scholarly journals Future systems and control research in synthetic biology

2018 ◽  
Vol 45 ◽  
pp. 5-17 ◽  
Author(s):  
Domitilla Del Vecchio ◽  
Yili Qian ◽  
Richard M. Murray ◽  
Eduardo D. Sontag
2018 ◽  
Vol 45 ◽  
pp. 1-4 ◽  
Author(s):  
Pramod P. Khargonekar ◽  
Munther A. Dahleh

2014 ◽  
Vol 136 (06) ◽  
pp. S15-S21 ◽  
Author(s):  
Scott J. Moura ◽  
Hector E. Perez

This article introduces key concepts in Electrochemical-based Control (ECC) systems for batteries, and highlights the fundamentals of battery electrochemistry, state-of-charge/state-of-health (SOC/SOH) estimation, and constrained control. Research on battery SOC/SOH estimation has experienced considerable growth, and can be categorized under equivalent circuit models (ECM) or EChem model-based algorithms. EChem models capture the spatiotemporal dynamics of lithium-ion concentration, electric potential, and intercalation kinetics. The most fundamental reduced EChem model is the single-particle model (SPM). The SPM idealizes each electrode as a single aggregate spherical particle. Advanced control systems that optimize battery performance and longevity are a key enabler for reducing costs and catalyzing deeper penetration into transportation fleets and electric power grids. The dynamic systems and control community are uniquely positioned to play a significant role, as batteries provide a rich opportunity for advancements in fundamental control science and emerging energy application areas.


2020 ◽  
Vol 50 ◽  
pp. 343-344
Author(s):  
Esteban A. Hernandez-Vargas ◽  
Giulia Giordano ◽  
Eduardo Sontag ◽  
J. Geoffrey Chase ◽  
Hyeygjeon Chang ◽  
...  

Author(s):  
Esteban A. Hernandez-Vargas ◽  
Giulia Giordano ◽  
Eduardo Sontag ◽  
J. Geoffrey Chase ◽  
Hyeygjeon Chang ◽  
...  

2002 ◽  
Author(s):  
Christopher Barnes ◽  
Linda R. Elliott ◽  
Phil Tessier ◽  
Plamen Petrov

Author(s):  
Joseph Ayers

This chapter describes how synthetic biology and organic electronics can integrate neurobiology and robotics to form a basis for biohybrid robots and synthetic neuroethology. Biomimetic robots capture the performance advantages of animal models by mimicking the behavioral control schemes evolved in nature, based on modularized devices that capture the biomechanics and control principles of the nervous system. However, current robots are blind to chemical senses, difficult to miniaturize, and require chemical batteries. These obstacles can be overcome by integration of living engineered cells. Synthetic biology seeks to build devices and systems from fungible gene parts (gene systems coding different proteins) integrated into a chassis (induced pluripotent eukaryotic cells, yeast, or bacteria) to produce devices with properties not found in nature. Biohybrid robots are examples of such systems (interacting sets of devices). A nascent literature describes genes that can mediate organ levels of organization. Such capabilities, applied to biohybrid systems, portend truly biological robots guided, controlled, and actuated solely by life processes.


2001 ◽  
Vol 2001 (1) ◽  
pp. 32-34 ◽  
Author(s):  
Clive Seager

2021 ◽  
Vol 62 ◽  
pp. 68-75
Author(s):  
Giansimone Perrino ◽  
Andreas Hadjimitsis ◽  
Rodrigo Ledesma-Amaro ◽  
Guy-Bart Stan

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