Automation Control Theory Perspectives in Intelligent Systems

In this paper, color image encryption algorithm based on improved RC4 and chaotic maps is proposed. In proposed algorithm, the classic RC4 algorithm in cryptography is improved, and then applied to proposed encryption algorithm. Firstly, the original image is divided into some sub-blocks. Then, the improved RC4 algorithm is applied to the operation between the adjacent two sub-blocks, thereby changes the value of pixels. Finally, the image is scrambled by logistic map. Experimental results show that the original image has a big change and a flat histogram after encrypted, and that the proposed algorithm has an enough large key space and a very high sensitivity to the key.

Computer-based control systems, especially if they run under general-purpose operating systems, often exhibit variance of the scan period of processing inputs and outputs. Although this fact is usually not taken into account when discrete control algorithms are used, it can cause worse performance of the control loop in comparison to the theoretical case. In this paper we describe a modified discrete LQ control algorithm that takes disturbances of the scan period into account and partially compensates their influence. We also show that such a controller can be implemented even on low-performance hardware platforms, if they are equipped with a sufficient amount of memory.

This contribution is aimed at a possible procedure approximating quasipolynomials by polynomials. Quasipolynomials appear in linear time-delay systems description as a natural consequence of the use of the Laplace transform. Due to their infinite root spectra, control system analysis and synthesis based on such quasipolynomial models are usually mathematically heavy. In the light of this fact, there is a natural research endeavor to design a sufficiently accurate yet simple engineeringly acceptable method that approximates them by polynomials preserving basic spectral information. In this paper, such a procedure is presented based on some ideas of discrete-time (digital) filters designing without excessive math. Namely, the particular quasipolynomial is subjected to iterative discretization by means of the bilinear transformation first; consequently, linear and quadratic interpolations are applied to obtain integer powers of the approximating polynomial. Since dominant roots play a decisive role in the spectrum, interpolations are made in their very neighborhood. A simulation example proofs the algorithm efficiency.

This paper describes implementation of an electronic compass and calibration method. Firstly describes used hardware and then focus on the method of sensor calibration parameters. The eCompass uses a three-axis accelerometer and three-axis magnetometer. The compass heading is a function of all three accelerometer readings and all three magnetometer readings. The accelerometer measures the components of the earth gravity and provide pitch and roll angle information which is used to correct the magnetometer data. The magnetometer measures the components of earth’s magnetic field (called geomagnetic field) to determine the heading angle to the magnetic north.

This research paper describes the method for the calibration of accelerometer and magnetometer for tilt compensated electronic compass. The electronic compass is implemented using triaxial MEMS accelerometer and triaxial MEMS magnetometer. The heading of the compass is generally influenced by scale factors, offsets and misalignment errors of these sensors. The proposed calibration method determines twelve calibration parameters in six stationary positions for accelerometer and twelve calibration parameters in 3D rotations for magnetometer.

Motivated by the special class of nonlinear systems, we introduce a scheduling technique that aims at extending the region of validity of linearization by designing an extra scheduling mechanism. Specifically, we show, how a simplification of a control problem may results in a considerably difficult scheduling procedure. In particular, the scheduling problem in the context of a nonlinear model of four tanks is addressed. The main innovation consists in the use of auxiliary scheduling variables dealing with the problem of limited number of output variables. This allows to construct a linear feedback controller at each operating point. Additionally, an integral control which ensures desired stability and performance requirements is presented. The resulting method has been integrated into the gain scheduled control design of the four tanks system and has shown a great performance through the operating range.

This paper describes the design procedure of nonlinear dynamical model of a real system—inverted pendulum—cart with pendulum. The aim of the paper is to create a mathematical model based on known constructional, mechanical and electrical characteristics of the physical system. Such a model is linearized into standard linear time-invariant state-space model where the input is motor power voltage and the outputs are cart position and pendulum angle. A linear model is used for discrete-time LQ controller design—state variables are estimated and the cart position is controlled with pendulum in upright metastable position.

Multihop wireless networks are the promising direction of communication networks. The paper presents an attempt of different authors past experience generalization of routing metrics development. These mertrics based on multihop wireless networks data transmission features. In particular, characteristics of wireless transmission that are recommended to be considered during the design of routing metrics are reviewed. The cross-layer routing metric for multihop wireless networks is proposed. In addition, discuss the advantages and disadvantages of the well-known routing metrics created for multihop wireless networks.

