Steady-state Time Research Articles

Multi-agent deep reinforcement learning for joint dynamic conservation voltage reduction and Q-sharing in inverter-based autonomous microgrids

Conservation voltage reduction (CVR) is implemented in power systems to mitigate power consumption in steady-state time scales. We propose dynamic-scale CVR (DCVR) as a potent solution to provide cost-effective frequency support in inverter-interfaced (micro) grids. The proposed DCVR reduces the voltage profile in dynamics and consequently power reduction helps to maintain instant production-consumption balance for dynamic frequency support. However, DCVR implementation in autonomous MGs (AMGs) faces critical control and stability problems. DCVR is implemented by controlling the voltage, which is a local variable, and makes it difficult to be realized through a decentralized structure. Besides, preserving accurate reactive power sharing (Q-sharing) through conventional droop controllers while employing the DCVR is another critical concern. In this light, this paper proposes a novel artificial intelligence (AI)-based decentralized control structure to implement the DCVR in AMGs for tackling the existing issues. The multi-agent deep reinforcement learning (DRL) model, with a deep Q-network (DQN) algorithm, is adopted to address the grid instabilities and inaccurate Q-sharing issues that arise due to incorporating the DCVR. The proposed method is able to handle the nonlinearity and complexity of the system while maintaining proper dynamic performance and AMG stability. Simulation results in MATLAB/Simulink prove the effectiveness of the proposed control method.

Sustainable power management in light electric vehicles with hybrid energy storage and machine learning control

This paper presents a cutting-edge Sustainable Power Management System for Light Electric Vehicles (LEVs) using a Hybrid Energy Storage Solution (HESS) integrated with Machine Learning (ML)-enhanced control. The system's central feature is its ability to harness renewable energy sources, such as Photovoltaic (PV) panels and supercapacitors, which overcome traditional battery-dependent constraints. The proposed control algorithm orchestrates power sharing among the battery, supercapacitor, and PV sources, optimizing the utilization of available renewable energy and ensuring stringent voltage regulation of the DC bus. Notably, the ML-based control ensures precise torque and speed regulation, resulting in significantly reduced torque ripple and transient response times. In practical terms, the system maintains the DC bus voltage within a mere 2.7% deviation from the nominal value under various operating conditions, a substantial improvement over existing systems. Furthermore, the supercapacitor excels at managing rapid variations in load power, while the battery adjusts smoothly to meet the demands. Simulation results confirm the system's robust performance. The HESS effectively maintains voltage stability, even under the most challenging conditions. Additionally, its torque response is exceptionally robust, with negligible steady-state torque ripple and fast transient response times. The system also handles speed reversal commands efficiently, a vital feature for real-world applications. By showcasing these capabilities, the paper lays the groundwork for a more sustainable and efficient future for LEVs, suggesting pathways for scalable and advanced electric mobility solutions.

Deep learning based buck-boost converter for PV modules

Over the past few years, the use of DC-DC buck-boost converters for Photovoltaic (PV) in renewable energy applications has increased for better results. One of the main issues with this type of converter is that output voltage is achieved with the undesired ripples. Many models are available in the literature to address this issue, but very limited work is available that achieves the desired goal using deep learning-based models. Whenever it comes to the PV, then it is further limited. Here, a deep learning-based model is proposed to reduce the steady-state time and achieve the desired buck- or boost mode for PV modules. The deep learning-based model is trained using data collected from the conventional PID controller. The output voltage of the experimental setup is 12V while the input voltage from the PV modules is 10V (when the sunlight decreases) to 24V (for 3.6 kVA) to 48V (for more than 5 kVA). It is among the few models using a single big battery (12V) for off-grid and on-grid for a single building. Experimental results are validated using objective measures. The proposed model outperforms the conventional PID controller-based buck-boost converters. The results clearly show improved performance in terms of steady-state and less overshoot.

