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Maximizing batch fermentation efficiency by constrained model-based optimization and predictive control of adenosine triphosphate turnover

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AICHE JOURNAL 2022年第4期68卷 e17555-e17555页

作者： Espinel-Rios, Sebastian Bettenbrock, Katja Klamt, Steffen Findeisen, Rolf Otto von Guericke Univ Lab Syst Theory & Automat Control Magdeburg Germany Max Planck Inst Dynam Complex Tech Syst Anal & Redesign Biol Networks Magdeburg Germany Tech Univ Darmstadt Control & Cyber Phys Syst Lab Darmstadt Germany

We present a constrained model-based optimization and predictive control framework to maximize the production efficiency of batch fermentations based on the core idea of manipulating adenosine triphosphate (ATP) wasting. In many bioprocesses, enforced ATP wasting -rerouting ATP use towards an energetically possibly suboptimal path- allows increasing the metabolic flux towards the product, thereby enhancing product yields and specific productivities. However, this often comes at the expense of lower biomass yields and reduced volumetric productivities. To maximize the overall efficiency, we formulate ATP wasting as a model-based optimal control problem. This allows for balancing trade-offs between different objectives such as product yield and volumetric productivity for batch fermentations. Unlike static metabolic control, one obtains a higher degree of flexibility, adaptability, and competitiveness. This can be advantageous towards achieving a sustainable and economically efficient biotechnology industry. To compensate for model-plant mismatch, disturbances, and uncertainties, we propose not only solving the optimal control problem once. Instead, we exploit the concept of moving horizon model predictive control combined with constraint-based dynamic modeling to capture the fermentation dynamics. The approach is underlined considering the industrially relevant bioproduction of lactate by Escherichia coli. We discuss practical challenges for the described control strategy and provide an outlook towards future developments.

关键词： dynamic enzyme-cost flux balance analysis enforced ATP wasting fermentation model predictive control model-based control optimal control

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Monitoring intracellular metabolite concentrations by moving horizon estimation based on kinetic modeling 22

Monitoring intracellular metabolite concentrations by moving...

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22nd World Congress of the International Federation of Automatic control (IFAC)

作者： Espinel-Rios, Sebastian Slaviero, Giulia Bettenbrock, Katja Klamt, Steffen Findeisen, Rolf Max Planck Inst Dynam Complex Tech Syst Anal & Redesign Biol Networks Magdeburg Germany Tech Univ Darmstadt Control & Cyber Phys Syst Lab Darmstadt Germany

ISBN: (纸本)9781713872344

The biotechnology industry can significantly benefit from new paradigms such as smart manufacturing, digitalization and quality-by-design to render more competitive and robust processes. Real-time monitoring of key process parameters and performance indicators can facilitate the transition toward smart biomanufacturing. Since cells are typically used to catalyze biotechnological processes, online monitoring of the cell's health and intracellular metabolic status is of interest to the bioprocess industry. However, intracellular monitoring is challenging due to the intrinsic physical limitation imposed by the cell wall/membrane and the long time required for analytical measurements. This work outlines how soft sensors based on moving horizon estimation allow inferring the intracellular metabolite concentrations in bioprocesses, even for advanced or complex metabolic systems. For example, it can be applied for monitoring metabolic cybergenetic systems, whereby metabolic pathways are dynamically regulated via genetic circuits and external inputs. The moving horizon estimator uses a kinetic model of the central carbon and energy metabolism that describes the dynamics of the intracellular metabolites. We underline the use of moving horizon estimation considering the anaerobic fermentation of Escherichia coli with optogenetic regulation of the adenosine triphosphate turnover. With the information on the extracellular substrate, product and biomass concentrations, we could reconstruct the internal cell's metabolic state with a good performance. Copyright (c) 2023 The Authors.

关键词： Bioprocess monitoring moving horizon estimation intracellular metabolites kinetic modeling fermentation

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Event-Triggered Bipartite Synchronization of Delayed Inertial Memristive Neural networks With Unknown Disturbances

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IEEE TRANSACTIONS ON control OF NETWORK SYSTEMS 2024年第3期11卷 1408-1419页

作者： Liu, Xiaoyang He, Haibin Cao, Jinde Jiangsu Normal Univ Res Ctr Complex Networks & Swarm Intelligence Sch Comp Sci & Technol Xuzhou 221116 Peoples R China Minist Educ Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Southeast Univ Sch Math Nanjing 210096 Peoples R China

This article focuses on the quasibipartite synchronization problems of delayed inertial memristive neural network (NN) with signed graphs and unknown external disturbances. First, an event-triggered hybrid impulsive mechanism is proposed to save the communication resources. In light of average impulsive interval theory and comparison principle, the range of impulsive effects is discussed so that neither positive nor negative effects disrupt the synchronization of the networks. Second, with the help of NN approximation theory, a neuroadaptive term is developed to resist the effects of unknown disturbances, and several conditions are given for quasibipartite synchronization. Furthermore, the lower bound of the event-triggered intervals demonstrates that Zeno behaviors can be avoided. Finally, the validity of the designed protocol is substantiated by a numerical example.

