25 papers · ranked by Valyu relevance
Jingyi Yang, Yuebao Yang, Mingtao Li
OptControl.jl1 (OptControl) implements that modeling optimal control problems with symbolic algebra system based on Julia language, and generates the corresponding numerical optimization codes to solve them with packages from Julia. OptControl does not define a data type, but generates a solution script by handling…
Sandra Zarychta, Tomasz Sagan, Marek Balcerzak, Artur Dąbrowski + 2 more
'Andrzej Stefański' 'Tomasz Kapitaniak'] This paper presents a novel, Fourier series based numerical method of open-loop control optimization. Due to its flexible assumptions, it can be applied in a large variety of systems, including discontinuous ones or even "black boxes", whose equations are not fully known. This…
Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones
In this paper, the CONFIG algorithm, a simple and provably efficient constrained global optimization algorithm, is applied to optimize the closed-loop control performance of an unknown system with unmodeled constraints. Existing Gaussian process based closedloop optimization methods, either can only guarantee local…
Chuanzhi Lv, Xunmin Yin, Hongdan Li, Huanshui Zhang
—This paper focuses on optimal control problem for a class of discrete-time nonlinear systems. In practical applications, computation time is a crucial consideration when solving nonlinear optimal control problems, especially under real-time constraints. While linearization methods are computationally efficient, their…
Ossama Abdelkhalik, Aimar Negrete
Modern optimal control theory involves adjoining the already known equations of motion of a dynamic system to the objective function using dynamic costates; this is done in order to constrain the optimal control solutions to satisfy the equations of motion. The use of costates increases the number of variables and…
Vitali Vansovits, Eduard Petlenkov, Aleksei Tepljakov, Kristina Vassiljeva + 2 more
In the present paper, a software framework comprising the implementation of Model Predictive Control-a popular industrial control method-is presented. The framework is versatile and can be run on a variety of target systems including programmable logic controllers and distributed control system implementations.…
Timothy Sands
Optimal control is seen by researchers from a different perspective than that from which the industry practitioners see it. Either type of user can easily become confounded when deciding which manner of optimal control should be used for guidance and control of mechanics. Such optimization methods are useful for…
Richard Betzel, Maria Grazia Puxeddu, Caio Seguin, Vincent Bazinet + 9 more
The human brain is never at “rest”; its activity is constantly fluctuating over time, transitioning from one brain state–a whole-brain pattern of activity–to another. Network control theory offers a framework for understanding the effort – energy – associated with these transitions. One branch of control theory that is…
Jiahong Xu, Simon Tomažič
Existing control strategies, such as Real-time Optimization (RTO), Dynamic Real-time Optimization (DRTO), and Economic Model Predictive Control (EMPC) cannot enable optimal operation and control behavior in an optimal fashion. This work proposes a novel control strategy, named the efficiency-oriented model predictive…
Alexander Gorobtsov, Oleg Sychev, Yulia Orlova, Evgeniy Smirnov + 6 more
'Olga Grigoreva' 'Alexander Bochkin' 'Marina Andreeva' 'Anastasios Doulamis' 'Nikolaos Doulamis' 'Athanasios Voulodimos'] We consider the problem of dimensionality reduction of state space in the variational approach to the optimal control problem, in particular, in the reinforcement learning method. The control…
Julio R. Banga, Sebastian Säger
Living organisms exhibit remarkable adaptations across all scales, from molecules to ecosystems. We believe that many of these adaptations correspond to optimal solutions driven by evolution, training, and underlying physical and chemical laws and constraints. While some argue against such optimality principles due to…
Zhiping Fan, Zhengyun Ren, Angang Chen
In this paper, we propose a new priority multi-objective optimization strategy of system output variables in cutting tobacco process. The proposed strategy focuses on the cutting tobacco moisture-controlled output variables optimization in feasible regions with two levels according to the priority. This study aims to…
Feifan Shen, Lingjian Ye, Hongwei Guan, Yuchen He
