Complex Control Systems Research Articles

Distributed point-to-point routing method for tasks in cloud control systems

With the rapid development of cloud computing and control theory, a new paradigm of networked control systems called cloud control systems is proposed to meet the requirements of large-scale and complex applications. Currently, cloud control systems are mainly built by using a centralized architecture. The centralized system is overly dependent on the central control plane and has huge challenges in large-scale heterogeneous node systems. In this paper, we propose a decentralized approach to establish cloud control systems by proposing a distributed point-to-point task routing method. A considerable number of tasks in the system will not rely on the central plane and will be directly routed to the target devices through the point-to-point routing method, which improves the horizontal scalability of the cloud control system. The point-to-point routing method directly gives a unique address to every task, making inter-task communication more efficient in a complex heterogeneous and busy cloud control systems. Finally, we experimentally demonstrate that the distributed point-to-point task routing approach is compatible against the state-of-the-art central systems in large-scale task situations.

Robust Walking Based on MPC With Viability Guarantees

Model predictive control (MPC) has shown great success for controlling complex systems, such as legged robots. However, when closing the loop, the performance and feasibility of the finite horizon optimal control problem (OCP) solved at each control cycle are not guaranteed anymore. This is due to model discrepancies, the effect of low-level controllers, uncertainties, and sensor noise. To address these issues, we propose a modified version of a standard MPC approach used in legged locomotion with viability (weak forward invariance) guarantees. In this approach, instead of adding a (conservative) terminal constraint to the problem, we propose to use the measured state projected to the viability kernel in the OCP solved at each control cycle. Moreover, we use past experimental data to find the best cost weights, which measure a combination of performance, constraint satisfaction robustness, or stability (invariance). These interpretable costs measure the tradeoff between robustness and performance. For this purpose, we use Bayesian optimization to systematically design experiments that help efficiently collect data to learn a cost function leading to robust performance. Our simulation results with different realistic disturbances (i.e., external pushes, unmodeled actuator dynamics, and computational delay) show the effectiveness of our approach to create robust controllers for humanoid robots.

MLD–MPC for Ultra-Supercritical Circulating Fluidized Bed Boiler Unit Using Subspace Identification

Before carbon capture and storage technologies can truly be promoted and applied, and nuclear or renewable energy power generation can become predominant, it is important to further develop more efficient and ultra-low emission USC units on the basis of leveraging the strengths of CFB technology. In view of this complex system with strong nonlinearity such as the boiler-turbine unit of a thermal power unit, the establishment of a model that is suitable for control is indispensable for the operation and the economics of the process. In this study the form of the nonlinear model after linearization at the steady-state point has been fully considered and an improved subspace identification method, which is based on the steady-state point deviations data, was proposed in order to identify a piecewise affine model. In addition, the construction of the excitation signal in practical applications has been fully considered. The identification results demonstrate that this method has a better adaptability to strong nonlinear systems. The identification normalized root mean square errors of each working condition were almost all less than 10%. On this basis, a framework that is widely applicable to complex system control has been established by combining with the mixed logic dynamic (MLD) model. The canonical form realization was performed in order to transfer the local models into the same state basis. The predictive control was carried out on the boiler-turbine system of a 660-MW ultra-supercritical circulating fluidized bed unit that was based on the above framework. The results indicate that the predictive control performance is closely related to the setting value of the ramp rate and, therefore, prove the effectiveness of the framework.

Mid‐Infrared Dynamic Wavefront Transformer Based on a Two‐Degrees‐of‐Freedom Control System

AbstractVast tunable optical components are realized based on dynamic reconfigurations of the incident wavefronts, such as beam steering and tunable lens. However, the dominant paradigm of current wavefront reconfiguration technologies relies on complex control systems with degrees of freedom much larger than output wavefronts, e.g., beam steering based on spatial light modulator or phased array antennas. Here, a new paradigm for dynamic reconfiguration of arbitrary output wavefronts using control systems with the same degrees of freedom is proposed. As an example, a wavefront transformer is demonstrated using an in‐plane two‐degree‐of‐freedom (2DOF) mechanical actuation system of metasurface doublet for semi‐omnidirectional beam steering, which measures a 6‐kHz modulation speed and a 131.2° × 131.2° field of view. This paradigm can be applied to metasurface transformers for dynamic wavefront reconfiguration with any control system for vast applications, such as tunable lens, beam steering, and dynamic beam profiler, just to name a few.