All optical half subtractor based on threshold switching and beams interference mechanisms

Abstract In this paper, ultra-fast, compact and high contrast ratio all optical half subtractor based on photonic crystal designed and simulated. The proposed design will be constructed using both threshold switching and interference of beams mechanisms. The proposed structure is composed of six waveguides and a nonlinear ring resonator. The simulation results show that the contrast ratio for D and B ports were obtained about 18.80 and 15.05 dB, respectively. Also the maximum rise, fall and steady-state times and total footprint for suggested all optical half subtractor are 0.5, 0.25, 1.5 ps and 234 μm2, respectively.

Boosted Electrocatalytic Glucose Oxidation Reaction on Noble-Metal-Free MoO3-Decorated Carbon Nanotubes

Electrocatalytic glucose oxidation reaction (GOR) has attracted much attention owing to its crucial role in biofuel cell fabrication. Herein, we load MoO3 nanoparticles on carbon nanotubes (CNTs) and use a discharge process to prepare a noble-metal-free MC-60 catalyst containing MoO3, Mo2C, and a Mo2C–MoO3 interface. In the GOR, MC-60 shows activity as high as 745 µA/(mmol/L cm2), considerably higher than those of the Pt/CNT (270 µA/(mmol/L cm2)) and Au/CNT catalysts (110 µA/(mmol/L cm2)). In the GOR, the response minimum on MC-60 is as low as 8 µmol/L, with a steady-state response time of only 3 s. Moreover, MC-60 has superior stability and anti-interference ability to impurities in the GOR. The better performance of MC-60 in the GOR is attributed to the abundant Mo sites bonding to C and O atoms at the MoO3–Mo2C interface. These Mo sites create active sites for promoting glucose adsorption and oxidation, enhancing MC-60 performance in the GOR. Thus, these results help to fabricate more efficient noble-metal-free catalysts for the fabrication of glucose-based biofuel cells.Graphical abstract

Numerical study of solid-state oxygen control bypass performance and corrosion distribution in a LBE flow loop

Liquid lead–bismuth solid-state oxygen control technology is considered to be one of the effective means to inhibit corrosion of structural materials. The dissolution rate of PbO particles in the mass exchanger (MX) is a crucial factor influencing the effectiveness of solid-state oxygen control. To enhance the oxygen control efficiency of the MX, a PbO particle dissolution model based on the UPBEAT (Universal lead(Pb) bismuth(Bi) Eutectic Advanced Test loop) was established. This model aims to determine the impact of temperature, LBE flow rate, operating time, and initial oxygen concentration on the dissolution rate of PbO particles and the steady-state time in the MX. The obtained insights inform the design and operational aspects of the MX. Simultaneously, a loop corrosion precipitation model was developed to simulate loop corrosion in both oxygen-free and solid-state oxygen control states. While the corrosion precipitation distribution in the loop remains consistent between oxygen-free and oxygen-controlled states, solid-state oxygen control effectively enhances the corrosion resistance of the loop.

An individual-level probabilistic model and solution for control of infectious diseases.

We present an individual-level probabilistic model to evaluate the effectiveness of two traditional control measures for infectious diseases: the isolation of symptomatic individuals and contact tracing (plus subsequent quarantine). The model allows us to calculate the reproduction number and the generation-time distribution under the two control measures. The model is related to the work of Fraser et al. on the same topic [1], which provides a population-level model using a combination of differential equations and probabilistic arguments. We show that our individual-level model has certain advantages. In particular, we are able to provide more precise results for a disease that has two classes of infected individuals - the individuals who will remain asymptomatic throughout and the individuals who will eventually become symptomatic. Using the properties of integral operators with positive kernels, we also resolve the important theoretical issue as to why the density function of the steady-state generation time is the eigenfunction associated with the largest eigenvalue of the underlying integral operator. Moreover, the same theoretical result shows why the simple algorithm of repeated integration can find numerical solutions for virtually all initial conditions. We discuss the model's implications, especially how it enhances our understanding about the impact of asymptomatic individuals. For instance, in the special case where the infectiousness of the two classes is proportional to each other, the effects of the asymptomatic individuals can be understood by supposing that all individuals will be symptomatic but with modified infectiousness and modified efficacy of the isolation measure. The numerical results show that, out of the two measures, isolation is the more decisive one, at least for the COVID-19 parameters used in the numerical experiments.

