Closed-loop Model Research Articles

The role of mechano-electric feedbacks and hemodynamic coupling in scar-related ventricular tachycardia

Mechano-electric feedbacks (MEFs), which model how mechanical stimuli are transduced into electrical signals, have received sparse investigation by considering electromechanical simulations in simplified scenarios. In this paper, we study the effects of different MEFs modeling choices for myocardial deformation and nonselective stretch-activated channels (SACs) in the monodomain equation. We perform numerical simulations during ventricular tachycardia (VT) by employing a biophysically detailed and anatomically accurate 3D electromechanical model for the left ventricle (LV) coupled with a 0D closed-loop model of the cardiocirculatory system. We model the electromechanical substrate responsible for scar-related VT with a distribution of infarct and peri-infarct zones. Our mathematical framework takes into account the hemodynamic effects of VT due to myocardial impairment and allows for the classification of their hemodynamic nature, which can be either stable or unstable. By combining electrophysiological, mechanical and hemodynamic models, we observe that all MEFs may alter the propagation of the transmembrane potential. In particular, we notice that the presence of myocardial deformation in the monodomain equation may change the VT basis cycle length and the conduction velocity but do not affect the hemodynamic nature of the VT. Finally, nonselective SACs may affect VT stability, by possibly turning a hemodynamically stable VT into a hemodynamically unstable one.

CONTROL-CORE: A Framework for Simulation and Design of Closed-Loop Peripheral Neuromodulation Control Systems.

Closed-loop Vagus Nerve Stimulation (VNS) based on physiological feedback signals is a promising approach to regulate organ functions and develop therapeutic devices. Designing closed-loop neurostimulation systems requires simulation environments and computing infrastructures that support i) modeling the physiological responses of organs under neuromodulation, also known as physiological models, and ii) the interaction between the physiological models and the neuromodulation control algorithms. However, existing simulation platforms do not support closed-loop VNS control systems modeling without extensive rewriting of computer code and manual deployment and configuration of programs. The CONTROL-CORE project aims to develop a flexible software platform for designing and implementing closed-loop VNS systems. This paper proposes the software architecture and the elements of the CONTROL-CORE platform that allow the interaction between a controller and a physiological model in feedback. CONTROL-CORE facilitates modular simulation and deployment of closed-loop peripheral neuromodulation control systems, spanning multiple organizations securely and concurrently. CONTROL-CORE allows simulations to run on different operating systems, be developed in various programming languages (such as Matlab, Python, C++, and Verilog), and be run locally, in containers, and in a distributed fashion. The CONTROL-CORE platform allows users to create tools and testbenches to facilitate sophisticated simulation experiments. We tested the CONTROL-CORE platform in the context of closed-loop control of cardiac physiological models, including pulsatile and nonpulsatile rat models. These were tested using various controllers such as Model Predictive Control and Long-Short-Term Memory based controllers. Our wide range of use cases and evaluations show the performance, flexibility, and usability of the CONTROL-CORE platform.

Particle-Swarm-Optimization-Based 2D Output Feedback Robust Constraint Model Predictive Control for Batch Processes

For the input and output constraints and uncertainties in batch processes, a 2D output feedback robust constrained model predictive control (MPC) method is designed by combining iterative learning control (ILC), MPC and output feedback. Firstly, an equivalent 2D-FM closed-loop prediction model is established by combining with the proposed output feedback controller. Then an optimization performance index function with terminal constraint is constructed to study its control optimization. According to the designed optimization performance index and Lyapunov stability theory, the feasible MPC problem is obtained by solving the linear matrix inequalities (LMIs). At the same time, the gain of the new output feedback control law is given to ensure that the performance index reaches the minimum upper bound under the constraints of input and output. In order to solve the manual adjustment problem of some parameters in the performance index function, the particle swarm optimization (PSO) algorithm is introduced, and a better solution is found near the controller by using the search optimization method. Finally, taking the injection molding process as an example and comparing with the existing method without using PSO algorithms, it is proved that the above method is more feasible.

