Feedback Subsystems Research Articles

Sustainable Process Study on Emergy and Carbon Emission Analysis of Building System Based on Neural Network Algorithm

Sustainable building systems can effectively reduce environmental pressures and mitigate the deterioration of the global climate. The sustainability of complex building systems is influenced by various factors. This article quantitatively analyzes building systems from an ecological emergy and carbon emissions perspective, and considers typical feedback structures’ impact. A neural network algorithm is employed for sustainability prediction analysis. The results demonstrate that both from an emergy and carbon emissions perspective, the operational phase of the building and the production phase of building materials are the main contributors (accounting for over 90%). Among the three types of feedback subsystems, the cross-feedback structure has a more significant impact and yields the best corrective effect. For example, the correction proportion of the building’s emergy sustainability parameter reaches 11.3%, while it is 15.8% for carbon emissions. The neural network model predicts a decreasing trend in the energy sustainability of buildings and increasing carbon emissions over time. To improve the sustainability of building systems, measures such as ecological landscape design and carbon sequestration in building materials are considered, which can enhance the sustainability of buildings to a certain extent.

МЕТОД ФОРМИРОВАНИЯ СТРУКТУР ЦИФРОВЫХ ДВОЙНИКОВ ПРЕДМЕТНО-ОРИЕНТИРОВАННЫХ ОБЪЕКТОВ В ПРОСТРАНСТВЕ ОТКРЫТЫХ ИСТОЧНИКОВ НА ОСНОВЕ ФОРМАЛИЗМОВ ТЕОРИИ МНОЖЕСТВ, ГРАФОВ, ТЕОРИИ КАТЕГОРИЙ И ТЕОРИИ ПОРОЖДАЮЩИХ ЯЗЫКОВ ХОМСКОГО

For the material of this article, open sources can be presented as information posted on the Internet for multiple and unlimited use in the form of machine-readable systematized data, in formats that allow their separate automated processing. Any of the open sources is partially structured content, cha¬racterized by the fact that it consists of fuzzy overlaps and connections formalized by a number of sustainable rules. Aim. The purpose of the study is to produce a mathematical description of the rules for the decomposition of links of virtual images of content based on statistical data of comparisons in order to formulate a digital analogue of the verbal structure. The research is accompanied by the development of a modular cross-platform predictive analytics system for distributed open sources of the social digital environment based on multi-stream data processing technologies. The system is based on the creation of a prototype of a digital twin, which allows monitoring and subsequent analysis of open sources. A cross-platform digital twin can be created for various open sources. Currently, among them, social networks are a priority for the analysis of the studied data. Materials and methods. Turning to the same type of code content, it becomes necessary to formalize the rules for categorizing the semantic meanings of the structure of connections of the object of study, which can be described in the language of graph theory, have a suitable structure in Lie matrices, obey the laws of transitivity and have properties that allow you to recreate connectivity in a quasi-projection. A method is proposed that makes it possible to produce sequential calculus that does not contradict each other according to the basic rules of axiomatics. Results. The method allows for real-time analysis of the data flow of open sources, identification of digital traces of research objects, identification of the structure of their connections. Conclusion. With the help of the proposed group of algorithmized mathematical iterations, it becomes possible to create a combination of local systems with feedback subsystems of predictive analytics of open sources of Internet resources and local systems for various purposes.

Construction of an Intelligent Analysis Model for Website Information Based on Big Data and Cloud Computing Technology

Based on big data and cloud computing technology, the development process of this system includes hardware cluster deployment of the delivery system, optimization of website delivery strategy, and development of the delivery management background system. The main functions in the following aspects are realized: first, we built the website back-end delivery subsystem and data collection and analysis subsystem to realize the control of website delivery and data collection; second, we designed and developed a process management subsystem for booking, management, and delivery of website resources and developed the contract management and order management subsystems to realize the accurate placement of user portraits on the website; then, the placement data monitoring and effect feedback subsystems, and the data inventory subsystem of the website system were designed and developed. Finally, based on the research of Android and based on the Eclipse platform, this article has completed the construction of the Android 4.0.3 version environment, successfully used the Java development language to develop a website information intelligent analysis and navigation system, and analyzed the various functional modules of the entire system. Experimental results show that the system not only realizes ordinary route and site query functions but also combines map API, integrates big data and cloud computing technology, and realizes congestion avoidance query, time optimal query, population heat map, and real-time viewing. The nearby use of this software’s personnel density distribution and other functions provides great convenience for personal travel, which can facilitate the real-time planning of travel plans, and has great practical and practical significance. Through the different levels of testing of various subsystems, the website delivery system meets the functional and nonfunctional requirements proposed by the network and on this basis realizes the use of group wisdom based on Pearson correlation coefficient, Cosine similarity, and Tanimoto coefficient for collaborative filtering website recommendation algorithm.