PLC mechatronics technology in the field of intelligent control application analysis

Abstract The traditional manual operation mode has problems such as high manpower cost, low efficiency, low safety, low operating precision, etc. Achieving unmanned intelligent systems in the field of mechanical and electrical engineering has become the key to transforming and upgrading relevant enterprises and improving their overall competitiveness. In this paper, an improved fuzzy PID control system is constructed based on a PLC control system combined with a fuzzy PID intelligence algorithm. It is applied to the pumping motor, coagulation dosing system, and other specific devices for simulation experiments, compared to the conventional PID algorithm, and evaluated the control system in this paper. The fuzzy PID control algorithm of this paper reduces the steady-state adjustment time of the response curve by 30% compared to the conventional PID algorithm, and the overshooting amount is reduced by 25%. With almost no overshoot, the pumping motor that was equipped with this paper’s PID algorithm reached its stable target speed in 0.3 seconds. In addition, this study found that in the coagulation dosing system model incorporating the fuzzy PID algorithm of this paper, when the model is accurate, only 20% of the overshooting amount occurs after the system has been running for some time. The conventional PID algorithm’s 50% overshoot is significantly less than this, and the time it takes to reach a steady state is also 50 minutes earlier than the conventional PID control. When the model is imprecise, fluctuations occur in both conventional PID control and fuzzy PID control, but the amplitude of the fluctuations in fuzzy PID control is relatively small. In conclusion, this paper shows that the fuzzy PID control algorithm in this paper has higher control accuracy, response speed, and stability than the conventional PID control algorithm.

Three-dimensional reconstruction and optimization of porous fuel electrode in reversible solid oxide cells based on the Lattice Boltzmann method

A reversible solid oxide cell can work as a fuel cell (FC) or an electrolyzer cell (EC) with superior efficiency in a single device, which has the potential to become the core of energy conversion and storage. Since the redox reaction occurs at the three phase boundary in the porous electrode, the microstructure of which has a significant effect on the dynamic performance of the cell. Current research on porous electrodes mainly focuses on parametric and steady-state analysis but lacks studies on dynamic performance. In this study, we investigate the mass transfer process and dynamic performance of rSOC fuel electrodes by 3D reconstruction and artificial generation combined with a two-dimensional lattice Boltzmann method. The results show that the effective diffusion coefficients and cell performance of the XCT cross-sectional and random sphere method are much higher than those of the Gaussian filter and fiber rod structure. The change in H2 concentration is larger for switching from FC to EC compared to switching from EC to FC, but the transient steady-state difference and relaxation time of the voltage is smaller. These results can be used as a reference for the design and optimization of the porous electrodes in reversible solid oxide cells.

Experimental study on failure characteristics and rheological properties of pillar-like rock samples with different shapes

The stability of coal pillar is extremely important to the control of rock strata movement and surface subsidence. It is of great significance for mining design to analyze the stability and failure characteristics of coal and rock pillars left after mining and to study the failure characteristics and rheological properties of coal and rock with different shapes. In this paper, based on uniaxial compression and rheological tests on rock samples, the rheological properties of rock samples with different shapes were discussed by using the nonlinear theoretical mechanics and damage theory, and the rheological mechanical characteristics of coarse yellow sandstone samples under the action of different free surface areas and the same loading contact area were investigated by means of experimental research, theoretical analysis and numerical simulation. The following conclusions were drawn: the failure characteristics and dynamic change process of rock samples with different shapes under the same loading contact area are obtained by uniaxial compression test and multi-stage rheological loading. The uniaxial compressive strengths of rock samples with the same loading contact surface area and different free surface areas are inversely proportional to their free surface areas. For the round sample, the stress level in the rheological test is obviously lower than the instantaneous peak uniaxial compression strength, while for the other samples, the stress level in the rheological test is close to the instantaneous peak uniaxial compression strength. For rock all these samples, both the ratio of steady-state rheological time to final failure time and the deformation degree decrease with the increase of free surface area.