KORRUPSIYA VA MANFAATLAR TO‘QNASHUVINING OLDINI OLISHDA KOMPLAENS NAZORAT TIZIMINING O‘RNI (DAVLAT VA XUSUSIY SEKTOR MISOLIDA)

This article discusses the positive achievements and mechanisms for overcoming corruption and conflicts of interest-based on the requirements for modern civil servants and provides a detailed analysis of the implementation of internal control systems. The system of complex control and its capabilities, its historical development and its role in preventing corruption and conflicts of interest are scientifically investigated. The positive experience and opportunities for the implementation of the complex control system in foreign countries, international organizations, and non-governmental organizations have been analyzed through national and foreign literature. Through the analysis of normative and legal acts of the Republic of Uzbekistan, the tasks set for the introduction of a comprehensive control system, the current situation and legal gaps are studied on the example of the public and private sectors. The external factors to be taken into account in the implementation of the complex control system, and the possible risks have been studied on the basis of scientific sources. Based on national and foreign experience, scientific proposals and conclusions of scientists, opinions, suggestions, and recommendations on the effective organization of a comprehensive control system in the prevention of corruption and conflicts of interest in the country were put forward.

ELECTROMAGNETIC COMPATIBLE CURRENT SOURCES WITH RELAY CONTROL

The development of industry leads to an increase in nonlinear loads, which are generators of higher harmonics in the network. The quality indicators of voltage and current consumed from the network are established by international standards for the quality of electricity. The simplest method of filtering harmonics is passive filters, lack of low quality harmonic compensation. The use of active filters improves the quality of the current. But active filters have a complex control system. The use of active rectifiers as part of semiconductor power supplies solves the problem of generating higher harmonics in the network and provides a power factor equal to 1.
 Six variants of three-phase and single-phase power supplies have been developed. They operate as a current source. All circuits consist of two parts: an active rectifier and a DC-DC converter. The scope of use of such sources is different: a direct current electric drive, an electric power system of wind turbines, an electric system of aircraft. The control system of the relay converters provides the formation of current and the maximum speed in the processing of disturbances. 
 Oscillograms of the current sources are obtained by digital modeling. They confirm the efficiency of the proposed sources, the electromagnetic compatibility of the power sources with the mains and the value of the power factor close to unity. Current sources are invarant to the action of disturbances: changes in load resistance, mains voltage. The study of electromagnetic processes made it possible to obtain analytical expressions for the maximum and minimum frequency of the relay mode, the capacitance of the capacitors and the operating conditions of the sources. 
 The developed program allows you to get the parameters for choosing the power elements of the circuit: inductance, capacitance, switching frequency of transistors. 
 The quality of the consumed current is analyzed by calculating the total harmonic distortion (THD). For all considered sources, the THD value is less than 5%, which meets the quality standards for the consumed current.

Impact of zoning heating and air conditioning control systems in users comfort and energy efficiency in residential buildings

