Variable Load Research Articles

STATISTICAL ANALYSIS OF FRICTIONAL PROCESSESOF A SLIDING BEARING

This article addresses the issue of diagnosing friction nodes in sliding bearings, which are among the mostchallenging and complex topics in the tribological research. The article presents a methodology for diagnosingfriction nodes operating under variable loads based on the analysis of vibration acceleration signals from thebearing using statistical methods. In the study, statistical parameters were determined to assess the technicalcondition of sliding bearings operating with variable loads under dry and mixed friction conditions. Usingstatistical tools to interpret selected tribological parameters that occur in the friction process aims to ensure theproper operation of the tribological system under operating conditions. Analysis of the measurement resultspresented in the study using statistical tools will allow the development of a methodology to assess the correctoperation of sliding bearings.

Application of an Improved State Feedback Control in the Selective Catalytic Reduction Denitrification Systems of Coal Power Units Under Variable Load Conditions

Selective catalytic reduction (SCR) flue gas denitrification systems are inherently complex, typically embodying characteristics of non-linearity, significant time delays, and susceptibility to multiple disturbances. In the context of coal power units engaging in deep load cycling and rapid frequency adjustment, conventional proportional-integral-derivative (PID) control struggles to meet the demands of effective control. This study introduces a control strategy that incorporates a “state observer + Linear Quadratic Regulator (LQR) state feedback + Improved Quantum Genetic Algorithm (IQGA) optimized PID”. Initially, local linear mathematical models of an SCR denitrification system at 340 MW, 450 MW, and 540 MW loads were used to design state observer and LQR state feedback control parameters for each operational condition. At a single load point, the IQGA was employed to optimize the outer loop PID parameters, followed by simulation experiments of load increases and decreases between 340 MW and 540 MW. The results demonstrated that, compared to two other strategies, the proposed approach reduced the overshoot by a minimum of 1.5% and shortened the adjustment time by 31.7% under conditions of step disturbances and internal perturbations. Throughout variable operational conditions, the strategy consistently exhibited minimal output fluctuations, rapid adjustment capabilities, strong disturbance rejection, and robust stability. This algorithm proves to be an effective method for controlling NOx concentrations, offering insights for precise ammonia injection control in future applications.

Investigation of the effect of repeated variable loads on the life cycle of transport structures using polymer composite materials

The problem of the life cycle of transport structures using polymer composite materials (PCM) is touched upon. It is noted that in the life cycle of transport structures, at the stage of operation, the endurance of structural materials plays a key role. The results of experimental studies of PCM depending on the magnitude of the coefficients of reinforcement with fiberglass reinforcement (SPA) are presented. The influence of the degree of prestress of the SPA on the life cycle of the structural element has been established. It is emphasized that in the study of the life cycle of structures, the coefficient of asymmetry of the external load application cycle is of no small importance. As a result of the study, it was found that with an increase in the coefficient of asymmetry of the application of an external load with a simultaneous increase in the prestress in the SPA, the coefficient of endurance, and, consequently, the life cycle of the element, increases.

Validity of Laws for Predicting Lifespan of Welded Points Under Variable Loading

The article examines the validity of the laws for predicting the life of welded points under variable amplitude loading, using three steels (HE360D, XE360D and XES) supplied by ArcelorMittal to Renault for the manufacture of automobile chassis parts. The fatigue tests revealed two modes of failure: cracking of the sheets at medium stresses and shearing of the molten core at high forces. For lifespan prediction, three damage laws were studied: Miner's law, Mesmacque and Amrouche law, and a proposed model. Miner's law, despite its simplicity and wide distribution, shows notable limitations in the presence of variable loads, because it does not take into account the interactions between successive load levels. The law of Mesmacque and Amrouche uses a damage indicator linked to the FN curve of the material, allowing a cycle by cycle estimation of the residual lifespan. However, it remains non-conservative at low effort. The proposed model, based on Chaboche law, overcomes some of its theoretical drawbacks, notably the dependence on the calibration parameters of the SN curve. By fitting this curve within a specific calibration window, the model improves forecast accuracy by taking into account parameter variability. This proposed model provides more reliable lifespan predictions that better correlate with experimental results, especially for low effort levels where Miner's law fails. The validation approach is based on comparing the predictions of the damage laws with the experimental results, by evaluating the deviation from the first bisector of the graphs. The results show that Miner's law is unsuitable for effort levels, while the proposed model turns out to be the most precise and conservative. The law of Mesmacque and Amrouche falls between the two, presenting a certain justice but remaining overall non-conservative. In conclusion, the proposed model offers a better match with experimental data, making its predictions more reliable for industrial applications.