In this paper, a split-step theta (SST) method is introduced and analyzed for nonlinear neutral stochastic differential delay equations (NSDDEs). The asymptotic mean square stability of the split-step theta (SST) method is considered for nonlinear neutral stochastic differential equations. It is proved that, under the one-sided Lipschitz condition and the linear growth condition, for all positive stepsizes, the split-step theta method with $$ \theta \in (1/2,1] $$θ∈(1/2,1] is asymptotically mean square stable. The stability for the method with $$ \theta \in [0,1/2] $$θ∈[0,1/2] is also obtained under a stronger assumption. It further studies the mean square dissipativity of the split-step theta method with $$ \theta \in (1/2,1] $$θ∈(1/2,1] and proves that the method possesses a bounded absorbing set in mean square independent of initial data.

In this paper a promising series of modifications of predictive control has been combined in order to extend the functionality of principles of predictive control via linearization. Based on this approach a linear model predictive controller is designed at each point to achieve desired local stability and performance requirements leading to guaranteed functionality through the whole operating range of a nonlinear system. In addition, a compensating technique has been applied in order to deal with the system dynamic burdened with a delayed control input. The improved predictive controller has been implemented and applied on illustrative examples of tank system.

An economical plant-wide control has been designed and implemented for biodiesel production by reactive distillation. Two available degrees of freedom have been assigned, to control the active constraints. The main conclusions were: (1) the optimal operation with lower value of the cost function (−946.72 USD/min) was established with liquid reflux, vapor stream, and feed flow molar ratio Methanol/Triglycerides of 8.43 kmol/min, 4.52 kmol/min, and 333:25, respectively. Additionally, the Biodiesel European Quality Standards were largely satisfied (Total Glycerol 0.25 wt%), even it exists an over purification, (2) the plant-wide control designed presented an adequate performance, maintaining stable and robust to disturbances and set-point changes, as it always reaches requested reference. Finally, in this study, the Tyreus-Luyben tuning method was the best tuning method, as it takes the least of time to reach the steady state.

This paper presents a process control method called the predictive control used to control a nonlinear process about a selected operating point. The system of the two funnel liquid tanks in series is chosen as an exemplar process. The predictive control is used in its state-space modification for CARIMA mathematical model. This paper describes the linearization process of the nonlinear system at the operating point and a process of a control signal calculation. The designed controller is verified on the process without and with a time-delay.

This paper presents a novel method for solving the mapping and scheduling problems in network on chip based on quantum evolutionary cellular automata (QECA). The method applies QECA to handle the multimedia application IP placement and scheduling problem. The QECA method is based on the concept and principles of quantum computing, such as quantum bits, quantum gates and superposition of states. Thus, the mechanism of the QECA method can inherently treat the balance between exploration and exploitation where each Q-bit individual can represent and explore all possible states and drive it to exploit a single state. The use of quantum bit representation leads to better population diversity compared with the classical bit representations while the use of quantum gate drive the population towards the best solution. The achieved results are about 0.99 % of the fitness function over 110 generations.

A mathematical model for determining the power of reciprocating compressors used in the production of low pressure compressed air in industrial enterprises has been set up. Simulation experiments have confirmed the adequacy of the developed mathematical support. For the practical application of the research results in intelligent control systems of compression facilities on the basis of the proposed model a set of applications has been created, which allows to minimize the power consumption for production and distribution of compressed air.

Simulation is a powerful and flexible technique for imitation of variety of stochastic processes and it has attractive advantages in comparison to analytical routine solutions. In this paper, the Monte Carlo simulation technique is used for imitation of operational process of electronic devices which is formalized by the model of Semi Markov process. The model considers sudden, gradual, latent and fictitious failures, human factor of service staff and time parameters of preventive maintenance. Simulation approach permits to obtain necessary data for estimation of recommended value of maintenance interval according to suggested optimality criterion. Moreover, it could be easily used for investigation and analyzing of the process with different combinations of input parameters.

The Smart Grid is a new paradigm that aims at improving the efficiency, reliability and economy of the power grid by integrating ICT infrastructure into the legacy grid networks at the generation, transmission and distribution levels. Automatic Metering Infrastructure (AMI) systems comprise the entire gamut of resources from smart meters to heterogeneous communication networks that facilitate two-way dissemination of energy consumption information and commands between the utilities and consumers. AMI is integral to the implementation of smart grid distribution services such as Demand Response (DR) and Distribution Automation (DA). The reliability of these services is heavily dependent on the integrity of the AMI data. This paper investigates the modeling of AMI data using machine learning approaches with the objective of load forecasting of individual consumers. The model can also be extended for detection of anomalies in consumption patterns introduced by false data injection attacks, electrical events and unauthorized load additions or usage modes.

