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

作者： Goreac, Dan Li, Juan Wang, Yi Shandong Univ Sch Math & Stat Weihai 264209 Peoples R China Univ Paris Est Creteil Univ Gustave Eiffel CNRS LAMAUPEM F-77447 Marne La Valleee France Shandong Univ Res Ctr Math & Interdisciplinary Sci Qingdao 266237 Peoples R China

ISBN: (纸本)9781713872344

This paper is concerned with the mathematical description of safety (herd immunity and feasible) zones for non-pharmaceutically controlled Brownian-driven compartmental models when intensive care units (ICU) restriction are enforced. The contribution focuses on consistency considerations leading to non-negative and sub-unitary components for possibly non-constant population models. Based on viscosity approaches, a family of conditions allowing to envisage regular-barrier safety zones is provided. Relevant examples of families of noise coefficients are described.

关键词： Safety zones Optimal control theory Stochastic optimal control problems Generalized solutions of Hamilton-Jacobi equations Brownian compartmental models Design of noise coefficients Epidemics dynamics and control Decision support and control Modeling and identification of environmental systems

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Optimal control for Indoor Vertical Farms Based on Crop Growth 22

Optimal Control for Indoor Vertical Farms Based on Crop Grow...

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

作者： Daniels, Annalena Fink, Michael Leibold, Marion Wollherr, Dirk Asseng, Senthold Tech Univ Munich Chair Automat Control Engn Munich Germany Tech Univ Munich Chair Digital Agr Freising Weihenstephan Germany

ISBN: (纸本)9781713872344

Vertical farming allows for year-round cultivation of a variety of crops, overcoming environmental limitations and ensuring food security. This closed and highly controlled system allows the plants to grow in optimal conditions, so that it reaches maturity faster and yields more than on a conventional outdoor farm. However, one of the challenges of vertical farming is the high energy consumption. In this work, we optimize wheat growth using an optimal control approach with two objectives: first, we optimize inputs such as water, radiation, and temperature for each day of the growth cycle and second, we optimize the duration of the plant's growth period to achieve the highest possible yield over a whole year. For this, we use a nonlinear, discrete-time hybrid model based on a simple universal crop model that we adapt to make the optimization more efficient. Using our approach, we find an optimal trade-off between used resources, net profit of the yield, and duration of a cropping period, thus increasing the annual yield of crops significantly while keeping input costs as low as possible. This work demonstrates the high potential of control theory in the discipline of vertical farming. Copyright (c) 2023 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： Modeling and control of agriculture Kinetic modeling and control of biological systems dynamics and control Plant factory Optimal control

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dynamics and control of a gyroscope-stabilized platform in a ship anti-aircraft rocket missile launcher

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Symposium on Mechatronic Systems, Mechanics and Materials

作者： Koruba, Zbigniew Kielce Univ Technol Fac Mechatron & Machine Bldg PL-25314 Kielce Poland

ISBN: (纸本)9783037856185

The paper presents the ways of stabilising and controlling a Ship Anti-Aircraft Rocket Missile Launcher (SAARML) with the use of a Three-Axis Gyroscope-stabilized platform (TAG). The analysis of the dynamics of the SAARML and TAG systems is conducted for the case of searching and tracking a manoeuvring air target in the conditions of interferences and the influence of kinematic forces from the base (ship's deck). Some research results are presented in a graphical form.

关键词： dynamics and control ship missile launcher gyroscope-stabilized platform

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Fish eradication in freshwater ecosystems by repeated fishing 10

Fish eradication in freshwater ecosystems by repeated fishin...

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10th Vienna International Conference on Mathematical Modelling (MATHMOD)

作者： Martinez, Carlos Souza, Allan T. Kubecka, Jan Czech Acad Sci Biol Ctr Inst Hydrobiol Na Sadkach 7 Ceske Budejovice 37005 Czech Republic

The removal of planktivorous fish results in ecosystem changes that increase water transparency and decrease the risk of harmful algal blooms. In many situations, complete eradication of fish is necessary to improve water quality, which can also protect natural populations. In this work, we construct a generic fish-zooplankton (FZ) model and we determine conditions to eradicate the fish population through repeated fish removal. The model accounts for the weight and age of fish, and is described by a system of ordinary differential equations with impulsive effects representing the reproduction process and fish removal. We demonstrate that the survival and extinction of fish can be determined from the roots of a polynomial, whose coefficients depend on maximal fecundity, mortality rates, and catching effort. If all roots of the polynomial lie within the unit circle, then eradication is ensured. To illustrate our results, we show the importance of removing young fish, and not only adults, to achieve eradication. Copyright (C) 2022 The Authors.

关键词： dynamics and control Biomanipulation Fish removal Impulsive differential equation

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Optimal control of Water Quality in a Recirculating Aquaculture System 13th

Optimal Control of Water Quality in a Recirculating Aquacult...