Nowadays, in the residential sector, a widely used Heating, Ventilation and Air Conditioning system is the ducted direct expansion inverter system based on the on/off control of a single zone, which cannot guarantee the thermal comfort in each room of the building. As a solution, the standard EN 15,232 regulates the use of control systems including thermal zoning as a fundamental condition in the energy efficiency in buildings. The zoning system can adapt the equipment working regime to meet the thermal demand in each zone monitoring the air temperature according to users’ preferences ensuring the thermal comfort in each zone. Framed in this goal, in contrast to complex and costly control systems, this paper presents a new zoned control system based on thermostats and motorized dampers in each zone, a control board and a communication gateway which allows the communication between the unit and the control board to set operational parameters as the speed of the fan or the supply air set point temperature.The practical feasibility of this new control system is presented with a thermo-economic comparison analysis with respect the conventional in the context of the Building Research Establishment Environmental Assessment Methodology certification scheme. The model of the zoning system together with implemented control algorithms is developed in TRNSYS17 and the case of study is a residential dwelling in three different Spanish cities. The results show how the thermal zoning control contributes to adapt the thermal energy to each zone in a more efficient way. Moreover, the regulation of the motorized dampers, fan speed and set point temperature of the unit ensures the thermal comfort in all the zones of the building guaranteeing a category B according to the standard regulations. Finally, from the point of view of energy consumption, energy savings from 21 to 42% are obtained, resulting in payback periods of the installation from 3.2 to 4.3 years.

Advanced and Complex Energy Systems Monitoring and Control: A Review on Available Technologies and Their Application Criteria.

Complex energy monitoring and control systems have been widely studied as the related topics include different approaches, advanced sensors, and technologies applied to a strongly varying amount of application fields. This paper is a systematic review of what has been done regarding energy metering system issues about (i) sensors, (ii) the choice of their technology and their characterization depending on the application fields, (iii) advanced measurement approaches and methodologies, and (iv) the setup of energy Key Performance Indicators (KPIs). The paper provides models about KPI estimation, by highlighting design criteria of complex energy networks. The proposed study is carried out to give useful elements to build models and to simulate in detail energy systems for performance prediction purposes. Some examples of energy complex KPIs based on the integration of the Artificial Intelligence (AI) concept and on basic KPIs or variables are provided in order to define innovative formulation criteria depending on the application field. The proposed examples highlight how modeling a complex KPI as a function of basic variables or KPIs is possible, by means of graph models of architectures.

Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems

Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems

A Novel Broad Echo State Network for Time Series Prediction: Cascade of Mapping Nodes and Optimization of Enhancement Layer

Time series prediction is crucial for advanced control and management of complex systems, while the actual data are usually highly nonlinear and nonstationary. A novel broad echo state network is proposed herein for the prediction problem of complex time series data. Firstly, the framework of the broad echo state network with cascade of mapping nodes (CMBESN) is designed by embedding the echo state network units into the broad learning system. Secondly, the number of enhancement layer nodes of the CMBESN is determined by proposing an incremental algorithm. It can obtain the optimal network structure parameters. Meanwhile, an optimization method is proposed based on the nonstationary statistic metrics to determine the enhancement layer. Finally, experiments are conducted both on the simulated and actual datasets. The results show that the proposed CMBESN and its optimization have good prediction capability for nonstationary time series data.

Preface to the Special Issue on “Control, Optimization, and Mathematical Modeling of Complex Systems”

Complex systems have long been an integral part of modern life and can be encountered everywhere [...]

Tracking Control of a Hyperchaotic Complex System and Its Fractional-Order Generalization

Hyperchaotic complex behaviors often occur in nature. Some chaotic behaviors are harmful, while others are beneficial. As for harmful behaviors, we hope to transform them into expected behaviors. For beneficial behaviors, we want to enhance their chaotic characteristics. Aiming at the harmful hyperchaotic complex system, a tracking controller was designed to produce the hyperchaotic complex system track common expectation system. We selected sine function, constant, and complex Lorenz chaotic system as target systems and verified the effectiveness by mathematical proof and simulation experiments. Aiming at the beneficial hyperchaotic complex phenomenon, this paper extended the hyperchaotic complex system to the fractional order because the fractional order has more complex dynamic characteristics. The influences order change and parameter change on the evolution process of the system were analyzed and observed by MATLAB simulation.

Автоматизированная система управления траловым комплексом

The article is devoted to the problems of developing an automated control system for a trawl complex.The analysis of trawl systems from the point of view of the concepts of lean production and lean environmental management is presented. The main design features of the developed automated trawl complex control system are described.