Systemic- Processual Shared Leadership Model with reference to Team Variables in IT Industry in India

The team characteristics under shared leadership are very important variables determining goal accomplishment by teams . There have been numerous studies on shared leadership and team characteristics . How do the team characteristics vary in content and importance and how do they impact functioning of team and are of relevance to goal achievement ? This paper is devoted to such interesting explorations like processual and systematic understanding of shared leadership in general and it’s team characteristic in particular. In this regard, attempt is made to galvanise intellectual thought towards dynamic , processual and systematic study of variables related to team like team characteristics and shared leadership. The IT teams mostly handle changing , dynamic newer projects demanding readjustment of team variables . The sample included 300 team members for collection of responses with regard to the team characteristics like multidisciplinary contribution, technical complexity , distributed actions , reciprocal dependency , value to member expertise , decision making opportunity, member feedback , consensual working , synchronised plans . Based on correlational and variance analysis , effort has been made to explore if shared leadership can be looked upon as a system model with input , throughput and output sub-systems . The findings of this research study include not only how conglomeration of the team variables into a system with the input-throughput and output subsystem may happen but also the various components comprising these subsystems . Also these components’ findings about the input, throughput , output and feedback sub-systems were verified through discussions with the experts .

Mapping typical and hypokinetic dysarthric speech production network using a connected speech paradigm in functional MRI

We developed a task paradigm whereby subjects spoke aloud while minimizing head motion during functional MRI (fMRI) in order to better understand the neural circuitry involved in motor speech disorders due to dysfunction of the central nervous system. To validate our overt continuous speech paradigm, we mapped the speech production network (SPN) in typical speakers (n = 19, 10 females) and speakers with hypokinetic dysarthria as a manifestation of Parkinson disease (HKD; n = 21, 8 females) in fMRI. We then compared it with the SPN derived during overt speech production by 15O-water PET in the same group of typical speakers and another HKD cohort (n = 10, 2 females). The fMRI overt connected speech paradigm did not result in excessive motion artifacts and successfully identified the same brain areas demonstrated in the PET studies in the two cohorts. The SPN derived in fMRI demonstrated significant spatial overlap with the corresponding PET derived maps (typical speakers: r = 0.52; speakers with HKD: r = 0.43) and identified the components of the neural circuit of speech production belonging to the feedforward and feedback subsystems. The fMRI study in speakers with HKD identified significantly decreased activity in critical feedforward (bilateral dorsal premotor and motor cortices) and feedback (auditory and somatosensory areas) subsystems replicating previous PET study findings in this cohort. These results demonstrate that the overt connected speech paradigm is feasible during fMRI and can accurately localize the neural substrates of typical and disordered speech production. Our fMRI paradigm should prove useful for study of motor speech and voice disorders, including stuttering, apraxia of speech, dysarthria, and spasmodic dysphonia.

Discussion on the Construction of Financial Risk Control System of Electric Power Research Institutes under the Background of Informational

The level of enterprise management informatization determines its ability and effect to avoid financial risks. Only by properly evaluating this degree of informational can enterprises be correctly guided to establish a scientific risk management system. This paper analyzes the current situation of the financial risk management of power companies and the specific industry characteristics of power companies, and analyzes the current situation of financial risk management of power companies, and through the questionnaires and other methods to deepen the problems and problems. The reason was analyzed. Then, according to the characteristics of the financial company’s financial risk, the financial risk control system of the power company including risk identification, risk measurement, risk control and risk feedback subsystems is constructed. Finally, based on the financial risk control system, the corresponding policies and systems are put forward to create a good environment for the operation of the financial risk control system of the power company.

Identification of Forward and Feedback Transfer Functions in Closed-Loop Systems with Feedback Delay

The subject of this paper is the identification of closed-loop continuous-time systems, with delayed feedback action, from sampled input-output measurements. In particular, a method for the identification of both forward and feedback subsystems is presented that requires only the knowledge of their orders and of the time-delay introduced in the feedback loop. The identification procedure is divided in two parts. The first step captures the behavior of the whole closed-loop system, estimating its transfer function. In the second step two different approaches are presented to separate the contributions of the forward and feedback subsystems in the loop. One of these approaches exploits a system theoretical method to compute the approximate greatest common divisor between polynomials. Numerical results validate the effectiveness of the proposed technique.

Passivity-based decentralized stabilization of multi-agent systems with uncertainty and mixed delays

In this paper, we investigate a decentralized stabilization problem of uncertain multi-agent systems with mixed delays including discrete and distributed time-varying delays based on passivity stability. We design a decentralized state-feedback stabilization scheme such that the family of closed-loop feedback subsystems enjoys the delay-dependent passivity stability for each subsystem. Then, by employing a new Lyapunov-Krasovskii function, a linear matrix inequality (LMI) approach is developed to establish the delay-dependent criteria for the passivity stability of multi-agent systems. The sufficient condition is given for checking the passivity stability. The proposed LMI result is computationally efficient. An example is given to show the effectiveness of the method.