Load frequency and virtual inertia control for power system using fuzzy self-tuned PID controller with high penetration of renewable energy

AbstractReliance on renewable energy is increasing, and generating units are being added to the network. Since renewable power fluctuates greatly, the frequency deviation of the grid becomes a crucial problem with access to renewable power generation. The fluctuation of the renewable power output of the system puts forward a higher demand for load frequency control of the power grid to increase the penetration of renewable power in the system. PID controller has proven its effectiveness for the LFC due to its simple structure and clear concept. In this article, the virtual synchronous generator is introduced and a fuzzy self-tuned PID controller is proposed for inertia control. The proposed controller is implemented in light of the significant integration of renewable energy and virtual inertia. The efficacy of the suggested controller is evaluated against the traditional PID controller for the Egyptian Power System as a case study under various load disturbance scenarios. The control technique is employed for variable loads with photovoltaic and wind turbine generation systems. Three instances of load changes are studied and the controller design is performed based on grey wolf optimizer in each case. The overshot and integral time absolute error are considered as comparison measures. The new contribution is applied to the proposed controller for the grid and virtual inertia. In the case of many load variations imposed, the disturbances of residential and industrial loads varied from 0.05, 0.01, 0.15, and 0.02 pu. The maximum overshoot is 0.005 for the proposed controller and 0.0078 for the classic PID controller. The integral time absolute error is 0.06429 for the proposed controller and 0.11481 for the classic PID controller. The results demonstrate the efficacy of the proposed controller for inertia control with high penetration of renewable energy. The results show that the proposed fuzzy self-tuned PID controller has an overshot less than the classical PID controller by 25% and integral time absolute error by 45%. These results show that the use of the proposed fuzzy self-tune controller for the grid and inertia gave a better performance in terms of the overshot value and the integral time absolute error.

An Optimized Strategy for the Integration of Photovoltaic Systems and Electric Vehicles into the Real Distribution Grid

The increasing spread of photovoltaic systems for private households (PVs) and electric vehicles (EVs) in order to reduce carbon emissions significantly impacts operation conditions in existing distribution networks. Variable and unpredictable PVs can stress distribution network operation, mainly manifested in voltage violations during the day. On the other hand, variable loads such as EV chargers which have battery storage in their configuration have the ability of storying a surplus energy and, if it is necessary, support a distribution network with energy, commonly known as vehicle-to-grid concept (V2G), to help voltage stability network enhancement. This paper proposes an optimal power flow (OPF)-based model for EV charging to minimize power exchange between the superior-10 kV grid and the observed distribution feeder. The optimization procedure is realized using the co-simulation approach that connects power flow analysis software and optimization method. Three different scenarios are observed and analysed. The first scenario is referred to as a base case without optimization. The second and third scenarios include optimal EV charging and discharging patterns under different constraints. To test the optimization model, a 90-bus unbalanced distribution feeder modelled based on real-life examples is used. The obtained results suggest that this optimization model does not only significantly reduce the power exchange between an external network and the distribution feeder but also improves voltage stability and demand curve in the distribution feeder.

Design and Performance of a Planetary Gearbox with Two DOFs

The article aims to describe the design and operation of a fundamentally new self-regulating planetary transmission, which, without a control system, changes the gear ratio under the influence of a variable external load. A self-regulating transmission can be created based on a kinematic chain with two degrees of freedom, having only one input. According to the laws of mechanics, such a chain has no definability of motion, since the number of inputs must be equal to the number of degrees of freedom. The equilibrium of a two-movable chain with one input can obtained by creating an additional constraint that substitutes a reaction in the instantaneous center of the intermediate link velocities by the friction moment in the hinge of the intermediate link. The friction moment creates a force constraint, which is taken into account in the equilibrium condition. The obtained equilibrium conditions ensure the definiteness of motion and the ability of self-regulation in the form of an inversely proportional dependence of the speed of the output link on the variable external load. The described method makes it possible to create a fundamentally new class of self-regulating mechanisms in all branches of technology. The interaction of kinematic and force parameters and the construction of parameter graphs was performed using the SolidWorks 2021 program with certain additions. The experimental studies performed confirm the reliability of the theoretical developments.