关键词： Synchronization control systems Biological neural networks Network systems Laplace equations Upper bound Switches Event-triggered control (ETC) hybrid impulsive control inertial memristive neural networks (MNNs) neural network (NN) approximation quasibipartite synchronization

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Graph neural networks for network science: A mini review

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EPL 2025年第2期150卷 21001-21001页

作者： Li, Jia Ji, Yixiu Zhang, Yu Ding, Jie Li, Cong Li, Xiang Fudan Univ Sch Informat Sci & Engn Dept Elect Engn Adapt Networks & Control Lab Shanghai 200433 Peoples R China Fudan Univ Res Inst Intelligent & Complex Syst Shanghai 200433 Peoples R China

Neural networks (GNNs), a class of neural networks specifically designed to handle graph-structured data, have emerged as a hot research topic in fields such as data mining, machine learning, and biomedical engineering. Network science studies the properties and behaviors of complex networks, with graphs serving as the mathematical abstraction of these systems. In recent years, GNN technology has demonstrated significant application potential in network science. In this letter, we provide a mini review of different types of GNNs, as well as their applications in important network science tasks, particularly in nodes and edges identification as well as network robustness. Finally, we discuss the promising future research directions.

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A Tracking control Approach With Sequence-Scaling Lyapunov-Based MPC for Quadruped Robots

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第9期20卷 10728-10737页

作者： Nie, Yingxuan Yuan, Quan Li, Xiang Fudan Univ Sch Informat Sci & Technol Dept Elect Engn Adapt Networks & Control Lab Shanghai 200433 Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Inst Complex Networks & Intelligent Syst Shanghai 201210 Peoples R China Tongji Univ Frontiers Sci Ctr Intelligent Autonomous Syst Shanghai 201210 Peoples R China Tongji Univ State Key Lab Intelligent Autonomous Syst Shanghai 201210 Peoples R China

This article studies the tracking control problem of an autonomous quadruped robot (AQR). A new kinematic model is presented to describe both the translation mode and the rotation mode of the AQR using the same number of inputs as compared with the linear inverted pendulum model. We newly propose a sequence-scaling Lyapunov-based model predictive control algorithm for the AQR to improve the tracking performance. Within the control framework, the sequence-scaling strategy is introduced to optimize the tracking, and simultaneously guarantee the closed-loop stability. The practical constraints, such as dynamic balance of motion and speed limits, are explicitly considered to provide a feasible tracking trajectory to the AQR. We analytically address the closed-loop stability, where a contraction constraint is built within the gait sequence. Simulation and hardware experiments on Unitree Aliengo witness the superior real-time control performance via the proposed algorithm.

关键词： Autonomous quadruped robot (AQR) Lyapunov theory model predictive control (MPC) tracking control

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Improved Fixed-Time Event-Triggered Average Consensus of Multi-Agent Systems Under DoS Attacks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2024年第8期71卷 3815-3819页

作者： Hui, Minghao Liu, Xiaoyang Cao, Jinde Jiangsu Normal Univ Res Ctr Complex Networks & Swarm Intelligence Sch Comp Sci & Technol Xuzhou 221116 Peoples R China Minist Educ Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Southeast Univ Sch Math Nanjing 210096 Peoples R China

This brief investigates the fixed-time average consensus (FxTAC) of nonlinear multi-agent systems (MASs) subjected to denial-of-service (DoS) attacks. Some less conservative fixed-time criterions are proposed to handle with DoS attacks. Then, the attainment of FxTAC is realized through the implementation of distributed event-triggered control (ETC). Moreover, the newly proposed average consensus control strategies effectively prevent the occurrence of Zeno behavior. Finally, a numerical example is proposed to verify the validity of the theoretical results.

