Multilevel Control Research Articles

Multi-level data-predictive control for linear multi-timescale processes with stability guarantee

Multi-timescale dynamics are common in chemical processes. These processes are often difficult to model and pose challenges in control system design. In this paper, we propose a data-based control approach for linear multi-timescale systems using a system behavioural framework. A data resampling method coupled with a novel data predictive control (DPC) design with multi-level optimisation horizons is developed to handle different timescales. To deal with the dynamics of different timescales, the optimisation horizons with small to large time intervals are used to predict and optimise control actions from near to distant future. Computational complexity wise, the multi-level structure allows horizon length to expand exponentially with optimisation steps. A trajectory-based dissipativity condition is also developed to ensure stability of the proposed DPC, while achieving disturbance rejection and tracking control. An example of controlling a multi-timescale reactive distillation column is presented to illustrate the proposed approach.

Quality assessment in a multi-level control system with discrete response functions

The article extends the authors' previous research to the case of discrete response functions. A process consisting of sequential operations is considered. For each operation, you can determine the currently available probability of its error-free (high-quality) execution. By the qualitative performance of the operation, we will understand the achievement of a given level of quality in quantitative proportion to the overall level. The purpose of the article is to build a quality management strategy in which a set of probabilities of quality levels not less than a certain threshold value is achieved, with minimal costs for carrying out appropriate measures. The corresponding optimization problem is presented and a heuristic multistep algorithm for its solution is given.

A Robust Control for Five-level Inverter Based on Integral Sliding Mode Control

The limitations of classical carrier wave-based pulse width modulation (PWM) techniques prevent themfromensuringgoodoutputqualityformulti-levelinverters.Thispaperproposesanewslidingmodecontrol(NSMC)method for controlling cascaded H-bridge multi-level inverters (CHB-MLIs) to improve the output quality of theinverter, reduce the common-mode (CM) voltage with high-order harmonics, and achieve stable and robustnesscontrolfortheCHB-MLIs.TheNSMCmethodmodulatesthePWMpulsesforthemulti-levelinverterbycomparingthecontrolsignalu(t)andthecomparatorlevelswithoutusingcarrierwavetechniques.Thisapproachfacilitatestheformation of a control signal u(t) which can be flexibly adjusted to optimize the generation of PWM pulses. Toreducethechatteringproblemaroundthesliding-modesurfaceathighfrequenciesandtoincreasespeedconvergence, the integral sliding-mode surface integrated with a continuous control law is used to design thecontroller. Additionally, a first-order low-pass filter (LPF) with a variable cut-off frequency is added to the controllawtoimprovestabilityandreduceoscillationcausedbyrapidandlargechangesintheloadcurrentamplitude.ThestabilityofthecontrolsystemisvalidatedbytheLyapunovtheory.Simulationandexperimentaltestswereperformedon the same cascaded H-bridge five-level inverter (CHB-5LI) with an R-L load. The results show that the proposedNSMC method is robust and performs better efficiently for multi-level inverter control systems. Furthermore, theoutput quality of the inverter is significantly improved compared to classical carrier wave-based PWM techniques,with a reduced CM voltage and fewer high-order harmonics, resulting in reduced losses and switching frequency. Therefore, the stability and strong robustness of the CHB-MLIs can b eachieved by the proposed NSMC method.

Active torque-based gait adjustment multi-level control strategy for lower limb patient–exoskeleton coupling system in rehabilitation training

This paper proposes an active torque-based gait adjustment multi-level control strategy for lower limb patient–exoskeleton coupling system (LLPECS) in rehabilitation training. The proposed controller has three levels of high, middle, and low sub-controllers: gait adjustment layer (high-level), interaction torque design layer (middle-level), and trajectory tracking layer (low-level). The high-level sub-controller uses an adaptive central pattern generator (ACPG) to adjust the desired gait for rehabilitation training according to the patient’s active torque. In the middle-level sub-controller, the desired interaction torque is designed with neural networks and the estimated muscle torque by utilizing nonlinear disturbance observer (NDO). In the low-level sub-controller, a time delay estimation-based prescribed performance model free control is designed for the accurate tracking performance of the exoskeleton, so as to make the actual interaction torque track the desired value. An exoskeleton virtual prototype, which is developed in SolidWorks, has been imported to MATLAB/Simulink to conduct co-simulations in the SimMechanics environment. The results of co-simulations demonstrate the effectiveness of the proposed control strategy when the patient’s muscle torque is at different recovery degrees.