Exploring the role of nanoparticle additives in reducing emissions in compression ignition engine

The paper discusses the growing environmental issues caused by vehicle emissions, leading many countries to tighten their emission standards to reduce the harmful gases released by motor vehicles. This is especially important as urbanization has increased, leading to more consumption of petroleum products. As a result, there is a growing need for cleaner, more sustainable fuel alternatives. Biodiesel has been recognized as a potential solution since it is renewable, non-toxic, and less environmentally harmful than traditional diesel. The study in question explores how adding biodiesel and nanoparticles affects diesel engine performance, particularly in terms of noise and particulate matter emissions (small particles of pollution). The research was carried out using a compression ignition engine (like those found in diesel vehicles) under constant RPM (revolutions per minute) and variable loads (changes in engine stress or power requirements). The results showed that when biodiesel was blended with nanoparticles and used as fuel, there was a noticeable reduction in noise levels, carbon dioxide (CO2), and particulate matter emissions compared to regular diesel. This suggests that biodiesel, especially when enhanced with nanoparticles, can effectively lower the harmful effects of diesel engines on the environment, offering a greener and quieter alternative.

Fuzzy Logic Controller for Power Control of an Electric Arc Furnace

Electric Arc Furnaces (EAFs) are widely used in the steel manufacturing industry to melt scrap steel by employing a large number of electric arcs. EAFs play an important role in ensuring the efficient production of steel. However, their nonlinear and variable load characteristics have a significant impact on power quality. Because the active power of an electric arc depends on its length, a system for controlling the electrode positions is necessary. This paper presents a control system based on a fuzzy logic controller for the active power control of an electric arc furnace. Individual simulation scenarios were chosen with both reference values and the process taken into consideration. The reference, constant value, step variation, and the sequence of step variation were investigated, as well as step disturbances and the sequence of step disturbances from the viewpoint of the process. Furthermore, the procedure of changing the tap on a transformer was investigated. The proposed solution minimizes the time required for charge elaboration, but the main benefit is that there are no additional costs in the implementation process because the installation remains identical, with the only changes being improvements to soft control management.

Bovine Gammaherpesvirus 6 Tropism in the Natural Host

Bovine gammaherpesvirus 6 (BoHV-6) is endemic in cattle in Europe, with a high prevalence. There is evidence that the virus is a commensal and not associated with disease processes. For other gammaherpesviruses, it is known that they have a rather specific target cell spectrum, generally including B cells and, at least in the early phase of infection, the epithelium of the respiratory tract. In a previous study we detected BoHV-6 by quantitative PCR for the gB gene sequence of BoHV-6 in lung, bronchial lymph nodes, spleen and tongue with variable loads, suggesting cells in these tissues as target cells. In the present study, formalin-fixed, paraffin embedded samples of the same tissues from 10 cattle, with high overall BoHV-6 copy numbers, were examined by RNA in situ hybridization for BoHV-6 ORF73. This revealed extremely limited viral ORF73 transcription. A signal was only detected in individual lymphocytes within lymphatic follicles in bronchial lymph nodes, and within very rare alveolar epithelial cells and interstitial cells in the lungs, without any evidence of pathological changes in the tissues. No signal was detected in the spleen or in the oral mucosa of the tongue. The results are consistent with previous findings with other gammaherpesviruses, murine herpesvirus-68, ovine herpesvirus-2 and/or Epstein–Barr virus. They provide further evidence that BoHV-6 is without any consequence to the host and can indeed represent a commensal in cattle.

A novel impact approach based on electromagnetic loading technology: A case study on CFRP/Al riveted structures

To investigate the mechanical response and damage behavior of aircraft fuselage composite structures under out-of-plane impact loads more efficiently and flexibility, this paper proposed a novel impact approach and testing platform based on inductive coils to yield electromagnetic impact force. The influence of system key parameters on the electromagnetic loading waveforms were analyzed using an electromagnetic field finite element model. Single/repeated impact tests on CFRP/aluminium alloy (Al) riveted structures were conducted at different voltages (energies) based on this approach. The results indicate that the electromagnetic impact (EMI) approach exhibits significant advantages in both variable strain rate loading and continuous impact loading scenarios. This device can efficiently achieve multi-point and multiple impact loading. The electromagnetic impact forces with various amplitudes and pulse-widths can be accurately obtained by altering voltage and capacitance values, which can demonstrate the good experimental consistency of such test approach. Besides, with this test method, the load threshold for damage formation can be clearly defined: once the impact force exceeds the damage threshold load, the delamination area of the CFRP laminates expand as the impact energy increases. Note that when the provided out-of-plane impact load is slightly higher than the damage threshold load by changing the voltage, significant delamination damage may suddenly manifest in any one impact event of the repeated impacts.