The impact of petrochemical industry economic activities on environmental factors using a fuzzy mathematical programming model

Due to the nature of activities and processes, the petrochemical industry causes the production of industrial effluents, emissions and wastes that have adverse effects on the environment. The purpose of this study is to investigate the effect of petrochemical economic activities on environmental factors. In this paper, in order to minimize the costs and the amount of pollution caused by the emission of harmful gases, the closed-loop green supply chain model has been used, in which direct and reverse logistics networks have been considered. As a result, a fuzzy mathematical programming model has been developed for when the data are not definitively known. After the demand parameters and the amount of pollution are considered fuzzy, the maximum and bisector mean methods of the area are considered as methods (diffusion) of comparison and ranking of fuzzy definite numbers, and by adding Limitations of these two methods, the model was developed. To solve the model with real data, a plant from the petrochemical industry was selected and the data were prepared for a solution with very good estimates. Finally, the colonial competition algorithm was used to solve it. According to the model, its applicability was shown to reduce the number of environmental pollutants along with the reduction of transportation and waste, and the model for the closed-loop supply chain, which simultaneously considers two direct and inverse logistics networks. It is appropriate.

ЗАСТОСУВАННЯ БІЗНЕС МОДЕЛЕЙ ЕКОНОМІКИ ЗАМКНУТОГО ЦИКЛУ В УКРАЇНСЬКИХ РЕАЛІЯХ

The article defines that one of the alternatives to the linear model of production and consumption, the existence of which provoked the global problems of today, is the concept of the economy of closed cycles or the circular economy, which provides for resource-efficient production and consumption, the preservation of products and their parts in closed production and sales cycles and reduction of the negative consequences of human activity for the environment, which determined the relevance of the article. The essence and main purpose of using closed-loop business models is considered. On the basis of a critical analysis of research on this issue, the signs of such business models are highlighted. The prerequisites for the transition to the economy of closed cycles, as one of the most important mechanisms for overcoming the global problems of humanity, are analyzed. The main areas of the emergence of circular business models are characterized, the development of which will improve the forecast of global economic development (due to the reduction of resource limitations to growth and the creation of additional value in various sectors). The possibilities of using circular business models in modern conditions by Ukrainian companies, depending on the sphere of their activity, are revealed. The existing classifications of circular economy business models are considered.The classification developed by Accenture specialists, under the auspices of the Ellen MacArthur Foundation, focused on the implementation of technologies that contribute to the use of fewer resources for the production of products and / or services, was examined and analyzed in detail; extending the service life of existing products and/or services through repair and restoration; completing the life cycle of products by recycling them. This was achieved using general scientific methods (system analysis, formalization) and methods of economic and statistical analysis (graphical, grouping, classification); A conclusion was made about the need to apply the analyzed techniques to Ukrainian realities. The main elements of the circular production process were systematized. The practical value of the conducted research lies in the possibility of developing a "roadmap" for the transition to a circular economy at different levels of public administration, as well as the strategy of long-term and sustainable development of individual companies.

Closed-loop supply chain models of lithium-ion battery considering corporate social responsibility

How to achieve harmonious development of economy, society, and environment, and scholars focus on closed-loop supply chain (CLSC) under corporate social responsibility (CSR). This paper focuses on the CLSC of lithium-ion battery (LIB) and explores the impact of CSR on the total profit of the CLSC. We propose a CLSC of LIB consisting of a manufacturer, a retailer, and a third-party recycler and develop a centralized decision-making model and two decentralized decision-making models for this problem. The results show that (1) total profit of the CLSC will be increased under CSR. (2) Consumers will pay attention to members that undertake CSR and thus influence the CLSC. (3) Profit sharing contracts increase the total profit of the CLSC in coordination. Verify the correctness of the model and the effectiveness of the coordination mechanism by numerical analysis.

Transfer Mechanism Analysis of Injected Voltage Harmonic and its Effect on Current Harmonic Regulation in FOC PMSM

Harmonic injection method is widely used in the suppression of current harmonic and torque ripple in field-oriented control (FOC) permanent magnet synchronous motor (PMSM) servo system. However, under some working conditions of FOC PMSM, the harmonic injection method fails to suppress the current harmonics and causes oscillation. To analyze the cause of oscillation, the transfer mechanism of injected voltage harmonic is analyzed in this article, and the relation between injected voltage harmonic and current harmonic is derived. The theoretical analysis results show that the relation between harmonics will change with motor speed and parameters of FOC PMSM. When the relation between harmonics is reversed, the existing harmonic injection method will fail and cause harmonic oscillation. To solve this problem, a simple improvement of the harmonic injection method is proposed in this article based on the proposed close-loop model. The correctness of the mathematical derivation and the effectiveness of the proposed method is evaluated by experiment and simulation.