Cooperative game-oriented optimal robust control for an uncertain wheeled mobile robot with position constraints

The trajectory tracking control performance of the wheeled mobile robot (WMR) is subject to position constraints, system uncertainties, and external disturbances. This paper explores the mechanism of the position constraints (equality and inequality) and considers the system uncertainties to be time-varying but bounded with fuzzy prescribed bounds. To solve the position constraints and uncertainties problems, a cooperative game-oriented optimal robust control method is proposed to provide high-precision, fast-response performance and robustness for WMR. First, a creative diffeomorphism transformation is proposed to convert the bounded state variables (subject to inequality constraints) into unbounded state variables. Accordingly, a restructured WMR system with the new state variables is established, which is free from inequality constraints. The uncertainties’ bound is described as a fuzzy number by employing fuzzy set theory, which builds the fuzzy dynamic system of the WMR. Second, the control goal for this study is to drive the WMR to follow the position constraints despite uncertainties. An optimal robust control is developed to guarantee that the tracking errors of the WMR converge to a predefined neighborhood of origin. Using Lyapunov stability analysis, a fuzzy performance index is constructed, including steady-state performance, time performance, and control effort. The fuzzy performance index is employed as the cost function based on the cooperative game theory. The optimal control design is formulated to seek the Pareto-optimal solution of control parameters. Finally, the stability analysis and comparative experiments demonstrate that the proposed control algorithm can ensure the WMR’s superior trajectory tracking convergence performance and strong robustness against uncertainties/disturbances.

Cuckoo Coupled Improved Grey Wolf Algorithm for PID Parameter Tuning

In today’s automation control systems, the PID controller, as a core technology, is widely used to maintain the system output near the set value. However, in some complex control environments, such as the application of ball screw-driven rotating motors, traditional PID parameter adjustment methods may not meet the requirements of high precision, high performance, and fast response time of the system, making it difficult to ensure the stability and production efficiency of the mechanical system. Therefore, this paper proposes a cuckoo search optimisation coupled with an improved grey wolf optimisation (CSO_IGWO) algorithm to tune PID controller parameters, aiming at resolving the problems of the traditional grey wolf optimisation (GWO) algorithm, such as slow optimisation speed, weak exploitation ability, and ease of falling into a locally optimal solution. First, the tent chaotic mapping method is used to initialise the population instead of using random initialization to enrich the diversity of individuals in the population. Second, the value of the control parameter is adjusted by the nonlinear decline method to balance the exploration and development capacity of the population. Finally, inspired by the cuckoo search optimisation (CSO) algorithm, the Levy flight strategy is introduced to update the position equation so that grey wolf individuals are enabled to make a big jump to expand the search area and not easily fall into local optimisation. To verify the effectiveness of the algorithm, this study first verifies the superiority of the improved algorithm with eight benchmark test functions. Then, comparing this method with the other two improved grey wolf algorithms, it can be seen that this method increases the average and standard deviation by an order of magnitude and effectively improves the global optimal search ability and convergence speed. Finally, in the experimental section, three parameter tuning methods were compared from four aspects: overshoot, steady-state time, rise time, and steady-state error, using the ball screw motor as the control object. In terms of overall dynamic performance, the method proposed in this article is superior to the other three parameter tuning methods.

Cosmogenic (un-)steadiness revealed by paired-nuclide catchment-wide denudation rates in the formerly half-glaciated Vosges Mountains (NE France)