For control structure design of the industrial off-gas benchmark system, application of the Skogestad's state-of-art design procedure has suggested the scrubber inlet pressure (Psi in the roaster) and one of the fan speeds (Nfan1 or N_fan2 in the furnace) as the self-optimizing controlled variables CVs. In this study…
Sandra Zarychta, Marek Balcerzak, Jerzy Wojewoda
control optimization in application to a discontinuous capsule drive model Authors: ['Sandra Zarychta' 'Marek Balcerzak' 'Jerzy Wojewoda'] The paper explains iterative and non-iterative approaches to control optimization with use of the Fourier series-based method. Both variants of the presented algorithm are used to…
Aidan Slattery, Zhenghui Wen, Pauline Tenblad, Diego Pintossi + 3 more
The optimization, intensification, and scaling up of chemical processes are essential and time-consuming aspects of contemporary chemical manufacturing, necessitating expertise and precision due to their intricate and sensitive nature. However, these process development problems are often carried out independently and…
Mengjia Zhu, Oliver Pennington, Tararag Pincam, Mohammadamin Zarei + 4 more
Bioprocesses are critical for sustainable industrial development but face challenges from their inherent uncertainties that affect efficiency and scalability. This study in-troduces a worst-case operational space design framework, integrating symbolic optimization with scenario-based validation, to preemptively…
Authors not listed
We develop a control-oriented model for manipulating calcium carbonate (CaCO3) precipitation through pH and/or dissolved CO2(aq) adjustments in a semi-batch process. We present two open-loop control strategies: first, a closed-form optimal control solution derived via Pontryagin’s Minimum Principle; and second, an…
Menno van Laarhoven, Alfredo Rates, Josiah B. Passmore, Shengling Shi + 3 more
Optogenetics enables experiments in out-of-equilibrium conditions to clarify biological mechanisms and quantify biophysical parameters. However, modelling and control techniques to study mammalian cell biology under optogenetic perturbation remain underutilised. Here, we benchmark these methods within mammalian cells…
Authors not listed
This paper introduces Optical Fiber Chemistry (OFC) as a fourth-generation catalytic paradigm, distinguished not by incremental improvements in catalyst materials but by a fundamental reconfiguration of the catalytic reaction platform. By employing optical fibers as active photonic control elements, OFC achieves gen-…
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We propose and establish a new catalytic paradigm—\textbf{Optical Fiber Chemistry (OFC)}—as the fourth generation of catalysis after thermocatalysis, electro-/photocatalysis, and photoelectrochemical synergy. OFC is a \textbf{multilayer interfacial chemistry} (planar or curved), with the sandwich-structured optical…
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Artificial intelligence (AI) is reshaping chemical engineering. Still, its role in safety-critical operations is limited because we rarely see tools that link physical models with data-driven methods. This study brings together three elements: physics-constrained neural networks, uncertainty quantification, and a…
Fangzhou Xiao, Jing Shuang Li, John C. Doyle
Metabolic dynamics such as stability of steady states, oscillations, lags and growth arrests in stress responses are important for microbial communities in human health, ecology, and metabolic engineering. Yet it is hard to model due to sparse data available on trajectories of metabolic fluxes. For this reason, a…
Michael P May, Brian Munsky
The field of synthetic biology focuses on creating modular components which can be used to generate complex and controllable synthetic biological systems. Unfortunately, the intrinsic noise of gene regulation can be large enough to break these systems. Noise is largely treated as a nuisance and much past effort has…
Emmanouil Alexis, Clarence W. Rowley, José L. Avalos
Achieving complex multi-species control objectives is essential for engineering advanced autoregulated biomolecular devices. This paper addresses the problem of robust steady-state tracking for outputs defined as multiplicative combinations of biomolecular species concentrations. We first introduce a control…
Authors not listed
This paper formally defines an operational isomorphism between spectral damping in molecular vibronic systems and neuromodulatory control in biological sensory systems. Without asserting causal continuity or physical identity across scales, we show that both domains instantiate the same class of output-selective…