This paper presents hardware and software solution of the scanning system designed for ballistic analysis of cartridge cases which were deformed by firing pin after shooting for identification process of firing weapon. The system is based on resistivity measurement between the scanning tip and a sample and three axis servomotor positioning controlled by application created in MATLAB programming environment. Output of the application is matrix of coordinates for 3D visualization of deformed cartridges for firearm identification process. Measured example results are included.

With the dynamicity in the load requirements of the user, it is essential that power transmission lines should be highly resilient against any possibilities of error or outage. The existing techniques have witnessed some good solutions towards ensuring fault tolerance, but it was never analyzed from the viewpoint of smart grid system using predictive principles. Hence, this paper presents a system that performs stochastic modelling of the distributed power generation system considering dual power states i.e. available and outage. The study also implements a cost effective algorithm for random modelling the distributed generation system of power to reduce the outage probability and increase the capacity probability considering all the possible cases of susceptible errors in transmission lines with islanding mechanism. The study outcome shows superior analysis of load capacity with respect to the existing system.

The main aim of this contribution is to present a Matlab program for robust stability analysis of families of polynomials with parametric uncertainty. The created software is applicable for basic uncertainty structures such as single parameter uncertainty (including quasi-polynomials), independent (interval) uncertainty structure, affine linear, multilinear, polynomial or general uncertainty structure. Moreover, the discrete-time interval polynomials can be analyzed as well. From the viewpoint of available tools, the program incorporates the Root Locus, the Bialas Eigenvalue Criterion, the Kharitonov Theorem, the Tsypkin-Polyak Theorem, the Edge Theorem and the Value Set Concept combined with the Zero Exclusion Condition. The use of the toolbox is briefly outlined by means of the simple example.

In this paper the FPGA based self tuning Proportional Integral (PI) controller using Iterative Feedback Tuning (IFT) Technique is proposed. This is accomplished by carrying out an overview of IFT technique and simulation, using Matlab/Simulink platform. The matlab m-file for the Self Tuning PI Controller is used to develop the VHDL code that describes the Self Tuning PI Controller hardware. Fixed point number representation is used in preference to floating point numbers for good performance in respect of reduced power consumption and enhanced speed in program execution. Finite state machine with Datapath (FSMD) model is preferred to Finite state machine plus Datapath (FSM + D) model for ease of implementation. Finally, the Self Tuning PI Controller VHDL code is simulated before implementing it on Altera EP4CE6E22C8 N FPGA.

The aim of this work is to describe the developed system which provides broad integration and better protection against a sabotage than commonly used systems. The communication bus which is used for message transmission is named Controller Area Network. The security of the CAN bus communication is ensured by the implementation of 3DES encryption method with regular changing of the cipher key. One of the main parts describes a designed database, a method of key assignment, a data encryption, a method of device addressing and a collision protection. Finally, the protocol testing is depicted.

This paper presents a project for simple web-based system identification from experimental data. A user can upload input/output data from a process to be identified in three common file formats, the data can be filtered simply using two approaches and a structure of the identified model is user-controlled. The resultant discrete-time ARX model is obtained in a common form together with the possibility to assess quality of identification and to obtain also a continuous-time model. The developed application is built on the interconnection of the latest web technologies with the MATLAB computing system where the obtained results can be easily exported. The paper explains motivation for development of this site and gives also detailed description of the whole process including the Web—MATLAB interconnection. The results are presented using selected screen-shots of the application and discussed further.

This paper summarizes the fundamental construction of higher-order-neural-units (HONU) as a class of polynomial function based neural units, which are though non-linear discrete time models, are linear in their parameters. From this a relation will be developed, ultimately leading to a new definition for analysing the global stability of a HONU, not only as a model itself, but further as a means of justifying the global dynamic stability of the whole control loop under HONU feedback control. This paper is organised to develop the fundamentals behind this intrinsic relation of linear dynamic systems and HONUs accompanied by a theoretical example to illustrate the functionality and principles of the concept.