Although catchment-wide denudation rates inferred from in situ cosmogenic nuclide concentrations measured in stream sediments has represented a ground-breaking progress in geomorphology over the last three decades, most of these studies rely on 10Be concentrations only. It seems that this current and routine one-nuclide approach to infer catchment-wide denudation rates has somehow overshadowed two key assumptions that are cosmogenic steady-state and short sediment transit time at the catchment scale. Although a paired-nuclide approach allow testing these assumptions, it is rarely performed on stream sediments and this can become highly problematic in slow-eroding, formerly glaciated contexts. In this study, we thus measure both 10Be and 26Al in stream sediments pertaining to twenty-one rivers draining an entire low mountain range: the Vosges Massif (NE France). The latter exhibits a sharp gradient between its southern and northern part in terms of lithology, morphometry and climate. Moreover, if its northern part remained void of glacial cover during Quaternary cold stages, its southern part was significantly and repeatedly glaciated. We aim to assess the factors that control the denudation of the Vosges Mountains and to quantitatively explore the impact of both repeated glacial cover and storage of glacially derived sediments on 26Al/10Be ratios, hence cosmogenic (un-)steadiness in modern river samples. Our results first show that elevation, slope, channel steepness and precipitation are primarily organised along a N-S increasing trend. 10Be- and 26Al-derived catchment-wide denudation rates accordingly range from 34 ± 1 to 66 ± 2, and 41 ± 3 to 73 ± 7 mm/ka, respectively, in thirteen investigated catchments that are in cosmogenic equilibrium. Lithological contrasts may control the pattern of denudation with a higher erodibility of the sandstone-dominated catchment to the north compared to the crystalline-dominated catchments to the south.Our results also show that catchments in strong cosmogenic disequilibrium (26Al/10Be ratios from 1.4 to 5.2) spatially cluster in the SW part of the Vosges Mountains that was the most intensively glaciated during Quaternary cold stages. If this precludes any conclusion about controlling factors at the whole massif scale, this study is the first to quantify the impact of past glaciations on cosmogenic (un-)steadiness measured in stream sediments. A statistically significant relationship between the degree of depletion of the 26Al/10Be ratios and the spatial pattern of glaciation is found: the larger the former glacial cover in each catchment, the lower the 26Al/10Be ratio. Equally important is the significant correlation reported between the degree of depletion of the 26Al/10Be ratios and the proportion of glacial and fluvio-glacial deposits within each catchment. These two relationships underline the link between cosmogenic unsteadiness in the stream cosmogenic signal and long-lasting and repetitive ice shielding, and complex sediment routing systems in glacial environments, respectively. We thus argue to systematically measure 26Al in complement to 10Be and to test the steady-state assumption when it comes to infer catchment-wide denudation rates from modern stream sediments, especially in slow eroding, formerly glaciated landscapes.

Mathematical Modeling of Collisional Heat Generation and Convective Heat Transfer Problem for Single Spherical Body in Oscillating Boundaries

The application of high-energy ball milling in the field of advanced materials processing, such as mechanochemical alloying and ammonia synthesis, has been gaining increasing attention beyond its traditional use in material crushing. It is important to recognize the role of thermodynamics in high-energy processes, including heat generation from collisions, as well as ongoing investigations into grinding ball behavior. This study aims to develop a mathematical model for the numerical analysis of a spherical ball in a shaker mill, taking into account its dynamics, contact mechanics, thermodynamics, and heat transfer. The complexity of the problem for mathematical modeling is reduced by limiting the motion to one-dimensional translation and representing the vibration of the vial wall in a shaker mill as rigid boundaries that move in a linear fashion. A nonlinear viscoelastic contact model is employed to construct a heat generation model. An equation of internal energy evolution is derived that incorporates a velocity-dependent heat convection model. In coupled field modeling, equations of motion for high-energy impact phenomena are derived from energy-based Hamiltonian mechanics rather than vector-based Newtonian mechanics. The numerical integration of the governing equations is performed at the system level to analyze the general heating characteristics during collisions and the effect of various operational parameters, such as the oscillation frequency and amplitude of the vial. The results of the numerical analysis provide essential performance metrics, including steady-state temperature and time constant for the characteristics of temperature evolution for a high-energy shaker milling process with a computation accuracy of 0.1%. The novelty of this modeling study is that it is the first to obtain such a high accuracy numerical solution for the temperature evolution associated with a shaker mill process.

