A highly important place in the theory and practice of automatic systems occupy the problems of synthesis of automatic regulation systems (ARS) based on the requirements for the dynamic quality of regulation processes. For class of linear stationary ARS such requirements are imposed upon the type and parameters of its transition characteristic which is uniquely determined by its transfer function (TF). In this connection the setting of problem of ARS synthesis with desired TF, corresponding to the given amplification coefficient, zeros and poles of the synthesized system is regularity. The given problem is worth while to call as the control problem of zeros and poles of ARS. In the present paper consists into two parts, the questions of control of zeros and poles ARS, which are important for engineering applications are considered. A critical analysis of the known compensation and compensation-modal regulation schemes is given. And also the new circuit solutions combining the functionality possibilities of compensation and modal approaches are proposed. The first part of the article the effect of compensation of zeros and poles of control objects in ARS is analyzed. The understanding of this effect gives the representation of the system of canonical structure of R. Kalman, according to which the compensation of zeros and poles of object does not mean their physical liquidation. As a result of compensation, they become the poles of its unobservable and unmanageable parts, which will be tell upon the regulation processes in the conditions of disturbances of the state of control object. The given effect and its negative results are clearly detected in the classical method of constructing of controllers on a priori given (desired, reference) TF of closed ARS. The influence of the factor of non-minimal phase zeros on the dynamics of control systems is studied. The effect of negative ejection in the transition characteristic of the system is described and its quantitative assessment is given for the case of a single real right zero. In the second part of the article the well-known methods for ARS synthesis with desired TF, based on use of polynomial calculus apparatus are considered and analyzed. New compensatory modal methods which may be of interest in engineering applications are proposed.

The problem of the synthesis of robust control systems with a high gain and, in particular, optimal by the criterion of quick action, which allow optimal control by the accuracy of regulation of multidimensional non-linear dynamic objects with functional uncertainties, is discussed. A method is proposed for the analytical construction of optimal control systems by the criterion of quick action for a wide class of multidimensional nonlinear dynamic objects with functional uncertainties, unstable objects; no minimal-phase objects, neutral object and objects with differentiation properties. Simplicity and universality, mathematical rigor and physical validity of this method consists in usingR.R Be llman’s method and decomposing the optimal by the criterion of quick action problem into a series of simple first-order simple problems of the same type. A theoretically comprehensive solution to the robust control problem is given by the idea of constructing systems that are stable with an unlimited increase in gain. In this case, optimal systems have stability properties. Such systems are synthesized using quadratic quality functionals that are not explicitly dependent on the control signal and the restriction on the control signal. It is significant that, in contrast to continuous systems with unmeasurable perturbations and a little-known object, in which the conditions of invariance require the use of infinitely large gains, in relay (discontinuous) systems, the equivalent effect is achieved using finite control actions. Since the performance problem is a particular problem of the accuracy of reproducing the input action on the control object, the established control error (including all error coefficients: by position, speed, acceleration, jerk, etc.) is theoretically strictly equal to zero if external and internal interference, acting only on the control object, but not on the control system, including sensors of state variables of the control object or the input signal of the task. However, due to the inertia of the object, there can be no talk of accuracy in the transient process of working out the input signal of the task, even if it is optimal in terms of the criterion of fast action.

In this paper the problem of identification algorithm for unknown frequency of a sinusoidal disturbance for a linear plant was considered. This problem is solved in the class of plants with known parameters and a measured of state variables. Regarding the frequency of the sinusoidal disturbance was assumed that the it upper limit is known. Despite the seeming triviality the considered problem is difficult. Using of numerous methods for parameters identification of the measured sinusoidal signals does not give success if the amplitude of sinusoidal disturbance is time-varying. In this paper we will assume that amplitude is the product of an unknown constant by a known strictly positive function of time. For the time-varying strictly positive function we will suppose that the upper boundary of its derivative is known. We note that such assumption on the amplitude of a time-varying sinusoidal disturbance is not a mathematical abstraction. Similar models arise in fault-detection strategy in DC/ AC conversion. It is well known that alternative energy sources require a high level of integration into the electrical power grids. For this purpose, DC/AC and AC/AC power converter are used to provide the coupling, synchronization and appropriate power flow to the electrical networks. These power converters employ high-frequency switching to manipulate the energy conversion process. As a result of a constant operation and load transients, the power switches in the DC/AC and AC/AC topologies are facing voltage, current and temperature stresses that could lead to a fault. After a fault, the DC/AC and AC/AC power converter will not be able to provide a symmetric voltage and current to the electrical network and, consequently, the faulty converter will induce harmonic noise. By evaluating such harmonic noise / disturbance, emergency situations can be avoided. In this paper the asymptotic convergence of the estimation of the frequency of the perturbing effect to the true value is proven. For clarification of design procedure of estimation algorithm and performance illustration an example was presented. The computer simulation results are demonstrating the achievement of a given purpose.