The paper presents the concept of the wireless sensor network dedicated to smart home applications. The innovative characteristic of this network is related to its use for information transfer and routing of selected sensors that simultaneously serve as Access Points and network clients. As a result, we obtain an alternative for the popular solutions based on AdHoc idea. Network traffic creates a cascading path for messages with optional selection of routes dependent on the strength of the received signal. Messages are transmitted between the AP using store and forward methods. Optionally, in order to save the consumed energy, customers transmitters can be switched solely during the transmission time. Sample implementations have been made on the basis of low-cost microprocessor controllers and communication modules commonly used in IoT. To verify correct implementation, some tests have been conducted, examining the quality and latency.

The current availability of powerful computing technologies enables using of complex computational methods. One of such complex method is also the self-organizing migrating algorithm (SOMA). This algorithm can be used for solving of various optimization problems. It may be used even for such complex task, as the non-linear process control is. In this paper, the capability of using SOMA algorithm for the model predictive control (MPC) of semi-batch chemical reactor is studied. The MPC controller including self-organizing migrating algorithm (SOMA) is used for the optimization of the control sequence. The reactor itself is used in chromium recycling process in leather industry.

Research in the audio and video surveillance is gaining more popularity due to its wide-spread applications as well as social impact. There have been considerable efforts which are focused on developing various algorithms and models for surveillance systems. Recently, the attention in audio and video surveillance has turned towards to design autonomous detection system. In this paper a surveillance system based on sound source localization by a microphone array is presented. The design of microphone array has an important issue in the accuracy of source localization. For the surveillance application, beamforming algorithms are implemented to increase the tracking and detection performance. The real-time capabilities of an automated surveillance system are analyzed, providing a performance analysis of the localization system under different acoustic conditions.

Elastic coupled multi-machine system (ECMMS) is a one of the MIMO nonlinear complicated systems in industry. In such system, mechanical vibrations are resulted due to mechanical elastic coupling through shafts of the multiple motors of the system. One solution is to apply local controller for each motor of the system. The local controllers have to be adaptive to maintain the alignment irrespective of multiple or shared load variations and other variable disturbances. So, this paper presents a method to equalize against the resulted mechanical oscillation, and to maintain the alignment among motors in the ECMMS by designing a decentralized control system associated with an adaptation method of the parameters of local controllers to be automatically adapted with variable operating conditions. An experimental set-up of ECMMS is used to apply the proposed approach practically. The simulation data are compared to the real time data provided from the experimental set-up.

In this paper, we present the results of research on the optimization modeling of ground motion attenuation of the two establish models by Youngs et al. [25] and the model of Lin and Lee [13] using the Levenberg-Marquardt method. This modeling is particularly important in the case of ground motion given that it takes a good model for predicting the strength of earthquakes in order to reduce the risk of the impact of the natural disaster. There are two main contributions of this research is the optimization of ground motion attenuation models with Levenberg-Marquardt method on two models that have been extensively used and the development of computer applications to help accelerate modeling, especially on large data with an area of extensive research. Levenberg-Marquardt method proved to give a good contribution to the modeling of ground motion attenuation that is indicated by the very small deviations between the predicted values with the actual value.

The paper describes the method of the debugging of the intellectual decision making systems. It combines the detecting of the structural errors and the testing of the knowledge base. Static analysis allows to detect so called structural errors such as incomplete knowledge, inconsistency, extra rules. Static debugging allows to build the static correct knowledge base. But even the static correct knowledge base can have errors connected with the inconsistency of the subject area which can be detected with the dynamic debugging (testing). The paper shows that the most difficult for the detection is the “forgetting about the exception” type of the errors. There is described the method of the generation of the full test set which allows to detect such types of the errors in the knowledge base. The method is based on the building of the tests for the logic schemes. The method was successfully approved for the testing of the rule-based expert systems and for the artificial network based on the 3-level perceptron.

This article considers the territory monitoring problems by air vehicles. Vehicles are considered as intelligent agents. A specific feature consists in the inherent antagonism of the motion environment, which is a common situation in practice. Three major conditions of monitoring are formulated, namely, (1) the necessity of repeated solution of the monitoring tasks with varying routes in each cycle, (2) the necessity of online communication among vehicles under their complete independence in decision-making and (3) the possibility of task failure by some vehicles due to constraints imposed by an unfriendly environment. We introduce a group control strategy for a fleet of vehicles performing monitoring. All vehicles-agents receive a given route from a leading agent or calculate and correct the route in the autonomous mode. The efficiency of the suggested approach is demonstrated by monitoring of an emergency situation, viz., a fire in a forest zone approaching a critical object (a nuclear power plant).