Direct active and reactive powers control of double-powered asynchronous generators in multi-rotor wind power systems using modified synergetic control

In the future, renewable energy sources will be of great importance in overcoming the problems of power generation using traditional sources, as their use contributes to protecting the environment from pollution and helps to raise human development. Therefore, it is necessary to search for a generation system that has high characteristics to raise the quality of energy and reduce the total cost of producing, transmitting, and consuming energy. This work proposes a new nonlinear direct reactive and active power control (DRAPC) for grid-connected double-powered asynchronous generators (DPAGs) in multi-rotor wind power (MRWP) systems. The designed DRAPC employs a modified synergetic control theory (MSCT) to regulate the DFPG-MRWP stator power. With out involving any synchronous coordinate transformations, the DRAPC-MSCT reduces the steady-state error (SSE), ripples and response time of stator powers while directly determining the required rotor control voltage. This technique fundamentally improves the transient performance compared to the DRAPC-SCT. Constant switching frequency is achieved as well by using pulse width modulation, which eases the designs of the power converters and AC harmonic filters.Through the use of three test cases (tracking test, robustness test, and variable-speed test using the Maximum Power Point Tracking), the potential of the DRAPC-MSCT to reduce system instability and uncertainty is evaluated. This comprises the ability of the controller to track DPAG powers references and improve performance during variations in system parameters and wind speed.Simulated results on a 1.5 MW grid-connected DPAG-MRWP are presented and compared with those of the DRAPC-SCT. The DRAPC-MSCT improves the reactive and active power ripples by 73.33% and 84.50%, respectively. Besides, improves the SSE of the reactive and active power by 51.61% and 69%, respectively compared to the DRAPC-SCT. The simulation results demonstrate the high performance and robustness of the DRAPC-MSCT for parametric variations of DPG-MRWP compared to the DRAPC-SCT.

Optogenetic control of YAP reveals a dynamic communication code for stem cell fate and proliferation

YAP is a transcriptional regulator that controls pluripotency, cell fate, and proliferation. How cells ensure the selective activation of YAP effector genes is unknown. This knowledge is essential to rationally control cellular decision-making. Here we leverage optogenetics, live-imaging of transcription, and cell fate analysis to understand and control gene activation and cell behavior. We reveal that cells decode the steady-state concentrations and timing of YAP activation to control proliferation, cell fate, and expression of the pluripotency regulators Oct4 and Nanog. While oscillatory YAP inputs induce Oct4 expression and proliferation optimally at frequencies that mimic native dynamics, cellular differentiation requires persistently low YAP levels. We identify the molecular logic of the Oct4 dynamic decoder, which acts through an adaptive change sensor. Our work reveals how YAP levels and dynamics enable multiplexing of information transmission for the regulation of developmental decision-making and establishes a platform for the rational control of these behaviors.

Distributed edge-based event-triggered optimal formation control for air-sea heterogeneous multiagent systems

This paper addresses the optimal formation control problem for a class of air-sea heterogeneous multiagent systems with external disturbances and model uncertainties. Multiple unmanned aerial vehicles (UAVs) and multiple unmanned surface vessels (USVs) are considered in this system. First, a distributed adaptive state compensator is designed for each agent to estimate the state information of the virtual leader. This compensator is equipped with an edge-based event-triggered scheme to reduce the amount of communication for each edge. Second, a reinforcement learning-based optimal formation controller with the appointed-time prescribed performance is designed to obtain the formation configuration for an air-sea system. This method not only optimizes the formation controller but also ensures the steady-state accuracy and stabilization time. Additionally, an event-triggered mechanism is proposed to reduce the number of optimal formation controller communications. A self-structuring actor-critic neural network and a self-structuring radial basis function neural network are also proposed to solve the Hamilton-Jacobi-Bellman (HJB) equation and approximate the uncertainty, respectively. It can constantly adjust the number of neurons, eventually obtaining an optimal number. Finally, it is proven by Lyapunov theory that all signals are semiglobally uniform and eventually bounded, and the simulation results are provided to illustrate the effectiveness of the scheme.