The Role of Thermal Analysis in Engine Fin Design: Insights and Perspectives

Objective: The study aims to address the significance of fins in enhancing the heat transfer rate of engine cylinders and highlight their applications and advancements in various fields. Methods: Thermal analysis of fins using ANSYS Workbench is an invaluable tool for engineers and researchers in determining and optimizing the heat transfer characteristics of finned structures. ANSYS Workbench provides a comprehensive platform for evaluating the performance of fins in various applications using simulations of computational fluid dynamics (CFD) and finite element analysis (FEA). With ANSYS Workbench, it is possible to assess the thermal behaviour of fins under a variety of conditions, such as variable boundary conditions and thermal loads. Some significant recent patents on Engine fin are also discussed in this review article. Results: Fins are designed to maximize contact with the surrounding air or coolant, thereby facilitating engine heat transfer to the surrounding environment. Engineers can enhance heat dissipation capabilities by considering parameters such as fin geometry, density, material selection, and manufacturing techniques while minimizing associated drawbacks. Conclusion: The numerous applications of fins highlighted in this review article will encourage researchers to find novel strategies to improve heat transfer by employing fins for use in a variety of sectors.

A strain-interfaced digital twin solution for corner fatigue crack growth using Bayesian inference

This paper introduces a digital twin solution for corner fatigue crack growth assessment. The digital twin comprises three core features: (1) diagnosis, (2) prognosis and (3) updating. The diagnosis arm performs remote crack size measurement via strain data collected from strategically identified locations. The prognosis component postulates the fatigue life across both linear-elastic and elasto-plastic loading regimes through a fatigue crack growth power law with the cyclic J-integral, ΔJ, as the crack driving force. Uncertainty in power law parameters, however, may result in differences between the prognosis and observed fatigue life. Hence, the digital twin completes the feedback loop via Bayesian updating of the power law parameters, thereby mirroring its physical counterpart closely. An improved estimation of the remaining useful life follows. The proposed digital twin solution validates against three specimens under constant amplitude loading and a single specimen under variable amplitude loading. The successful application of the approach marks a significant step toward operational digital twins within practical settings.

Performance Evaluation of Solar PV Integrated with Custom Power Device under Various Load Conditions

The non-linear properties and rapid switching of power electronic equipment are the primary causes of power quality issues in power systems, particularly in the power distribution systems. The widespread use of delicate equipment, which continuously pollutes the environment, is making power quality problems worse. The increasing integration of renewable energy sources into the generation mix and the decarburization of the economy have created new challenges for smart grid technology, requiring creative solutions such as energy storage systems and smart transformers. This article describes a solar photovoltaic integrated unified power quality conditioner (UPQC) that uses a deep learning method based on neural networks and a novel compensating technique. Here, two Deep Neural Network algorithms are used, one in the solar PV system to obtain the maximum power under various irradiance situations, and the other to manage the UPQC under various load conditions. When compared to the conventional UPQC based on PQ Theory, DNN-UPQC produces superior results in terms of reducing total harmonic distortion. This iterative strategy, which is focused on soft computing, provides faster convergence to the target condition while maintaining the updating weight within a predetermined limit. PV-based UPQC has been connected individually to reduce voltage sag, swell, and unbalance in variable load conditions. The system's dynamic and steady state performance are assessed by modelling it with a MATLAB-Simulink in different load condition.