Hydrogen-based microgrid: Development of medium level controls in a multilevel algorithm framework

In renewable-based microgrids, intermittency caused by some energy sources highlights the important role of energy storage systems. Nowadays, hydrogen and thermal energy storage are expected to play key roles in grid-scale applications, for facilitating effective penetration of clean energy sources. This paper, through a multilevel control framework for the energy management of a renewable and reversible solid oxide based microgrid, develops medium level controls accounting for the dynamic behaviour of storage systems. The storage systems considered are a hydrogen storage tank and a thermal energy storage based on phase change material technology. In particular, the proposed algorithm is helpful in the microgrid design phase as well as for clearly assessing high-level energy management strategies, since dynamic and transient behaviours of tanks during both charging and discharging phases are validated. In this way, top-level energy management strategies can be further refined and optimized in addition to a techno-economic design being pursued, primarily through shrinking the initial sizes of storages and thereby achieving significantly lower initial capital costs. For the analyzed microgrid, its feasibility is demonstrated by reducing by as much as 40% the size of the hydrogen tank and by up to 20% the energy capacity of the thermal storage. Finally, the proposed medium level control in a multilevel algorithm framework for a hydrogen-based microgrid is also seen to be fruitful for avoiding waste energy, which can be beneficial against the background of distributed energy systems acting in virtual power plants.

Автоматизация и цифровизация ультразвуковых технологических процессов

Having analyzed the literature sources, it is revealed that digital production includes not only full automation of production processes, but also the creation of a multi-level infrastructure for their control on the basis of information technologies. Technical solutions based on this approach will significantly intensify production processes. The possibilities of automation and digitalization of ultrasonic technological processes are viewed through the creation of a hardware and software com-plex that includes technological and measuring equipment, as well as software to select the most effective technical solu-tions. Some general principles of creating ultrasonic technologies are substantiated, their stages of development include setting the task, analysis of the processing object, selection of the processing scheme and equipment, process control and quality monitoring. Methodological approaches to the implementation of production processes with a multi-level process control infrastructure based on information technologies are proposed. Examples of developed software products are given, with the help of which search engine optimization methods are used to select equipment and rational processing modes. It shows not only the possibility of using automated technology, but also the creation of a self-learning technological system based on it. The development and creation of equipment for the implementation of the proposed technical solutions has in its basis general principles of using numerical control software. The proposed algorithm can be used for a wide range of ultra-sonic technologies: cleaning, surface plastic deformation, coating, cutting, etc. In addition, the combination of the choice of technical and information solutions makes quick switch from one type of processing to another possible. Recommendations on the implementation of the proposed technical and information solutions are given.

Adaptive Power Reserve Control for Photovoltaic Power Plants Based on Local Inertia in Low-Inertia Power Systems

Retirement of thermal power plants and growth in the capacity of power electronics based renewable energy sources reduce the inertia of power systems, making them more sensitive to frequency disturbances. The shortfall of system inertia cannot be compensated by the remaining synchronous generators and alternative solutions are required. Photovoltaic power plants (PVPPs) can provide frequency support services through the application of flexible power point tracking methods and power reserves. This paper proposes a power reserve distribution method based on local inertia across the PVPPs of a power system aimed at enhancing the system frequency response compared to fixed power reserve levels, especially in weaker and less meshed networks. A multi-level adaptive power reserve control for different system inertia levels is also proposed. The performance of the methods against different frequency events is validated through extensive real-time simulations based on benchmark network models.

Mitigation of harmonics for five level multilevel inverter with fuzzy logic controller

Introduction. The advantages of a high-power quality waveform and a high voltage capability of multilevel inverters have made them increasingly popular in recent years. These inverters reduce harmonic distortion and improve the voltage output. Realistically speaking, as the number of voltage levels increases, so does the quality of the multilevel output-voltage waveform. When it comes to industrial power converters, these inverters are by far the most critical. Novelty. Multilevel cascade inverters can be used to convert multiple direct current sources into one direct current. These inverters have been getting a lot of attention recently for high-power applications. A cascade H-bridge multilevel inverter controller is proposed in this paper. A change in the pulse width of selective pulse width modulation modulates the output of the multilevel cascade inverter. Purpose. The total harmonic distortion can be reduced by using filters on controllers like PI and fuzzy logic controllers. Methods. The proposed topology is implemented with MATLAB/Simulink, using gating pulses and pulse width modulation methodology and fuzzy logic controllers. Moreover, the proposed model also has been validated and compared to the hardware system. Results. Total harmonic distortion, number of power switches, output voltage and number of DC sources are analyzed with conventional topologies. Practical value. The proposed topology has been very supportive for implementing photovoltaic based multilevel inverter, which is connected to large demand in grid and industry.