The blocking events, overflows and losses in telecommunications, especially in systems with very low probability, are one of the major estimation problems. Speed-up simulation is the most convenient method for estimation of rare events. The speed-up simulation in this investigation is done with one of the splitting methods—RESTART with implementation of LRE. The main purpose of the research is to determine the significant parameters for speed-up simulation of network of queues: tandem and parallel queues.

The proposal of the soft targets security contains with technical and management solutions. Management solution is based on legislative safety and security and organization management requirements. Technical solution is based on technical requirements of applied products (for example: detectors, sensors etc.) and interconnection requirements. The aim of the article is the description of the basic functional processes, which will be applied to the software architecture. The proposed solution could connect a methods, technical components and management procedures into system. The methodology exploits a lot of inputs for supporting the operating staffs in relation to smart and quickly reaction. At the end the article proposes software solution, which is realized by fuzzy logic.

One of the ways of modeling to be used is so called ‘visual modeling’. In turn, there are many visual approaches, and only one of them is to apply algorithmic networks. The paper gives a short introduction of the algorithmic network approach and the Cognitron system is based on this approach. Further, the article describes the algorithmic model “Development Evaluation of the Information Society” and the corresponding algorithmic networks, created based on the method of development evaluation of the information society in Saint-Petersburg, developed in St. Petersburg Information and Analytical Center. The program system for working with the model is described, which consists of the Cognitron-Service program and the Cognitron system.

The paper presents an architecture of the information system based on intellectual technologies aimed to serve information needs of heterogeneous users of an industrial enterprise. Technologies for automated creation of semantic model of the subject domain based on the principle “user as an expert” as well as the model of a user’s mental stereotypes are discussed. To improve effectiveness of the system in sense of information search speed the authors propose techniques for synthesis of cognitive navigation interface and for information retrieval on the base of subtractive relation. The effectiveness of proposed technologies is confirmed by experiment.

In this paper a new approach to the creation of short-term forecasting systems of river flooding is being further developed. It provides highly accurate forecasting results due to operative obtaining and integrated processing of the remote sensing and ground-based water flow data in real time. Forecasting of flood areas and depths is performed on a time interval of 12–48 h to be able to perform the necessary steps to alert and evacuate the population. Forecast results are available as web services. The proposed system extends the traditional separate methods based on satellite monitoring or modeling of a river’s physical processes, by using an interdisciplinary approach, integration of different models and technologies, and through intelligent choice of the most suitable models for a flood forecasting.

This contribution deals with the potential of the so called active knowledge database in conjunction with the agricultural resort. The authors of this contribution initially focus attention on the defining the term active databases, their possible roles and expectations associated with them. Agriculture of the Czech Republic certainly has some potential, which can initiate a qualitative change in the functioning of the entire agricultural sector. The authors also deal with the possibility of the creation of such databases and derive their principles from classical relational databases. The crucial matters of this examination will relational database technology (especially the issue of the database triggers) and the theory of measurement and evaluation of the quality of software products. Active database must be created only on the principles of relational database technology and on these principles must also work. The proposed principles of active databases are then verified through a functional prototype and then are generalized. On the basis of these conclusions are then specified the recommendations, which can significantly increase the benefits of this phenomenon.

Elements of the methodological basis of the theory of monitoring automated (computer-aided) systems structure-dynamics control are proposed in the paper. This theory can be widely used in practice. It has an interdisciplinary basis provided by the classic control theory, operations research, artificial intelligence, systems theory and systems analysis. The proposed approaches were implemented in software prototypes. The software prototypes were developed to simulate control processes for space-facilities control system (SF CS). The unified description of various control processes allows synthesizing both technical and functional structures of SF CS simultaneously. The presented multiple-model complex, as compared with known analogues, has several advantages. It simplifies decision-making in SF CS structure dynamics management, for it allows seeking for alternatives in finite dimensional spaces rather than in discrete ones. The complex permits to reduce dimensionality of SF CS structure-functional synthesis problems in a real-time operation mode.