Networked scheduling for decentralized load frequency control

This paper investigates the scheduling process for multi-area interconnected power systems under shared but band-limited networks and decentralized load frequency controllers. To cope with sub-area information and avoid node collision of large-scale power systems, round-robin and try-once-discard scheduling are used to schedule sampling data among different sub-grids. Different from existing decentralized load frequency control methods, this paper studies multi-packet transmission scheme and introduces scheduling protocols to deal with multi-node collision. Considering the scheduling process and decentralized load frequency controllers, an impulsive power system closed-loop model is well established. Furthermore, sufficient stabilization criteria are derived to obtain decentralized output feedback controller gains and scheduling protocol parameters. Under the designed decentralized output feedback controllers, the prescribed system performances have been achieved. Finally, a three-area power system example is used to verify the effectiveness of the proposed scheduling method.

Performance-driven closed-loop model learning with Bayesian optimization for the Car-in-the-Loop test bench control with unknown input

A major control task of a full vehicle test bench is the tracking of the wheel hub speed with disturbance and unknown inputs such as the vehicle drive torque. For this control task, Internal Model Control (IMC) and Linear-Quadratic-Gaussian controller (LQG) are investigated on the quarter-vehicle prototype of a full vehicle test bench concept called Car-in-the-Loop (CiL). In a classic model-based control approach, the identification of the model and the optimization of the controller are carried out separately. The effort for system identification is huge and the sequential approach might result in a suboptimal closed-loop performance. With little prior knowledge of the complex system, we can use Bayesian optimization (BO) to learn a model that explicitly optimizes the control performance directly under closed-loop conditions. Experimental results on the CiL prototype show that similar or better control performance can be achieved with the performance-driven approach for both IMC and LQG.

A geometric multiscale model for the numerical simulation of blood flow in the human left heart

<p style='text-indent:20px;'>We present a new computational model for the numerical simulation of blood flow in the human left heart. To this aim, we use the Navier-Stokes equations in an Arbitrary Lagrangian Eulerian formulation to account for the endocardium motion and we model the cardiac valves by means of the Resistive Immersed Implicit Surface method. To impose a physiological displacement of the domain boundary, we use a 3D cardiac electromechanical model of the left ventricle coupled to a lumped-parameter (0D) closed-loop model of the remaining circulation. We thus obtain a one-way coupled electromechanics-fluid dynamics model in the left ventricle. To extend the left ventricle motion to the endocardium of the left atrium and to that of the ascending aorta, we introduce a preprocessing procedure according to which an harmonic extension of the left ventricle displacement is combined with the motion of the left atrium based on the 0D model. To better match the 3D cardiac fluid flow with the external blood circulation, we couple the 3D Navier-Stokes equations to the 0D circulation model, obtaining a multiscale coupled 3D-0D fluid dynamics model that we solve via a segregated numerical scheme. We carry out numerical simulations for a healthy left heart and we validate our model by showing that meaningful hemodynamic indicators are correctly reproduced.</p>

Hybrid Dynamic Phasor Modeling Approaches for Accurate Closed-Loop Simulation of Power Converters

Modelling the fast dynamics of power converters is of growing concern in power grids and Microgrids. Dynamic phasor (DP) concept has been widely applied to switched power converter for modelling fast transients efficiently due to the inherent frequency shift property of DPs. The dynamics introduced by the DC/AC power converters depend on the controllers, which are implemented either in the stationary frame or on the synchronous reference frame (SRF). Hybrid closed-loop modelling methods that consider DP-based power converter plant model are not established and the applicability and accuracy of such hybrid approaches are not fully understood. This paper attempts to address this gap by proposing two hybrid closed-loop modelling approaches: Hybrid DP-DQ and Hybrid DP-EMT and discusses the applicability and accuracy for various controller types. Furthermore, this paper presents a DP switched model of single and three phase two level power converter and discusses the selection of harmonics to reduce model complexity. The proposed hybrid approaches were validated against detailed switched power converter models and for a wide range of scenarios, the Hybrid DP-EMT method is found to be superior compared other methods. Finally, application dependent recommendations are made for the selection of suitable hybrid closed-loop model for the accurate simulation of single phase and three phase power converters.

Spatial High Precision Scanning Control Method Based on Feedforward Closed-Loop Model Reference Adaptive

The time-modulated Fourier transform spectrometer realizes spectrum detection by scanning the optical path of the corner mirror. During the scanning process, the servo system is required to have high-precision and low-speed characteristics. Aiming at the fluctuation of scanning speed caused by spatial micro-vibration during scanning, a closed-loop model reference adaptive control algorithm based on feedforward is studied. The permanent magnet synchronous linear motor is used to drive the angle mirror to move back and forth along the guide rail to achieve large optical path and high-precision scanning with the maximum optical path difference of ± 34cm, the speed stability ≥ 99%.