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13th IFAC Symposium on dynamics and control of Process Systems, including Biosystems (DYCOPS)

作者： dos Santos, Allyne M. Attramadal, Kari J. K. Skogestad, Sigurd Norwegian Univ Sci & Technol NTNU Dept Chem Engn NO-7491 Trondheim Norway Norwegian Univ Sci & Technol NTNU Dept Biotechnol & Food Sci NO-7491 Trondheim Norway

This study compares nonlinear model predictive controls, using setpoint tracking objective function (NMPC), and economic objective function (E-NMPC), with a hierarchical control structure of PI controllers applied to the water treatment of a Recirculating Aquaculture System (RAS), which consists of a tank, a biofilter, a stripper and an oxygen cone. Two of the three control structures used in this work consist of an optimization layer on top of proportional integral (PI) control loops or NMPC. The optimization layer reduces the degrees of freedom with an economic objective function by deactivating some of the manipulated variables when choosing between buffer and base addition and location of addition to the system. The third structure consists of a single layer with E-NMPC. The PI control structure is easy to design once we know the relationship between the variables. The PI controllers' performance were satisfactory, but a small back-off would be needed, if the constraints would not be soft constraints, or use of buffer with base would be necessary to improve speed and avoid constraint violation, as some components took more than 6 days to reach the optimal concentration. The NMPC and the E-NMPC performed better: the NMPC was much faster on conducting the controlled variables to optimal conditions, despite not providing optimal economic cost during the trajectory;and the E-NMPC provided a mixture of smooth trajectory and optimal cost. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license(https://***/licenses/by-nc-nd/4.0/)

关键词： Process control applications control of constrained systems dynamics and control Hierarchical multilevel andmultilayer control Optimal operation of water resources systems Model predictive control of water resources systems

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Dynamic Analysis of Aortic Flows: Transient Response of Flow-Compliance and Flow-Resistance When Subjected to Sinusoidal Variations of Input Pressure

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ASME Open Journal of Engineering 2025年 4卷 041004页

作者： Nisar, Syed Anas Banerjee, Debjyoti

The dynamic response of the ascending aorta to sinusoidal pressure inputs using the hyperelastic Mooney–Rivlin model was explored in this study. Flow capacitance models were deployed to estimate the capacity of the aorta by predicting the change in blood volume as a function of the pressure variation. The results gleaned from this study are crucial for understanding the cardiovascular malfunction. The numerical predictions obtained from the hyperelastic model were validated using results in the literature. The numerical model was formulated using nonlinear stress–strain characteristics of aortic tissues, and this strategy provides sufficient accuracy for predicting the response of the aorta to pressure variations (that mirror natural heart rhythms). The results from this study demonstrate the essential role of the aorta in mitigating the effects of pulsatile blood flow, thereby protecting the vascular system from significant pressure spikes by acting as a damper that leverages flow capacitance effects. By emphasizing the need to integrate realistic, patient-specific bio-mechanical properties into simulation models, the results obtained from this study set the stage for advancing diagnostic, therapeutic, and management strategies in cardiovascular therapy. These models can be refined extensively using actual patient data and can provide a platform for future exploration by integrating them into clinical diagnostic systems, which in turn, can improve therapeutic outcomes for cardiovascular patients.

关键词： Fluid dynamics computational foundations for engineering optimization bio-heat and mass transfer fluid mechanics/dynamics fluid mechanics bio-mechanical dynamics design engineering cardiovascular engineering cardiovascular devices dynamics and control cardiovascular diagnostics flexible structures bio-research dynamic systems flows in biological systems complex systems fluidics bio-fluid dynamics flexible-body dynamics fluid friction bio-inspired design computational fluid dynamics (CFD) biomedical simulation fluid instability biomechanics computational engineering fluid control systems Flow (dynamics) electrochemical capacitors Capacitance digital twins applied mechanics complex flows fluid flow Aorta Cardiovascular system Transients (dynamics) fluid–structure interaction damping biologically-inspired methods bio-system sensor dynamics of structures design and control of biological systems biological systems applications Pressure compliant mechanisms compliant mechanism synthesis fluid transients design and design optimization dynamical analysis and method bio-engineering simulation biomedical systems

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Investigating Suitable Combinations of Dynamic Models and control Techniques for Offline Reinforcement Learning Based Navigation: Application of Universal Omni-Wheeled Robots

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ASME Letters in Dynamic Systems and control 2024年第2期4卷 021007页

作者： Amarasiri, Nalaka Barhorst, Alan A. Gottumukkala, Raju Department of Mechanical Engineering University of Louisiana at Lafayette Lafayette LA 70504