The paper presents several event-driven models for generation of test operation telemetry data of some systems in small satellites. The models, based on the Poisson flow of events and Gaussian distribution of state duration, are showed to give the unsatisfactory simulation quality. The proposed event-driven model with nonstationary probabilities of transitions between states are more suitable for generation of telemetry data and can be used for the development of the algorithms for revealing the predictors of hardware failures.

This paper proposes a method of reordering point cloud into a bit stream which has ordered structure, and features the ability to save local space features, which allows to use the methods of run-length encoding to reduce the bit volume of the scanned 3D data. The proposed method can be implemented in software designed to work with 3D scanned data, raw 3D data transmission for further post-processing of complex spatial forms.

In this article an approach is suggested to ensuring safe functioning of air transportation systems. This approach allows calculation of the probability of complicated situations appearing out of combining of events, which would not be dangerous if taken separately. Mathematical support of an information/management system is worked out, which allows suggestion of actions at different time periods to minimize the probability of appearance of a critical combination of events in the process of functioning of an air transportation systems.

In this paper, we investigate the issues of establishing adaptive feedbacks between complex systems (CSs) scheduling and execution from the perspectives of modern control theory. In using optimum control for the scheduling stage, feedback adaptive control for the execution stage, and attainable sets for the analysis of the achievement of the planned performance in a real execution environment, we provide a mathematically unified framework for CSs scheduling and execution control. The proposed framework makes it possible to analyze the correspondence of RFID (Radio Frequency Identification) functionalities and costs to the actual needs of execution control and support problem-oriented CSs adaptation for the achievement of the desired performance. The developed framework can be applied as an analysis tool for the decision support regarding the designing and applying RFID infrastructures in supply chains.

The components of intrusion and hold-up alarm systems are not only the receiver of the electromagnetic interference that is around them but also these components are the source of the electromagnetic interference. If the components generate excessively high interference, their activity could have an adverse effect on other electronic devices in their vicinity or it can cause errors in the functional properties of the entire security alarm system. For this reason, each component must be tested for electromagnetic immunity and also their electromagnetic interference must be measured in accredited laboratories for electromagnetic compatibility.

In paper two-level genetic and ant algorithms are proposed to optimize the functioning of the automated technological machining complex. For suggested genetic and unt algorithms it is designed the object-oriented simulation model, which allows to calculate the fitness function and evaluate potential solutions. The problem-oriented crossover, mutation and reproduction operators for two-level genetic algorithm are developed. The transition and calculation of the concentration for synthetic pheromone rules are determined for suggested ant algorithms.

The paper describes the scientific and methodical foundations of study into the central issues of structural modeling of monotone and non-monotone complex objects such as determining their structural reliability and survivability. The studies are based on the original concept of the genome of the system structural construction. Particular attention is paid to the monotone and non-monotone structures of the second type using the example of systems “at least k of n” and “exactly k of n”. Features inherent in them are revealed.

The paper focuses on forecasting of the state of the regional comprehensive security by using of multi-model complexes. The informational technology for forecasting of such security based on simulation is proposed. Particular attention is paid the formal description of comprehensive security by using of the theory of matrices and graphs. Computer models designed by using of agent-based modeling and system dynamics method were developed in this study. The results of computer simulation can be considered as analytical information for decision-making in the field of comprehensive security of regional socio-economic and nature-technical systems.

In this paper, we describe the technique of dynamic cognitive geovisualization. Cognitive geovisualization can be used to support user cognitive activity in carrying out tasks of monitoring and forecasting in decision support systems for managing complex natural and technological objects. A feature of cognitive geovisualization is that the construction of geoimages taken into account the peculiarities of perception of the user. Cognitive geoimages improves the efficiency of the visual analysis of large amounts of data, speed and quality of decision-making. We describe the application of dynamic cognitive geovisualization technology in information decision support system for regional radiological monitoring, control and forecasting. To confirm the possibilities of technology we have created a prototype of web geoserver for radiological monitoring, control and forecasting. The main functions of the dynamic cognitive geovisualization technology implemented in this web geoserver as the user tools.

In this paper the concept of integrated modeling and simulation of the processes of the Complex Technical–Organizational System (CTOS) is presented. Practical directions of the remote sensing for environmental monitoring of the protected area are proposed by the authors. Methodical basis of the integrated modeling and simulation, the process of CTOS operation, and the technology of the remote sensing for environmental monitoring are considered. Results of CTOS remote sensing are shown to adapt models to a changing environment.