Study of electrochemical biosensor for determination of glucose based on Prussian blue/gold nanoparticles-chitosan nanocomposite film sensing interface

A highly electroactive bilayer composite film sensing interface of Prussian blue (PB)/gold nanoparticles-chitosan (AuNPs-CS) was modified on Au electrode through electrochemical deposition and coating method followed by integrating glucose oxidase (GOx) into the interfacial matrix to fabricate a high-performance glucose biosensor. The excellent electrocatalytic ability of the PB/AuNPs-CS composite film sensing interface for H2O2 was evaluated, which has a broad linear response of 0.01–7.95 mM, with a low detection limit (LOD) 0.269 μM and a high sensitivity of 511.82 μA·mM−1·cm−2. The enhanced electrocatalytic activity of this sensing interface for H2O2 is attributed to the protection from the network CS film to PB and the synergistic effect of PB and AuNPs. Consequently, an electrochemical biosensing interface was constructed with GOx immobilized as a model enzyme. The PB/GOx-AuNPs-CS biosensing nanocomposite film was capable of a fast steady-state response time (within 2 s) and high sensitivity to glucose with a wide linear range of: 0.025–2.00 mM (R 2 = 0.99), with a sensitivity of 40.41 μA·mM−1·cm−2 and a LOD of 1.62 μM; and 2.00–6.50 mM (R 2 = 0.98), with a sensitivity of 8.90 μA·mM−1·cm−2 and a LOD of 7.16 μM. The biosensor has good anti-interference and selectivity, which provides a promising wide linear range platform for clinical blood glucose detection in the future.

Performance enhancement of large-scale linear dynamic MIMO systems using GWO-PID controller

The multi-input multi-output (MIMO) technique is becoming grown and integrated into wireless wideband communication. MIMO techniques suffer from a large-scale linear dynamic problem, it will be easy to adjust the proportional-integral-derivative (PID) of a continuous system, unlike the nonlinear model. This work displays the tuning of the PID controller for MIMO systems utilizing a statistical grey wolf optimization (GWO) and evaluated by objective function as integral time absolute error (ITAE). The instantaneous adjusting characteristic GWO approach is the criterion that distinguishes such a combination-proposed strategy from that existing in the traditional PID approach. The GWO algorithm searching-based methodology is used to determine the adequate gain factors of the PID controller. The suggested approach guarantees stability as the initial scheme for a steady state condition. A combination of ITAE combined with the GWO reduction method is adopted to reduce the steady-state transient time responses between the higher-order initial scheme and the unit amplitude response. Simulation outcomes are illustrated using MATLAB software to show the capability of adopting the GWO scheme for PID controlling.

Reliability control of a thermoelectric cooler with changes in ambient temperature

The paper presents the development of method of thermoelectric system reliability indexes control for providing thermal modesof radio electronic equipment, based on thermoelectric coolers medium temperature variation. A mathematical model for investigating influence of the environment temperature variation on the reliability performance of a single-cascade thermoelectric cooler at a given temperature level of cooling, thermal load, geometry of thermoelement branches for different characteristiccurrent operating modes is considered. The results of calculations of the basic parameters, reliability indices, dynamic characteristicsand the analysis of dependences are given for revealing the peculiarities of control processes. It is shown that decreasing the medium temperature at a given chiller design decreases the operating current, increases the cold-productivity, and decreases the time of reaching a steady-state operating mode for various characteristic current operating modes. The time to steady-state operation decreases from the minimum failure rate to the maximum cooling capacity at a fixed medium temperature. The minimum steady-state operation time is ensured in maximum cooling capacity mode. Reduction of such significant for control indices as the amountof consumed energy for different characteristic current operation modes, required heat dissipation capacity of the radiator, time of reaching the steady-state mode is noted. Analysis of research results has shown that it is possible to control indicators of reliability of a single-stage cooler of a given design by changing the medium temperature by changing the value of operating current. A change in the medium temperature of the thermoelectric cooler due to an external supporting device makes it possible to vary the reliability indices and to find a compromise between the reliability, dynamics and cooling capacity of the thermal mode support system.