DETERMINATION OF OPTIMAL CONDITIONS FOR HERMETIC WELDING OF THIN FOILS WHEN USED IN MEMBRANE-TYPE STRUCTURES

Purpose. Development of optimal technology for welding thin-walled shells mode of 12Х18Н10Т steel (δ=0.15 mm), working at alternating loads. Research methods. Research methods. For welding automatic argon-arc welding (AAAW) equipment was used for of orbital welding, which includes a MW 2600 current source (FRONIUS) with software control unit and welding head of closed type MW40. Research warks showed that this type of welding is not enough for such small thicknesses concentration of the welding arc, which does not allow stable forming of the bath and obtaining solid uniform seam. A special robotic complex was used for microplasma welding STARWELD 190H, which includes: a power source for the regular arc INV 50; source main arc power supply INV 190; SIEMENS Simatic S 7-300 control unit; robot CR3-535M (MITSUBISHI); manipulator and HPH 80 plasmatron. Welding quality control was carried out by visual inspection and metallographic examination. Taking into account the conditions of operation of the parts, according to the technical conditions of the drawing, it was also provided pneumohydraulic control method. Obtained results. Visual inspection the outer surface of the welds showed the absence of defects in the form of pores, cracks, shells, no fusions, undercuts, etc. The geometric dimensions of the weld met the requirements of the standard documentation valid at the enterprise. Metallographic studies of the boxes membranes, welded by microplasma welding, gave a positive result. Defects of metallurgical character were not found in the welds. Practical value. The optimal method of welding that can be applied is determined for the manufacture of thin-walled membrane structures, from the point of view of manufacturability and economy expediency It has been established that microplasma welding allows obtaining a hermetically tight seam, when the thickness of parts to be welded is about 0.15 mm. The performance of welded membrane boxes is confirmed in the barostatic valve of an aircraft engine. It is established that micro plasma welding can be used in the manufacture of thin-walled shells made of 12X18H10T steel (δ=0.15 mm), which work at variable loads. The technological process of welding is introduced into the series production.

Automatic control system for the electric drive of an overhead crane considering elastic connections

Purpose. Investigation of the peculiarities of the automatic control system of an overhead crane electric drive with regard to elastic connections.. Research methods. To achieve this goal, we used the methods of system analysis and modeling with the help of software tools. This made it possible to reflect accurately the processes occurring in the system, as well as to test various operating scenarios and their impact on the overall system efficiency. Results. The study considered the automatic control system of the electric drive and the importance of taking into account elastic connections. The proposed adaptive system uses the RBF neural network. The use of the proposed controller ensures resistance to disturbing influences and allows to level the load oscillations. The adaptability of the system is ensured by changing the parameters (load, speed of movement of mechanisms, stiffness, positioning accuracy, etc.) to meet the operating conditions of the overhead crane. Thanks to this, the system is able to operate efficiently even under variable loads and external influences. Computer modeling of the proposed control system was carried out, which confirmed its effectiveness under various operating conditions. Scientific novelty.This system provides damping of load oscillations and increases the crane positioning accuracy. This is achieved by comparing it with existing control methods according to various criteria. It is proposed to use an algorithm for adapting the parameters of the control system in real time (load, trolley speed, cable length, mechanism stiffness, etc.), which significantly improves (by 5-7% positioning accuracy, by 8-10% stability) the performance of the system. In addition, the study confirmed the ability of the system to adapt to different operating conditions (changed load, variations in travel speed, uneven external disturbances), ensuring the stability and reliability of its operation, which is especially important for ensuring continuous operation of the crane in industrial environments. Practical value. The use of this system can increase the overhead crane productivity by 5-10% compared to traditional control systems. Implementing the system in an industrial environment will significantly improve the efficiency and safety of the crane, as well as reduce maintenance and repair costs. In addition, this system can be used to modernize existing cranes, which will extend their service life and improve their reliability. This opens up new opportunities to improve the efficiency of industrial processes associated with the use of overhead cranes and provides better working conditions for operators.

Crack Propagation Tests for Load Sequences Developed Using Different Flight Parameters of a Trainer Aircraft

Abstract Military aircraft are subjected to highly variable and unpredictable loads due to diverse mission profiles, armament configurations, and individual piloting styles. This variability complicates the definition of precise load spectra, particularly in cases where data loss occurs due to Flight Data Recorder (FDR) malfunctions or data mishandling. This paper investigates the use of different flight parameters, such as load factor (nz ), barometric height (Hb ), and horizontal velocity (Vp ), to define load sequences for the PZL-130 “Orlik” TC-II military trainer aircraft. These sequences were then used to evaluate crack propagation using Compact Tension (CT) specimens. The results show that the incorporation of additional flight parameters improves the accuracy of crack propagation predictions when compared to direct strain measurements. This study highlights the potential of using available flight data to develop reliable load spectra for fatigue life estimation in military aircraft, even when direct load measurements are not financially feasible.