Online Iterative Learning Compensation Method Based on Model Prediction for Trajectory Tracking Control Systems

In this article, to guarantee the good tracking performance of the precision motion system for various tracking tasks, an online iterative learning compensation method is proposed for closed-loop motion control systems. The prediction model is based on the closed-loop model of the linear second-order system with a proportional-integral-derivative controller, and an estimation term is added to deal with the influence of slow-varying uncertain disturbances. On the basis of the accurate state prediction, the dynamical feedforward compensation can be obtained, which suppresses the tracking error caused by the dynamical lag. Furthermore, in order to simultaneously compensate the errors caused by nonlinear factors such as uncertain disturbances and to guarantee the smoothness of the compensated trajectory, the optimal compensation gain is determined through online iterative calculation. The online iterative approach is similar to iterative learning control, but does not require several offline iterations of a repeating trajectory. Comparative experiments are carried out on an industrial motion stage. Various experimental results consistently demonstrate that the proposed compensation scheme can achieve the tracking accuracy comparable to iterative learning, while maintaining the robustness to trajectory changes and uncertain disturbances without reoffline iteration.

CIRCULAR ECONOMY AND AGRICULTURAL SECTOR: POINTS OF CONTACT AND PROSPECTS OF SYMBIOSIS

The relevance of the research topic is determined by the fact that in the modern agricultural sector in general the development of economic relations is carried out on a linear principle across countries, the motto of which is the triad “get-recycle-utilize”. However, in modern conditions, the most relevant is the organization of economic relations in the agricultural sector based on the principle of sustainable use of all components of renewable resources, in this regard, innovative business models are needed that determine how to process what is currently considered waste.
 The problem of the study lies in the fact that during the transition of agricultural enterprises to relationships within a circular economy, it is necessary to take into account certain factors that determine both success and risk. This should include technical, logistical, economic, financial and marketing, organizational and spatial, institutional and legal, environmental, social and cultural factors. At the same time, the specific factors for the agricultural sector are innovative conversion technologies, flexible internal and external logistics, joint investments in R&D, price competitiveness, etc.
 The purpose of the study is to consider the points of contact and prospects for the symbiosis of the circular economy and the agricultural sector.
 In the analysis of the material, comparative research methods were used, the consideration of the research topic was carried out on the basis of an analysis of sources and publications covering the main conceptual foundations of the development of the circular economy and the agro-industrial complex.
 The authors concluded that while several success factors are also crucial for closed-loop business models in general, some of them are very specific to those evaluating agricultural waste and by-products.

Computer Network Dynamic Balance Flow Distribution Based on Closed-Loop Particle Swarm Feedback Model

Based on the closed-loop particle swarm feedback model, this paper proposes a graphical method to analyze the stability of the computer network dynamic balance system. First, based on the second-order time delay system model of congestion control, the stability of the system is described by characteristic pseudopolynomials. Secondly, based on the inverse line, the stability of the system is verified by graphical analysis methods, and the PID controller parameter range that guarantees the stability of the system is obtained, and the relationship between the controller proportional gain boundary and the network characteristic parameters is analyzed. Then, based on the analysis of the basic particle swarm optimization algorithm, the particle swarm evolution formula is divided into two parts, its own factors and social factors, and the influence of each part on the evolution speed and position of the particle swarm is analyzed, and an improved particle swarm is proposed. Finally, according to the above analysis, we find the corresponding equation from the appropriate solution in turn, thereby designing a class of particle swarm optimization algorithm with fewer intermediate variables. In view of the system involved in the classical PID control parameter tuning method, the improved particle swarm algorithm is applied to the parameter tuning and optimization of the PID controller. During the experiment, the improved PSO-PID controller optimization algorithm was used in the random early detection algorithm of active queue management, the process of the improved algorithm was researched and designed, and the relevant performance of the improved algorithm was verified through simulation experiments.

A closed-loop multi-scale model for intrinsic frequency-dependent regulation of axonal growth

This article develops a closed-loop multi-scale model for axon length regulation based on a frequency-dependent negative feedback mechanism. It builds on earlier models by linking molecular motor dynamics to signaling delays that then determine signal oscillation period. The signal oscillation is treated as a front end for a signaling pathway that modulates axonal length. This model is used to demonstrate the feasibility of such a mechanism and is tested against two previously published reports in which experimental manipulations were performed that resulted in axon growth. The model captures these observations and yields an expression for equilibrium axonal length. One major prediction of the model is that increasing motor density in the body of an axon results in axonal growth—this idea has not yet been explored experimentally.