Robust Strong Structural Controllability of Complex Power Systems

Ensuring the control of power systems is crucial for their safe operation. This paper analyses the robust controllability of complex power systems from the structural sighta structural point of view. Stressing the dominant role of generators in the control of power systems, we propose three kinds of controllable networks by generator nodes. Additionally, the satisfied conditions and the relevant proof of zero forcing set in the controllable networks by generator nodes and extra nodes are given. Besides, tThe satisfied conditions and the relevant proofs of the largest set of removable edges that have no -effect on the strong structural controllability in three kinds of controllable networks by generator nodes are also proposed. Finally, the robustness of strong structural controllability of IEEE 39 bus system and IEEE 14 bus system have been analyzed. The zero-forcing set and the largest set of removable edges of IEEE 39 bus system and IEEE 14 bus system are provided.

Model of the supporting leg of an anthropomorphous robot or exoskeleton with two movable links taking into account the dynamics of the electric drive. Power engineering: research, equipment, technology

Currently, the direction associated with the development of exoskeletons and anthropomorphic robots is experiencing rapid growth due to the increase in the computing power of microprocessors and the breakthrough development of the theory of control of complex systems, including electromechanical systems that simulate the biomechanics of the human musculoskeletal system. This paper presents a controlled mechatronic robotic model of the support leg of an anthropomorphic robot or exoskeleton with two moving links.GOAL. Mathematical modeling of the dynamics of the supporting leg of an exoskeleton or an anthropomorphic mechanism in the form of two moving links.METHODS. The main difference between the model presented in this study and those created earlier is the use of angles counted between links corresponding to the case of real operation of electric drives. To achieve the goal of the work, the methods of robotics, mathematical modeling, mechatronics, theoretical mechanics, the study of systems of ordinary differential equations, control theory, empirical data for the human musculoskeletal system were applied.RESULTS. For the model of the mechanism, a system of Lagrange equations of the second kind is written, direct and inverse problems of dynamics are solved for a given program control of the motion of a mechatronic robotic system. The results are presented graphically and as an animated visualization of the movement of the links. Calculations were carried out both without taking into account the dynamics of electric drives, and taking into account the rotation of the rotors of electric motors. It has been established that the influence of the dynamics of the rotor of the electric motor on the mechanism is significant.CONCLUSION. The developed methods for setting the program movement of the supporting leg of an exoskeleton or an anthropomorphic robot made it possible to solve direct and inverse problems of dynamics and establish the need to take into account the rotating rotor of an electric motor.

Back to the future: Cybernetics for safety, quality and cybersecurity

There is a lack of a holistic framework that ensures Industry 4.0 systems include Internet of Things (IoT) devices and computer systems designed to be fail-safe during cyberattacks. The silo view of treating industrial risk, Information Technology (IT) risk, and software quality as separate fields are leading to exploitable and hackable systems as documented by recent events. A stable system requires the collaboration and integration of engineering experts in quality, software design, reliability along with quality managers and auditors to focus on the intersection of technology and safety/reliability. The field of Cybernetics was originally created as an interdisciplinary field to understand and control complex systems. A multi-faceted and cross-disciplinary approach will be required to design fail-safe systems that can withstand cyberattacks in Industry 4.0. Integrating roles and responsibilities cannot succeed without a similarly aligned cross-functional approach, including a RAIC framework.

Observer‐based distributed model predictive control of complex systems with state coupling constraints

In this paper, the cooperative distributed model predictive control (DMPC) problem of a class of complex systems consisting of several subsystems is studied. The states of these subsystems are coupled with each other, and thus bring challenges for the model predictive control algorithm. Moreover, though the subsystems can communicate with each other, they only can access to the output information of their neighboring subsystems. In this case, Luenberger observers are used to estimate the unknown states and a distributed prediction strategy is established for the studied system. Then, the optimal control of the closed-loop system is realized by designing distributed model predictive controller on the basis of the estimated states. The terminal constraints are introduced in the proposed DMPC algorithm to ensure the iterative feasibility and also the stability of the closed-loop. Finally, the effectiveness of the proposed method is verified by a numerical simulation.