Design and performance evaluation of a multi-load and multi-source DC-DC converter for efficient electric vehicle power systems

This paper introduces the design and comprehensive performance evaluation of a novel Multi-Load and Multi-Source DC-DC converter tailored for electric vehicle (EV) power systems. The proposed converter integrates a primary battery power source with a secondary renewable energy source—specifically, solar energy—to enhance overall energy efficiency and reliability in EV applications. Unlike conventional multi-port converters that often suffer from cross-regulation issues and limited scalability, this converter ensures stable power distribution to various EV subsystems, including the motor, air conditioning unit, audio systems, and lighting. A key feature of the design is its ability to independently manage multiple power loads while maintaining isolated outputs, thus eliminating the inductor current imbalance that is common in traditional systems. Experimental validation using a 100 W prototype demonstrated the converter’s ability to deliver stable 24 V and 48 V outputs from a 12 V input, with output voltage deviations kept within ± 1%, significantly improving upon the ± 5% deviations typically seen in existing converters. Furthermore, the system achieved an impressive 93% efficiency under variable load conditions. The modular nature of the converter makes it not only suitable for EV applications but also for a broader range of industries, including renewable energy systems and industrial power supplies. This paper concludes by discussing optimization strategies for future improvements and potential scaling of the technology for commercial use in sustainable energy applications.

A new integrated modelling and control of ternary pumped storage hydro power generation for small signal stability studies

Pumped storage hydro power generation (PSHPG), a reliable renewable energy source with an energy storage feature, can impart efficient damping torque to power system oscillations to improve small signal stability with appropriate modelling and additional compensation through the governor. But ternary PSHPG (T-PSHPG) has the unique feature of hydraulic short circuit (HSC) mode, where both pumping and generating modes operate simultaneously. This study presents a novel fourth-order modified Heffron Phillips (MHP) model of T-PSHPG in coordination with a multi-band Power system stabilizer (MB-PSS) employing 2-way penstock, where primary penstock circulates water from the upper reservoir to the lower reservoir through the turbine and secondary penstock divides primary penstock, thereby creating short-circuit path through the pump. Also, this model includes additional reactive power droop control to maintain the voltage profile. A new state space matrix has been developed for coordinating T-PSHPG in HSC mode with MB-PSS. The control parameters of the proposed coordinated model are set by a new multi-objective differential evolution-improved particle swam optimization (DE-IPSO) algorithm. With variable load, random solar and wind source penetrations, it has been found that the proposed model can provide adequate damping actions. The sensitivity of the proposed model has been observed by varying critical model parameters by ±50 %. For all conditions, the settling time of speed variation is within 2.672 s to 5.951 s and the minimum damping ratio lies within 0.105 to 0.455. The minimum damping ratio is 0.32 and the settling time is found to be 3.1 s for system response subject to sudden solar power variation, which has been observed by shifting system eigenvalues toward the left half of the complex plane. Time and frequency domain parameters with sensitivity analysis predict system oscillations being damped effectively with consistency for the proposed modelling and control strategy. The results are verified in real-time with OPAL-RT real-time digital simulator. It has been justified by the present study that appropriate modelling of T-PSHPG along with coordinated control action provided by MB-PSS can handle critical power system oscillations efficiently and effective damping torque can be imparted in HSC mode.

Intelligent robust controllers for tribotronic conical fluid film bearings

The article presents the results of the development of means for intelligent robust control of the parameters of a tribotronic rotor-support system with a tapered bearing with a removable bush. The proposed controller is implemented on the basis of deep Q-network reinforcement learning (DQN) synthesized on the basis of a numerical model of a rotor support system. The control strategy involved simultaneous control of the shaft position and friction in the lubrication layer. Methods for control synthesis are presented for both a deterministic system and a system with stochastic parameters. In the latter case, a controller synthesis technique is proposed that takes into account uncertainties in the system at the training stage. Testing of the resulting controllers shows the better ability of a controller trained to take into account uncertainties to cope with variable loads, as well as predict possible changes in the system and proactively transfer the system to more advantageous states.