REVIEW OF CONFIGURATIONS AND STRATEGIES OF CONTROL OF MICRONETWORKS BASED ON POWER ELECTRONICS

The growing implementation of distributed energy resources requires the development of the architecture of traditional electricity systems. With the growing deployment of distributed energy resources, especially for small combined heat and power plants and renewable energy sources based on distributed generation units, the architecture of the future power supply system must be transformed in order to carry out more complex operations. The article provides an overview of micronetwork configurations with greater flexibility and reliability, parameters, structures, and control methods for electronically connected distributed energy resource installations. Of the configurations considered, DC micronetwork and high-frequency AC micronetwork have shown better performance for some special applications, such as low-voltage and geographically small networks. The corresponding parameters in the structures of the blocks of distribution energy resources and the topology of power electronics are considered. With the increase in the nominal capacity of distribution power resource units, multilevel converters provide effective ways to reduce cost and increase efficiency. Methods of controlling electronically connected aggregates of distribution energy resources under different operating modes are described. Under the influence of load and line impedance characteristics, different strategies of load distribution among units of distribution energy resources, control of instantaneous active and reactive power are compared. A multi-level hierarchical control architecture, micronetwork power and energy management is described. A comparison of control architectures based on centralized and distributed technology indicates that the modern micronetwork must become smart and flexible with the help of telecommunication infrastructures and the next generation of information technology.

Addressing the challenges of homogeneity, quality control and waste handling in soil bio-cementation: A large-scale experiment

In an attempt to go beyond the conventional laboratory experiments widely reported in literature around the emerging technique of soil bio-cementation, this work addresses key challenges related to its large-scale application. Precisely, a state-of-the-art installation with a draining bottom boundary is introduced and a novel treatment strategy, based on ex-situ hydrolysis within a 1000 L bioreactor, is described. Hydrolyzed solutions are injected in a tank filled with 0–4 mm sand, via a system of eight injection tubes to treat a total surface of 40 m2 across a depth of 2 m. A multilevel, spatial and temporal quality control system is used to monitor the injection processes across several cycles via chemical and hydraulic means. In total, 20.8 m3 of reactant solutions are supplied to the targeted zone, equal to one pore volume and over 120 chemical analyses are carried-out. Reaction efficiencies overall exceeded 80%, while by increasing the number of treatment cycles, and thus calcification levels, a gradual increase in the recorded pressure at the injection inlet was captured, that reached up to 75 kPa. Zones where the injection pressure increased the most are found to yield better resistance in the vicinity of the corresponding injection tube. A dynamic penetrometer campaign reveals that increase in the tip resistance, is found to exceed 5 MPa and yields more homogenous response across the bottom 0.5 m of the tank, which is believed to reflect the effect of initial confinement on the deposition of calcite. For the zones with the highest cementation, correlated φ’ values yield a 5° increase, while the oedometric modulus is found to double. The results suggest that ex-situ bio-cementation, where hydrolysis occurs in bioreactors instead of inside the soil mass, is capable of yielding similar precipitation efficiencies and mechanical improvement compared to traditional bio-cementation, where bacteria are injected directly into the soil. Finally, the monitoring of MICP at the scale of typical geotechnical works is discussed along with the problematic of residual ammonium, which in this study is found to reach absorded quantities of 4 mol/L.

RESEARCH OF INFORMATION FLOWS IN THE CONTROL OF INTELLIGENT POWER SYSTEM REGIMES

The purpose of this work is to solve the problem of optimizing the management of maintenance and repair equipment at large enterprises. In a unified management system, the operational collection, consolidation and transfer of indicators about the state of all numerous power equipment allows solving and sometimes avoiding many problems. It is about reducing the time for repair work (equipment downtime), offloading personnel, optimizing logistics chains, and reducing material costs. The general problems of creating intelligent energy systems from the point of view of information and telecommunication technologies have been studied. A way to process information flows in the monitoring and management of intelligent energy systems modes is proposed, which involves combining information and mathematical technologies and the use of international data standards. The approach to the development of a new information and technological infrastructure of intelligent energy systems is considered. After conducting the analysis, the optimal system is seen as a multi-level control system for intelligent electric power systems. The technology combines intelligent tools for situation analysis and software systems for mode modeling and control. The use of IT infrastructure allows to create a single information space that includes data and knowledge, as well as a set of mathematical models and methods for solving the problems of the electric power industry in the conditions of active adaptive management. In the conclusions, a detailed classification of the types of information about mode parameters is provided and the relationship between the quality of mode information and the application of various mathematical models is determined.