This study is devoted to development of a neural network based control system of robots group. The control system performs estimation of an environment state, searching the optimal path planning method, path planning, and changing the trajectories on via the robots interaction. The deep learning neural networks implements the optimal path planning method, and path planning of the robots. The first neural network classifies the environment into two types. For the first type a method of the shortest path planning is used. For the second type a method of the most safety path planning is used. Estimation of the path planning algorithm is based on the multi-objective criteria. The criterion includes the time of movement to the target point, path length, and minimal distance from the robot to obstacles. A new hybrid learning algorithm of the neural network is proposed. The algorithm includes elements of both a supervised learning as well as an unsupervised learning. The second neural network plans the shortest path. The third neural network plans the most safety path. To train the second and third networks a supervised algorithm is developed. The second and third networks do not plan a whole path of the robot. The outputs of these neural networks are the direction of the robot’s movement in the step k. Thus the recalculation of the whole path of the robot is not performed every step in a dynamical environment. Likewise in this paper algorithm of the robots formation for unmapped obstructed environment is developed. The results of simulation and experiments are presented.

Permanent magnet synchronous motors (PMSM) are widely used in practice due to its high-energy efficiency, compactness, reliability and high regulation performance. When controlling a PMSM rotor speed, the main control principle is the principle of cascade control with PI-regulators, which includes an external control loop for speed and two internal loops for stator currents along the (d, q)-axes. There are attempts to eliminate the disadvantages of this principle using for the control laws synthesis of modern methods of nonlinear control such methods as linearization feedback, backstepping, predictive control, sliding mode control, methods of robust and adaptive control, fuzzy and neural network control, a combination of these methods etc. However, in most cases, the use of these methods are intended to by means of an appropriate method to synthesize a static or dynamic set points for the standard PI-controllers of rotor speed and currents. In this paper we propose to consider two approaches of synergetic control theory (SCT) to construct a robust control law of PMSM: a sliding mode control laws design by the SCT method with subsequent invariant manifolds aggregation and the principle of integral adaptation (PIA). These approaches implement vector control and are not guided by the standard structure of the principle of cascade regulation of PMSM. The proposed approaches simplify the stability analysis of the closed-loop system: stability conditions consist of stability conditions of functional equations of SCT and the stability conditions for finish decomposed system, which the dimension is substantially less than the dimension of the original system. From the results of the comparisons of synthesized the PMSM robust control laws, we can say that more preferable laws synthesized in accordance with the PIA. The theoretical positions of this paper are illustrated by the results of modeling, which are showing the fulfillment of the control tasks: the achievement of targets, robustness to the change of the PMSM load moment.

The article deals with the automation of the ergonomic examination procedure (EE) of the Data-Control Field (DCF) of the cockpit of promising combat aircraft using artificial intelligence technologies. A balanced combination of aircraft control algorithms, its complex of on-board equipment and weapons, as well as artificial intelligence technologies provides information support for the aircraft crew. The relevance of the ergonomic assessment of DCF at all stages of the aircraft designing and operation is noted. The features of the EE of the DCF of cockpit, goals and objectives, as well as methods of examination are described. EE are monitoring and evaluating the completeness and correctness of the implementation of ergonomic requirements for the designed aircraft and substantiating possible ways to improve the ergonomic characteristics of the aircraft. EE includes systemic and design issues, among which the important issues are the choice of DCF structure. EE technology elements are considered. The tasks of the automated EE system are listed: the assessment of human-machine interaction, quality of information support, the registration and assessment of cockpit geometric characteristics (visibility and reach) and operator’s functional state, formalization of parameters and the formation of an integral assessment. The system combines information, hardware and software into a single complex. A distinctive feature of the DCF EE is the a priori uncertainty of the source data. Models of the algebra of fuzzy sets allow to formalize the decision-making process during the EE. The integral assessment by the Analytic Hierarchy Process (AHP) method is described. AHP as a method for evaluating multicriteria alternatives is well known. The applicability of the method is noted in cases where the issuance of absolute estimates of alternatives by given criteria is difficult.