A method for estimation of stator and rotor resistances in induction motors is presented. The developed algorithm also allows to estimate the rotor flux. It is assumed that currents and voltages of stator windings and mechanical rotor speed are measurable and all the other parameters of the motor are known. The proposed method ensures a global boundness of all signals and exponential convergence of the estimates.

A method is proposed for a sinusoidal signal parameters estimation, when the time-varying amplitude of the signal is the product of a known function and unknown coefficient. A new parametrization approach is applied to obtaine linear regression model. The estimation algorithm for the model and initial signal parameters is synthesyzed on the base of standart gradient method. The parameters estimation errors are shown to converge exponentialy to zero.

The problem of improved convergence for algorithm of adaptive parameter adjustment is considered. Previously known results based on application of special dynamic filters with memory are expanded to the class of dynamic error model. Applicability of proposed algorithm for solving of adaptive control problems for linear time-invariant plants is demonstrated. Simulation results are presented.

A stable continuous system with multiple complex conjugate eigenvalues of state matrix is considered. The system is realized as a consecutive chain of identical oscillatory links, so that the eigenvalue multiplicity is equal to half of state vector dimension. The case under investigation presuppose that the eigenvalues spectrum is represented by a modified Butterworth distribution and lies in a sector not wider than 60о. It is found that free motion norm of the system may demonstrate a considerable deviation from a monotonically decreasing curve even at small imaginary part of eigenvalues. The deviation is the greater the smaller is the eigenvalue real part modulus and the greater is its multiplicity and the gain coefficient. An analytical solution to the problem of free motion system state vector norm is derived, the solution correctness is verified by computer modeling.

The problem of tracking of a multi-sinusoidal signal with unknown parameters is solved with the use of a robotic system. The main feature of the proposed approach is a fast frequency estimation using the dynamic regressor extension and mixing (DREM) method allowing to improve performance of simultaneous multiple frequencies estimation. The developed compensation algorithm makes it possible to solve the problem in the presence of time delays. Results of the experimental study and comparison analysis of the robotic tracking system based on DREM and classical gradient methods are presented.

The problem of synthesis of trajectory control in the presence of unmeasurable constant external disturbances is studied with the use of differential geometry methods. The problem is noted to be a reasonable extension of the classical trajectory control problem. The developed procedure for controller synthesis to solve the described problem is presented. The efficiency of the proposed controllers is demonstrated with results of computer modeling.

A parallel kinematics robot manipulator for dynamic manipulation tasks is developed and tested experimentally. Such systems are widely used in aviation and driving simulations, control automation, e. g. for quick sorting tasks. Advantages of robotic manipulators with parallel kinematics are their high speed and positioning accuracy when working in a limited workspace. Based on the described results, a Stewart robotic platform with two degrees of freedom equipped with a vision system was built. The system integration is implemented in MatLab/Simulink. A mathematical model of the system is presented. Two algorithms of output adaptive control are extended to the class of discrete systems are tested, comparative analysis of the algorithms is performed.

An algorithm for visual navigation of autonomous mobile robot and determination of its position in uncertain environment using computer vision system is considered. The algorithm employs comparison of three-dimensional scene images based on comparison of the local images.

It is noted that many of hydrolithospheric processes are described by partial differential equations, and corresponding mathematical models do not have analytical solutions; in several cases, there are no mathematical models, too. Therefore, to solve a practical problem, such as synthesis of control system of flow rate of producing wells or formation of an optimal technological modes of operation field, it is necessary to develop an approximate model. A method of approximating model construction for a hydrolithospheric process is presented. The proposed approach is based on the methods of frequency synthesis and distribution of high-quality modes theory. Design of distributed regulators using the developed method is reported to ensure required quality parameters.

The problem of synthesis of control systems for hydrolithospheric process is considered. It is noted that practical creation of automated control systems for production wells providing high-quality flow of technological processes, calls for development of theoretical methods of distributed regulators design. A method for synthesis of distributed control system for hydrolithospheric process is proposed; the approach is based on combination of the conventional frequency synthesis method with qualitative theory of modes distribution.

A control system of walking robot Darwin-OP moving along a given trajectory is presented. The robot trajectory is a red line recognized by built-in videocamera. The control system consists of PD controller for angular positions of the robot head (for tracking the desired trajectory) and PD controllers for the longitudinal and transverse velocities of the robot. Evaluation of the effectiveness of the proposed solution is carried out by a third-party videocamera mounted above the robot. Experimental results demonstrate a small enough deviation from the desired trajectory.

For an object with delay, a new structural schematic of system of robust control with compensation of slowly changing perturbation at the object output is proposed. The object transfer functions are supposed to be stable or related to the boundary of aperiodic stability. To ensure the system robustness, predictor in the control loop is replaced by a nominal servo system in which a signal for disturbance compensation is generated. The proposed approach is reported to allow for realization of a rough system in relation to the uncertainty in the delay magnitude and parametric uncertainty of the transfer function. Construction of robust regulators in the traditional class of control laws is analyzed. The necessity of roughness of the main control loop is demonstrated.

Non-linear mathematical models of biochemical wastewater treatment with activated sludge are developed. The proposed approach is based on the dynamic models by Monod, Haldane, and Canales, with environment temperature considered as the influencing external factor. The development of biocenosis takes place in a confined space of the reactor under certain technological limitations and assumptions. Dependence of the growth rate of microorganisms on the temperature of the environment is based on the empirical Van't Hoff equation. Results of model calculations are presented for four temperature regimes, change of regime is performed by gradual increase and subsequent decrease in temperature to the set values. The families of graphs of transient processes of substrate and active sludge concentrations under various temperature conditions are demonstrated. Optimal temperature conditions corresponding to the most favorable conditions for the development of biocenosis of activated sludge and providing the most effective purification are determined. The simulation results confirm the sensitivity of the system to temperature changes. The obtained results are recommended to account for in analysis of nitrification and denitrification models, which are characterized by higher dynamic orders, and in design of a control system to improve water quality and reduce the time spent on biological treatment.

A system of management and control over safe energy supply is considered. Critical situations related to explosion and fire safety at sites associated with human activity are analyzed. The most important reasons reducing the total level of explosion and fire safety of an object are found in situation when simultaneous exploitation of power supply and gas supply systems takes place. Requirements to the management and control system for safe power supply are established. A method and schematic of a safe system are proposed, a description of the algorithms of the system operation is presented.

Various ways of using cognitive technologies in modern control systems for primary oil refining process are considered. A general schematic of rectification column as an object under the control is demonstrated, an information about possible problems in monitoring and managing of the refining process is presented. Modern methods of cognitive control system design for primary oil refining are analyzed. A variety of options for building a cognitive control system are described, which can be combined with an existing system into a software-algorithmic complex.

An intellectual agent that solves the task of finding the maximum of the smell function of in threedimensional space is considered. The direction of movement of the agent depends on the inertia of decisionmaking. A model of the search with the account for inertia of the trend generation process and resistance is developed. Experimental data and simulated results obtained with the use of the model of inertial agent of search are presented.