Monitoring and control of water-ecological space in the Dongting Lake region

The territorial spatial planning in the new era strengthens the control of different functional spaces and emphasizes integrated and coordinated development of each functional space. Therefore, it is important to monitor the “structure-function” characteristics of water-ecological space based on the context of territorial spatial planning and develop a management and control framework. Based on land use and social statistics, and with the help of ArcGIS analysis, this paper examined the structure and function of the water-ecological space in the Dongting Lake study for 2010, 2015, and 2020, generating a control framework and proposing key initiatives. The main results are as follows: 1) The overall scale of the water ecological space in the Dongting Lake study is over 7,300 km2. Water bodies had the largest share, followed by coastal terrestrial areas, while the land-water ecotone was the smallest. There was a small decrease in the water ecological space during the study period. Yueyang had the largest overall scale of water ecological space, while Linli had the smallest. 2) The comprehensive function of water ecological space in the Dongting Lake study was about 0.4000, increasing somewhat during the study period. Among the units, the comprehensive function value was highest in Yuanjiang City, while Jincheng City had the lowest. 3) From the structural elements of water ecological space, scientific planning of functional zoning of water ecological space should be carried out and combined with the delineation of “three zones and three lines.” Key initiatives such as multi-scale and multi-level planning and control, use control and access restrictions, determination of water ecological space ownership, pollution control and accountability, and comprehensive water ecological treatment and restoration should be promoted.

Defining Unidirectional Motions and Structural Reconfiguration in a Macrocyclic Molecular Motor.

The construction of sophisticated molecular machines requires not only precise control of energy fueled motions but their integration into larger functional architectures. Macrocyclization of molecular motors is a way to harness the intrinsic directionality of their rotation and use them to actively power different processes at the nano-scale. An effective concept in this regard uses a defined fragment of the molecular motor as a revolving door within the macrocycle. In this way, motor motions can be transmitted to distant structural entities, other rotations can be actively accelerated, or mechanical molecular threading events can be realized. In this work, a dual macrocyclization approach is presented, which not only allows to supersize the revolving door element but also structurally reconfigure the macrocycle in which the revolving door rotates. Unique possibilities for a multi-level precision control over integrated directional motions are thus opened up without deteriorating the functionality of the molecular machine.

Multi-Level Synthesis Gate Voltage Active Control Technology for Optimizing IGBT Switching Characteristics

Compared with the conducting and blocking steady-state processes, the voltage and current stress of IGBT become very higher in the turning-on and turning-off transient processes, and the instantaneous power loss increases significantly. The switching transient conditions greatly affect the reliability and stability of IGBT device and power converter. During the IGBT turning on process, the reverse recovery of the symmetrical bridge arm anti paralleled diode can cause additional turn-on loss and current peak overshoot. The gate voltage active control technology can effectively suppress current spike and reduce turn-on loss in the period from the initial opening time to Miller platform. The multilevel synthesis technology can adjust the gate voltage waveform and produce depression or bulge in the normal driving voltage waveform for a certain time. In this paper, the sensitive parameters of gate voltage active control, which affect the current overshoot, and turn-on loss of IGBT are studied based on the theoretical calculation and mathematical model. A multi-level synthesis gate voltage active control technology is proposed according to the principle of gate voltage active control. The relationship among the acting voltage amplitude, execution time, current peak and switching loss is studied. Considering the actual application conditions, the optimized active control scheme of gate voltage is designed. Finally, the switching characteristics test is carried out, the results verify that the proposed control technology can effectively reduce the current overshoot and turn-on loss in comparison with the conventional schemes.

Operational control of probabilistic processes in a multi-stage specialized system

A process consisting of sequential operations is considered. For each operation, you can determine the currently available probability of its error-free (high-quality) execution. By the qualitative performance of the operation, we will understand the achievement of a given level of quality in quantitative proportion to the overall level. The purpose of the article is to build a quality management strategy in which a set of probabilities of quality levels not less than a certain threshold value is achieved, with minimal costs for carrying out appropriate measures. The article presents the decomposition of operations into activities; classification of activities into activities with conditionally linear or asymptotic response; quality assessment in a multi-level control system with response functions of various types; optimization problems and their algorithmic solutions.