关键词： Fixed-time average consensus event-triggered control denial-of-service attacks nonlinear multi-agent systems Fixed-time average consensus event-triggered control denial-of-service attacks nonlinear multi-agent systems

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Further Results on Fixed-Time Leader-Following Consensus of Heterogeneous Multiagent Systems With External Disturbances

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2024年第1期54卷 416-425页

作者： Liu, Xiaoyang Wang, Luxiang Cao, Jinde Jiangsu Normal Univ Res Ctr Complex Networks & Swarm Intelligence Sch Comp Sci & Technol Xuzhou 221116 Peoples R China Minist Educ Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China Southeast Univ Sch Math Nanjing 210096 Peoples R China Yonsei Univ Yonsei Frontier Lab Seoul 03722 South Korea

This article considers some further results on fixed-time leader-following consensus of disturbed heterogeneous multiagent systems (DHMASs). Both the first-order (FO) nonlinear nodes and second-order (SO) ones are contained in the considered system model. First, a distributed observer is developed to ensure the estimated states converge to the leader's real states under a directed graph. Second, an integral sliding mode controller (SMC) is proposed to guarantee the predefined-time consensus (PTC) of FO agents based on the Gudermannian functions. Third, a nonsingular terminal SMC is given to realize consensus of SO agents in a predefined time. It is pointed out that, both the reaching and sliding time can be preset as to the task requirements. Finally, the effectiveness of new designs are illustrated by two numerical examples.

关键词： Observers Multi-agent systems Directed graphs Uncertainty Task analysis Cybernetics Convergence External disturbances fixed-time control heterogeneous multiagent systems (MASs) predefined-time consensus (PTC) sliding mode control

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Finite-Time Predictive Consensus for Discrete-Time Heterogeneous Multi-Agent Systems Over Switching Digraphs

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2023年第6期70卷 2136-2140页

作者： Li, Huiyan Li, Xiang Fudan Univ Elect Engn Dept Adapt Networks & Control Lab Shanghai 200433 Peoples R China Tongji Univ Inst Complex Networks & Intelligent Syst Frontiers Sci Ctr Intelligent Autonomous Syst State Key Lab Intelligent Autonomous Syst Shanghai 201210 Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Shanghai 201210 Peoples R China

This brief investigates the finite-time consensus of discrete-time heterogeneous multi-agent systems with the predictive mechanism on switching digraphs. By optimizing the consensus problem, a fully distributed model predictive controller in the analytical form is developed. Moreover, sufficient conditions are obtained, and the finite-time stability is guaranteed with an explicit settling time. Numerical examples illustrate the effectiveness of the designed controller and the validity of the derived theoretical results.

关键词： Consensus heterogeneous multi-agent systems discrete-time systems finite-time model predictive control

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On Evolutionary Vaccination Game in Activity-Driven networks

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2023年第1期10卷 142-152页

作者： Han, Dun Li, Xiang Fudan Univ Adapt Networks & Control Lab Dept Elect Engn Shanghai 200433 Peoples R China Fudan Univ Res Ctr Smart Networks & Syst Sch Informat Sci & Engn Shanghai 200433 Peoples R China Jiangsu Univ Sch Math Sci Zhenjiang 212013 Jiangsu Peoples R China Tongji Univ Shanghai Res Inst Intelligent Autonomous Syst Inst Complex Networks & Intelligent Syst Shanghai 201210 Peoples R China

Since human face-to-face communications change over time, their perceived probabilities associated with uncertain outcomes usually present a nonlinear fashion in reality. This article incorporates both humans active characteristics and risk perception into epidemic spreading and explores a comprehensive evolutionary vaccination game in activity-driven networks. According to the weighting effect, the individuals' activity rate thresholds are obtained in different cases under the framework of the pure Nash equilibrium. Furthermore, how the number of connected edges of activated individuals m and infection rate lambda affect individuals' vaccination, decision-making is theoretically analyzed. It is proven that some unvaccinated individuals gradually become vaccinated individuals with the increase of m or lambda. Moreover, there is a unique pure Nash equilibrium social state (Pareto optimization), and the pure Nash equilibrium together with Pareto optimization has the same equilibrium for our proposed evolutionary vaccination game, which provides an alternative condition judging the stability of game system. In the case of complete information and individual complete rationality, the factors, including vaccination cost, individuals' activity rate, the number of connected edges of activated individuals, and infection rate, have a significant influence on the final average social cost.

关键词： Vaccines Games Costs Statistics Sociology Epidemics Nash equilibrium Activity-driven networks pure Nash equilibrium vaccination weighting effect

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The Selection of the Comparative Evaluation Method of the Effectiveness of the Insurance Company Branches 15

The Selection of the Comparative Evaluation Method of the Ef...

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15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Kozlov, Aleksandr Noga, Nikolai V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Complex Networks Lab Moscow Russia

The authors propose the comparative analysis of the various ranking methods usage to determine the effectiveness of the branches of an extensive insurance company. In turn, the effectiveness of the branches is conside... 详细信息

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

关键词： Hamming distance

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