic visual analyzer. The second algorithm describes a group recognition approach. Robots are able to exchange information about the scene they are observing presented in the form of a graph using local communication. The robot, receiving such information from its neighbors, is able to expand its picture of the world and more correctly choose its behavior based on the recognized situation than if it only had its own data. A demonstration task was set to test the efficiency, approximately simulating a colony of ants that gather food in a certain area. Colony, nest, food, and enemy individuals are modeled in the developed simulation environment. Group efficiency was defined as the amount of food collected over the allotted time period. Animates using the visual memory algorithm showed an increase in efficiency for all the studied memory parameters. Moreover, the dependence is not monotonic, and there is a certain value at which maximum efficiency is achieved. The use of the group recognition algorithm also showed an increase in efficiency compared to the basic visual analyzer. The experiments were carried out for different distances of local interaction. As with memory, there is a value of interaction distance at which the maximum efficiency is achieved. The combination of both algorithms also has interesting results. The experiments showed that the smaller the memory of the robot, the greater the increase in efficiency from using the collective recognition algorithm.

For multi-criteria design problems of complex mechanical systems with a large number of control parameters, technical constraints, and quality criteria, the search for Pareto solution domain takes quite a lot of time varying from hours to days. In fact, the decision-maker (DM) desires to examine a small number of reasonable Pareto optimal solutions in order to understand the problem itself and control the decisionmaking in a simple manner. This paper presents the improvement of a visual interaction analysis method or VIAM developed by the authors with the aim of providing a tool for DM to define the optimal and mutually-agreed solutions in the multi-criteria decision making (MCDM). Indeed, VIAM allows for evaluating the distribution domain of the Pareto optimal solutions defined by the genetic algorithm, which supports the DM to set additional thresholds for the objectives to filter the desired solutions and suggest to shrink or expand the threshold to control the search. In case of mutually-agreed solution non-existence, VIAM allows for providing instruction to reestablish the multi-objective problem that new Pareto solution domains can be found as desired by the DM. Based on VIAM, a visual interaction analysis tool or VIAT was developed by means of Matlab. VIAT was then used for the multi-criteria design of slider-crank mechanism for an innovative fruit vegetable washer with three objectives. Comparative study on the obtained results from VIAT with the existing design option and the obtained solution from the traditional method "concession by priority" has shown the effectiveness of the method proposed in this paper. VIAT is actually a very user-friendly tool that makes the multi-criteria design more practical especially for the mechanical system.