DEVELOPING A MOBILE ROBOT WITH VOICE COMMANDS

The paper deals with the development of a transport robot control system with voice commands and simulation of their movement in Microsoft Robotics Developer Studio (MRDS) software product. The advantages of MRDS over other programmes are discussed. The programming language used was VPL, a visual programming environment for creating and debugging applications. It was designed multi-level control of the robot. At the top level of control, human voice commands are recognised, setting the direction of movement of the robot and its motion functions. At the lower level, the wheel speed is controlled by a microcontroller, which generates pulse width modulation output signals.

Multi-level model predictive control based multi-objective optimal energy management of integrated energy systems considering uncertainty

Integrated energy systems (IES) with renewable energy systems (RES), carbon capture systems (CCS) and energy storage systems (ESS) are considered efficient in supporting the low-carbon energy supply with both economic and environmental benefits. Effective energy management is required to ensure the economical, environmental and reliable operation of the IES. However, the optimal IES operation is considered a non-trivial task due to the renewable generation uncertainty and the optimization of multiple contradictory objectives (e.g. economic, environmental and risk costs). This paper aims to provide a multi-level optimization model for the real-time optimal IES operation consisting of RES, ESS and CCS. This work quantifies the uncertainty by the Conditional Value at Risk (CVaR) theory in the optimization model. The uncertainty is further reduced by improving the operation strategy through a model predictive control (MPC)-based method. Also, the multi-objective optimization model is adopted to minimize the economic cost, carbon dioxide emissions (CDE) and primary energy consumption (PEC) for optimal energy scheduling in the intra-day stage. Based on the result of the intra-day stage, the feedback correction model is applied to adjust the schedule to balance the difference between the forecasting and actual values. Numerical results show that the proposed solution can provide the trade-off between economical and environmental performance. Through ablation experiments, the proposed method with feedback correction can carry out demand response with lower costs, CDE and PEC. The proposed solution is further confirmed with outperformed performance compared with single-objective optimization methods and other stochastic optimization methods. In addition, a robustness analysis is conducted to quantify the benefits of RES, ESS and CCS in IES.

A new design method for the openings of shell structures under the dual control of principal stress lines and stress contours

Current design software lacks high precision and effective control in handling complex shell opening designs. This study develops a new workflow for generating shell openings based on the exceptional modeling advantages of Grasshopper, a visual programming language integrated with the Rhino software. The process contains two critical subroutines developed in Python for data processing and transformation. One is a selection tool based on the K-nearest neighbors classification algorithm for processing principal stress line data. The classification result is the guideline for shell meshing, which substantially improves the structural rationality of mesh shells generated based on dynamic equilibrium methods and particle spring systems. Another tool developed in this study based on the computer vision library OpenCV provides the functionality to read and process stress image data. In addition, this subroutine allows multi-level control of shell opening dimensions according to stress contours. In contrast with the conventional method, the new method efficiently brings shell form under the dual control of principal stress lines and stress contours for the first time. The obtained shell-opening results indicate increased freedom in layout, shape, and smoothness. The method is applied to a free-form shell, and three typical practical examples are presented to demonstrate its structural efficiency and visual effect.

HRL4EC: Hierarchical reinforcement learning for multi-mode epidemic control

Infectious diseases, such as Black Death, Spanish Flu, and COVID-19, have accompanied human history and threatened public health, resulting in enormous infections and even deaths among citizens. Because of their rapid development and huge impact, laying out interventions becomes one of the most critical paths for policymakers to respond to the epidemic. However, the existing studies mainly focus on epidemic control with a single intervention, which makes the epidemic control effectiveness severely compromised. In view of this, we propose a Hierarchical Reinforcement Learning decision framework for multi-mode Epidemic Control with multiple interventions called HRL4EC. We devise an epidemiological model, referred to as MID-SEIR, to describe multiple interventions' impact on transmission explicitly, and use it as the environment for HRL4EC. Besides, to address the complexity introduced by multiple interventions, this work transforms the multi-mode intervention decision problem into a multi-level control problem, and employs hierarchical reinforcement learning to find the optimal strategies. Finally, extensive experiments are conducted with real and simulated epidemic data to validate the effectiveness of our proposed method. We further analyze the experiment data in-depth, conclude a series of findings on epidemic intervention strategies, and make a visualization accordingly, which can provide heuristic support for policymakers' pandemic response.

Multilevel control by duality

We discuss the multilevel control problem for linear dynamical systems, consisting in designing a piece-wise constant control function taking values in a finite-dimensional set. In particular, we provide a complete characterization of multilevel controls through a duality approach, based on the minimization of a suitable cost functional. In this manner we build optimal multi-level controls and characterize the time needed for a given ensemble of levels to assure the controllability of the system. Moreover, this method leads to efficient numerical algorithms for computing multilevel controls.