Uncertainty-oriented reliability and risk-based output control for complex systems with compatibility considerations

This study addresses two challenges, namely, the generally existent uncertainty that has been overlooked by many current approaches, and compatibility with multiple surrogate models in the process of output control instead of relying on one specific model. In the proposed approach, reliability and risk are used to better represent and model the generally existent uncertainty. Furthermore, the proposed approach has a higher level of compatibility, which is independent of a specific surrogate model. These two aspects are the major theoretical contributions of the proposed approach. A practical case study of reducing building tilt rate (BTR) in tunnel engineering shows that the BTR can be reduced from the original [0.8516, 2.7573] to [0.4904, 1.0664] by 41.65%-73.17% with an average reduction of 56.64%. When uncertainty was not considered, the average reduction of the BTR was 50.36%, while overestimation and underestimation were observed in most sets of data. Three surrogate models were cross-checked to validate the compatibility of the proposed approach, namely the Gaussian process regression (GPR), back-propagation neural network (BPNN), and belief rule base (BRB). The results of cross-checking show that: (1) GPR and BPNN are mutually recognizable, that is, the mutual MAPE is less than 1%, (2) GPR has recommended the most robust parameter settings, and (3) BRB has underestimated the BTRs. Owing to the ability to represent and model uncertainty and the high compatibility of the surrogate models, the proposed approach can be extended to more engineering problems in various fields.

Global Sensitivity Analysis of Economic Model Predictive Longitudinal Motion Control of a Battery Electric Vehicle

Global warming forces the automotive industry to reduce real driving emissions and thus, its CO2 footprint. Besides maximizing the individual efficiency of powertrain components, there is also energy-saving potential in the choice of driving strategy. Many research works have noted the potential of model predictive control (MPC) methods to reduce energy consumption. However, this results in a complex control system with many parameters that affect the energy efficiency. Thus, an important question remains: how do these partially uncertain (system or controller) parameters influence the energy efficiency? In this article, a global variance-based sensitivity analysis method is used to answer this question. Therefore, a detailed powertrain model controlled by a longitudinal nonlinear MPC (NMPC) is developed and parameterized. Afterwards, a qualitative Morris screening is performed on this model, in order to reduce the parameter set. Subsequently, the remaining parameters are quantified using Generalized Sobol Indices, in order to take the time dependence of physical processes into account. This analysis reveals that the variations in vehicle mass, battery temperature, rolling resistance and auxiliary consumers have the greatest influence on the energy consumption. In contrast, the parameters of the NMPC only account for a maximum of 5% of the output variance.

Hybrid power-heat microgrid solution using hydrogen as an energy vector for residential houses in Spain. A case study

In order to favor a transition to a renewable energy economy, it is necessary to study the possible permeation of renewable energy sources not only in the electric grid or industrial scale, but also in the small householding scale. One of the most interesting technologies available for this purpose is solar energy, since it is a mature technology that can be easily installed in every rooftop. Thus, a techno-economic assessment was carried out to evaluate the installation of a solar-based power-heat hybrid microgrid considering the use of hydrogen as an energy vector in a typical residential house in Spain. Lead-acid batteries plus the photovoltaic and solar thermal energy installation are complemented with a hydrogen system composed of an electrolyzer, two metal hydride bottles, and a fuel cell. A simulation tool has been generated using experimental models developed and validated with real equipment for each one of the electric microgrid component. Three operating modes were tested making use of this tool to better manage the energy consumed/produced and optimize the economic output of the facility. The results show that setting up a hydrogen-based microgrid in a residential house is unviable today, mainly due to the high cost of hydrogen generation and consumption equipment. If only solar energy is considered, the microgrid inversion (12.500 €) is recovered in ten years. On the other hand, selling the electricity output has almost no repercussions considering current electrical rates in Spain. Finally, while using an optimization algorithm to manage energy use, battery life-spam, and economic benefit slightly increase. However, this profit may not be enough to justify the use of a more complex control system. The results of this research will help users, renewable energy companies, investigators, and policymakers to better understand the different factors influencing the spread of renewable smart grids in households and propose solutions to address these.