Economically independent reverse logistics of customer-centric closed-loop supply chain for herbal medicines and biofuel

With the primary aim to investigate the financial self-reliance of the reverse-chain, present study formulates a cost-efficient and customer-centric closed-loop supply chain model that links the herbal medicines with biofuel. The proposed model simultaneously considers the production of second-generation biofuel from used products in the reverse-chain and the re-manufacturing of casing soil as returnable items in manufacturing-chain to address the environmental concerns and ensure a long-term sustainability. Concurrently, this study ameliorates the satisfaction of the retail customers of herbal medicines along with the large clients of second-generation biofuel. In order to achieve more desirable optimal value of main objective function, the present study develops an emended minmax method based semi-autonomized multi-objective optimization algorithm by amending the classical minmax method. Apart from determining the more desirable optimal values of this model with the proposed algorithm in certitude-state, this study determines another Pareto optimal solution of this model under fuzziness in incertitude-state. The sensitivity analysis of ten key parameters of proposed model together with five graphical patterns advocates for the usages of the advanced equipment at both pharmaceutical plants and recycle-plants. This study asks to cautiously and systematically upgrade the machinery at factory. For legislators, while this study appeals to shoot up the business-commitment of pharmaceutical plants to assure a steady availability of herbal medicines, this favors only a reasonable obligation to procure used substrates by recycle-plants.

A Youla–Kucera formulation of the controller design from data problem

The Youla–Kucera parametrization is a fundamental result in system theory, very useful when designing model-based controllers. In this paper, this formulation is employed to solve the controller design from data problem, without requiring a process model. It is shown that, given a set of input–output data generated by the plant and a desired closed-loop reference model, it is possible to estimate an stable filter that parametrizes the controller that minimizes the norm between the closed-loop dynamics and the requested behavior. The employed parametrization gives more degrees of freedom in the controller design than previous works in literature, allowing to achieve more stringent closed-loop performances. The proposed design methodology does not imply a plant identification step and it provides an estimate of the model-matching error between the requested and the resulting model as indicator of stability and performance of the derived control loop. The proposed solution is evaluated in regulation problems for non-minimum phase systems through Monte Carlo simulations and in experimental conditions for the regulation of temperature in an ohmic assisted hydrodistillation process.

Development of closed-loop modelling framework for adaptive respiratory pacemakers

ObjectiveVentilatory pacing by electrical stimulation of the phrenic nerve has many advantages compared to mechanical ventilation. However, commercially available respiratory pacing devices operate in an open-loop fashion, which require manual adjustment of stimulation parameters for a given patient. Here, we report the model development of a closed-loop respiratory pacemaker, which can automatically adapt to various pathological ventilation conditions and metabolic demands. MethodsTo assist the model design, we have personalized a computational lung model, which incorporates the mechanics of ventilation and gas exchange. The model can respond to the device stimulation where the gas exchange model provides biofeedback signals to the device. We use a pacing device model with a proportional integral (PI) controller to illustrate our approach. ResultsThe closed-loop adaptive pacing model can provide superior treatment compared to open-loop operation. The adaptive pacing stimuli can maintain physiological oxygen levels in the blood under various simulated breathing disorders and metabolic demands. ConclusionWe demonstrate that the respiratory pacing devices with the biofeedback can adapt to individual needs, while the lung model can be used to validate and parametrize the device. SignificanceThe closed-loop model-based framework paves the way towards an individualized and autonomous respiratory pacing device development.

Improved solutions for shared value creation and maximization from used clothes: Streamlined structure of clothing consumption system and a framework of closed loop hybrid business model

Underutilization, downcycling, and landfilling of clothes and their material remain challenging problems of the current clothing consumption system (CCS). Past research and the stakeholders of CCS recognize the circular economy as a solution. However, a review of CCS's existing structure, past research, and publicly available information on its industry practices and solutions reflect potential oversight and partial adoption of the circular economy and the unintended loss of value and market share for brands. Our investigation shows that around two-thirds of sample three hundred brands and brand owners do not engage in value maximization activities from used clothes. Furthermore, only four percent of the sample engages in upcycling, and it remains a niche activity as the availability of similar used clothes remains a primary barrier in scaling it up. This analytical investigation proposes an explicit CCS structure. It supports it with a customizable framework of a closed-loop hybrid business model (CLHBM) as an improved solution to scale up and accelerate reuse, upcycling, and recycling of used clothes. It uses a hypothetical example and stylized model to illustrates the potential of CLHBM-approach to generate higher margins and increase the economic pie for brands while reducing the virgin material pie and increasing the product and material life compared to business-as-usual-approach. The paper concludes with a discussion and recommendations for proposed solutions' successful implementation.