Stability of an analog optimization circuit for quadratic programming

Vichik, Sergey; Arcak, Murat; Borrelli, Francesco

doi:10.1016/j.sysconle.2015.11.006

Cited by 19 publications

(1 citation statement)

References 12 publications

(21 reference statements)

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“…To tackle these problems, advanced optimization methods shed light on developing computer-aided design (CAD) tools to find solutions for demanding specifications and trade-offs [4]. The design process must be more productive, cost-effective, and error-free to achieve reliability and stability [5].…”

Section: Introductionmentioning

confidence: 99%

Optimization techniques for analog and RF circuit designs: an overview

Kouhalvandi

Ceylan²,

Özoğuz

2020

Analog Integr Circ Sig Process

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Optimizations have gained much consideration from the researchers working in the domains of analog and radio frequency (RF), recently. Dealing with highly nonlinear behavior of active components and aiming to meet design specifications are common issues in all nonlinear circuit designs. As a consequence and accordingly, many studies have been conducted on diverse optimization methods and algorithms for tackling the design problems and meeting optimal solutions with high accuracy. The main purpose of this article is to provide a comprehensive and systematic literature review for the optimization approaches applied by the researchers for designing various analog and microwave circuits. We focus on considering the existing optimization methods from the newly published optimization methods in the last decade. Thus, this study can guide and enlighten complementary metal-oxide-semiconductor analog and RF microwave circuit designers to consider optimization methods commonly used in both areas and to expand conventional performance figures used in their area.

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Section: Introductionmentioning

confidence: 99%

Optimization techniques for analog and RF circuit designs: an overview

Kouhalvandi

Ceylan²,

Özoğuz

2020

Analog Integr Circ Sig Process

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Ultrafast Hybrid Computing Systems Enabled by Memristor‐Based Quadratic Programming Circuits

Liu,

Cheng,

Hossain

et al. 2024

Adv Funct Materials

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Implementing algorithms purely on digital computing platforms dramatically halts the performance of conventional computing systems. Revolutionary computing systems with extreme energy efficiency and high accuracy are demanded to handle the growing computing tasks. Here, the research on hybrid analog–digital computing platforms enabled by memristor‐based optimization solvers for achieving ultrafast computations is presented. By utilizing tunable memristors as parameters to solve linear programming (LP) and quadratic programming (QP) problems, a real‐time control algorithm for micro air vehicles (MAVs) and a support vector machine (SVM) algorithm for cancer diagnosis are implemented. These experiments demonstrate over 2000x speed‐up compared to conventional digital platforms, with negligible energy consumption, using a memristor‐based system consisting of six memristors. These findings underscore the vast potential of memristor‐based optimization solvers not only in hybrid analog–digital computing platforms but also as a transformative solution for a wide range of modern computing challenges. This approach promises significant advancements in energy efficiency and ultrafast speed, positioning it as a leading contender for next‐generation computing paradigms.

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A nonlinear model predictive tracking control strategy for modular high-temperature gas-cooled reactors

Wang

Zeng

et al. 2018

Annals of Nuclear Energy

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Stability of an analog optimization circuit for quadratic programming

Cited by 19 publications

References 12 publications

Optimization techniques for analog and RF circuit designs: an overview

Optimization techniques for analog and RF circuit designs: an overview

Ultrafast Hybrid Computing Systems Enabled by Memristor‐Based Quadratic Programming Circuits

A nonlinear model predictive tracking control strategy for modular high-temperature gas-cooled reactors

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