Decentralized Stabilization of Interconnected Systems With Time-Varying Delays

This technical note establishes decentralized delay-dependent stability and stabilization methods for two classes of interconnected continuous-time systems. The two classes cover the linear case and the Lipschitz-type nonlinear case. In both cases, the subsystems are subjected to convex-bounded parametric uncertainties and time-varying delays within the local subsystems and across the interconnections. An appropriate Lyapunov functional is constructed to exhibit the delay-dependent dynamics at the subsystem level. In both cases, decentralized delay-dependent stability analysis is performed to characterize linear matrix inequalities (LMIs)-based conditions under which every local subsystem of the linear interconnected delay system is robustly asymptotically stable with an gamma -level <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> - <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">gain</i> . Then we design a decentralized state-feedback stabilization scheme such that the family of closed-loop feedback subsystems enjoys the delay-dependent asymptotic stability with a prescribed gamma-level <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> gain for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on a representative example.

Decentralized Stabilization of Interconnected Systems with Time-varying Delays

Decentralized delay-dependent stability and stabilization methods are developed for a class of linear interconnected continuous-time systems. The subsystems are time-delay plants subjected to convex-bounded parametric uncertainties and the interconnections are time-delay couplings. The delay-dependent dynamics are established at the subsystem level through the construction of appropriate Lyapunov-Krasovskii functional. We characterize decentralized linear matrix inequalities (LMIs)-based delay-dependent stability conditions such that every local subsystem of the linear interconnected delay system is robustly asymptotically stable with an γ–level L 2 –gain. A decentralized statefeedback stabilization scheme is designed such that the family of closed-loop feedback subsystems enjoys the delay-dependent asymptotic stability with a prescribed γ–level L 2 gain for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on a representative example.

Synchronisation and communication with regularly clocked optoelectronic discrete time chaos

A report is presented on the first synchronisation results with two optoelectronic nonlinear delayed feedback subsystems generating sequences of regularly clocked picosecond light pulses with chaotically distributed amplitude. Chaos encoding and decoding of pseudorandom binary information is also demonstrated. The proposed principle is a promising way for securing high-rate communications with chaos at the physical level.

Trajectory tracking of leader–follower formations characterized by constant line-of-sight angles

A group of identical unicycles is controlled by means of local feedback laws that require measurements of the unicycles relative positions and speeds. Vehicle interconnections are considered unilateral and are modeled by means of a directed acyclic graph. Although not needed for the implementation of the controllers, the desired trajectory of each vehicle is derived from the requirement that the formation must rotate with the leader while ensuring that the relative positions and line-of-sight angles between unicycles are time-invariant. Exponential convergence of the actual trajectories to a ball centered on the desired trajectories is obtained by computing the Jacobian of the nonlinear dynamics and using results from contraction theory. Instrumental to this derivation is the subsystem feedback decomposition interpretation of the plant model. In this context, convergence depends on the uniform negative definiteness and strict positive realness of the forward and feedback subsystems. Such properties are obtained provided a set of linear and bilinear matrix inequalities as well as kinematic constraints are satisfied. A numerical example illustrates the convergence property of a leader–follower formation.

Identification of complex systems with unknown feedback subsystems

A novel identification algorithm for a linear discrete-time multivariable closed-loop system is proposed based on an output over-sampling scheme. If the feedback subsystem is operating with period T. the structure and parameters of forward and feedback subsystems can be determined simultaneously by using the over-sampled output data. It can be used in closed-loop identification even though neither the knowledge of the forward and feedback subsystems nor the observation of input to the forward subsystem can be available.

Simultaneous identification of forward and feedback systems in closed-loop structure

A novel discrete-time identification algorithm is developed to simultaneously identify forward and feedback subsystems included in a closed-loop structure. It is clarified that if the feedback subsystem is operating with a period T , the parameters of the forward and feedback subsystems can be determined by using the input data to the overall closed-loop system and the over-sampled output data which has a smaller sampling interval than T .

Transient stability hierarchical control in multimachine power systems

The authors present the optimal transient stability control problem in a hierarchical structure for multimachine power systems. The two-level structure retains the local closed-loop controls, thereby easing its implementation on existing systems. The formulation accounts for nonlinearities and interconnections, and the optimization of the system transient performance is obtained with less computational effort. Since the computations are distributed among the many local feedback subsystems, the storage and solution times are considerably less than those required by a single overall centralized controller. This advantage becomes much stronger as the system size increases. For illustration purposes, this technique was applied successfully to a four-machine system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

&amp;lt;tex&amp;gt;L_2&amp;lt;/tex&amp;gt;-stability of interconnected systems using a reformulation of the passivity theorem

In this paper, we give a reformulation of the well-known passivity theorem for single-loop systems, which removes the asymmetry between the conditions on the forward and feedback subsystems. This reformulation leads to stability as well as instability criteria for interconnected systems, and these are shown to contain known results as special cases.