Omnidirectional locomotion provides wheeled mobile robots (WMR) with better maneuverability and flexibility, which enhances their energy efficiency and dexterity. Universal omni-wheels are one of the best categories of wheels that can be used to develop a WMR (Amarasiri et al., 2022, “Robust Dynamic Modeling and Trajectory Tracking controller of a Universal Omni-Wheeled Mobile Robot,” ASME Letters Dyn. Sys. control., 2(4), p. 040902. 10.1115/1.4055690). We study dynamic modeling and controllers for mobile robots to train in a reinforcement learning (RL)-based navigation algorithm. RL tasks require copious amounts of learning iteration episodes, which makes training very time consuming. The choice of dynamic model and controller has a significant impact on training time. In this paper, we compare a traditional Kane’s equations model to a non-holonomic canonical momenta model (Barhorst, 2019, “Generalized Momenta in Constrained Non-Holonomic Systems—Another Perspective on the Canonical Equations of Motion,” Int. J. Non-Linear Mech., 113, pp. 128–145.). We implemented four controllers: proportional integral derivative, linear quadratic regulator with integral action, pole placement, and a full nonlinear sliding mode controller. We summarize the pros and cons of each of the modeling techniques, and control laws implemented. The outcomes of our analysis will improve RL training time for path generation in unstructured environments.

关键词： robotics Kane pole placement dynamics and control machine learning Kinematics LQR nonlinear control autonomous systems nonlinear systems agents based systems Dynamic modeling kinematic non-holonomic model validation multibody systems control equipment PID computational methods Dynamic models control applications canonical momenta computer-aided control design modeling vehicle dynamics and control unmanned vehicles sliding mode Momentum Robots mobile robot Pole placement robust control trajectory tracking

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Economic Nonlinear Model Predictive control of Continuous Viral Bioreactors

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IFAC-PapersOnLine 2024年第18期58卷 238-243页

作者： Pavan K. Inguva Luc T. Paoli Richard D. Braatz

Viral particle systems are integral parts of modern biotechnology, finding use in vaccines, drug delivery platforms, and recombinant protein production. Continuous manufacturing of these systems can offer improved manufacturability and quality control. However, viral systems often have complex kinetics which can introduce undesirable process dynamics and lower product titers in continuous operation. This article explores the use of economic nonlinear dynamic optimization and model predictive control to achieve multiple process objectives such as maximizing productivity and/or purity. Economic nonlinear model predictive control is also demonstrated to robustly control the bioreactor under plant-model mismatch in different scenarios.

关键词： dynamics and control Nonlinear process control Model predictive and optimization-based control Advanced manufacturing Industrial biotechnology

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Deep Reinforcement Learning control of Wave Energy Converters 9

Deep Reinforcement Learning Control of Wave Energy Converter...

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9th IFAC Symposium on Mechatronic Systems (MECHATRONICS) / 16th International Conference on Motion and Vibration control (MoViC)

作者： Zou, Shangyan Zhou, Xiang Weaver, Wayne Abdelkhalik, Ossama Oregon State Univ Sch Civil & Construct Engn Corvallis OR 97331 USA Michigan Technol Univ Dept Mech Engn & Engn Mech Houghton MI 49931 USA Iowa State Univ Dept Aerosp Engn Ames IA 50011 USA

One major challenge of converting wave energy to useful electricity is the development of highly efficient Power Take-off (PTO) control algorithms. Conventional model-based controls are typically developed based on reduced-order models and neglecting the dynamics of other subsystems. Although showing promising performance in idealized conditions, it may be misleading in practice. On the other hand, it is nearly impossible to derive a model-based control for a highly nonlinear/complex system (e.g., a wave-to-wire model). Therefore, in this study, we propose a Deep Reinforcement Learning (DRL, model-free) control that aims at/capable of optimizing the performance of WECs from wave to wire. This wave-to-wire model is composed of a heaving point absorber and a direct-drive PTO unit. The numerical simulations are first conducted on comparing the performance of the proposed DRL and conventional model-based controls. The results show maximumly a 152% improvement in terms of the electricity generation and an 84% improvement in terms of the power quality. Moreover, the robustness of the proposed control is also validated under varied real ocean conditions at PacWave. The results indicate a consistent improvement of power production and quality of the proposed DRL control compared to model-based controls. Copyright (c) 2022 The Authors. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0/)

关键词： dynamics and control Renewable Energy System Modeling and Integration control of renewable energy resources Reinforcement learning control Data-Driven Decision Making

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Data-driven Model Reduction for Soft Robots via Lagrangian Operator Inference

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IFAC-PapersOnLine 2024年第17期58卷 91-96页

作者： Harsh Sharma Iman Adibnazari Jacobo Cervera-Torralba Michael T. Tolley Boris Kramer

Data-driven model reduction methods provide a nonintrusive way of constructing computationally efficient surrogates of high-fidelity models for real-time control of soft robots. This work leverages the Lagrangian nature of the model equations to derive structure-preserving linear reduced-order models via Lagrangian Operator Inference and compares their performance with prominent linear model reduction techniques through an anguilliform swimming soft robot model example with 231,336 degrees of freedom. The case studies demonstrate that preserving the underlying Lagrangian structure leads to learned models with higher predictive accuracy and robustness to unseen inputs.

关键词： Model Reduction Robotics Lagrangian and Hamiltonian systems Modeling and Identification dynamics and control

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