This paper analyzes PROFIBUS-DP network delay in detail and presents the calculational formula of its maximum time-delay, which is significant to the research of PROFIBUS-DP. At the same time, the paper puts forward a...This paper analyzes PROFIBUS-DP network delay in detail and presents the calculational formula of its maximum time-delay, which is significant to the research of PROFIBUS-DP. At the same time, the paper puts forward a method of simplifying the network induced time-varying indeterminate system according to the features of the network. Through the analysis of a pump-control-motor system which is composed of PROFIBUS-DP network, it illustrates the network＇s influence on the performance of control systems. This method helps to design and analyze the network＇s influence on the performance of control systems, which is of considerable practical value in a time when network control systern is widely used.展开更多
The control problem for single-input single-output（SISO） systems in the presence of mixed uncertainties, both stochastic and deterministic uncertainties, is considered. The stochastic uncertainties are modeled as ex...The control problem for single-input single-output（SISO） systems in the presence of mixed uncertainties, both stochastic and deterministic uncertainties, is considered. The stochastic uncertainties are modeled as exogenous noises, while the deterministic uncertainties are time invariant and appear as the unknown parameters which lie in a bounded interval. Based on a subdivision for the continuous interval, a robust adaptive controller is designed. The controller can not only realize the system output to track the desired output, but also learn a more accurate interval which contains the true value of the unknown parameter with a learning error given in advance. An example is given finally to demonstrate the effectiveness of the proposed method.展开更多
Deterministic databases are able to reduce coordination costs in a replication.This property has fostered a significant interest in the design of efficient deterministic concurrency control protocols.However,the state...Deterministic databases are able to reduce coordination costs in a replication.This property has fostered a significant interest in the design of efficient deterministic concurrency control protocols.However,the state-of-the-art deterministic concurrency control protocol Aria has three issues.First,it is impractical to configure a suitable batch size when the read-write set is unknown.Second,Aria running in low-concurrency scenarios,e.g.,a single-thread scenario,suffers from the same conflicts as running in high-concurrency scenarios.Third,the single-version schema brings write-after-write conflicts.To address these issues,we propose Gria,an efficient deterministic concurrency control protocol.Gria has the following properties.First,the batch size of Gria is auto-scaling.Second,Gria’s conflict probability in low-concurrency scenarios is lower than that in high-concurrency scenarios.Third,Gria has no write-after-write conflicts by adopting a multi-version structure.To further reduce conflicts,we propose two optimizations:a reordering mechanism as well as a rechecking strategy.The evaluation result on two popular benchmarks shows that Gria outperforms Aria by 13x.展开更多
In this paper,we consider the mixed optimal control of a linear stochastic system with a quadratic cost functional,with two controllers—one can choose only deterministic time functions,called the deterministic contro...In this paper,we consider the mixed optimal control of a linear stochastic system with a quadratic cost functional,with two controllers—one can choose only deterministic time functions,called the deterministic controller,while the other can choose adapted random processes,called the random controller.The optimal control is shown to exist under suitable assumptions.The optimal control is characterized via a system of fully coupled forward-backward stochastic differential equations(FBSDEs)of mean-field type.We solve the FBSDEs via solutions of two(but decoupled)Riccati equations,and give the respective optimal feedback law for both deterministic and random controllers,using solutions of both Riccati equations.The optimal state satisfies a linear stochastic differential equation(SDE)of mean-field type.Both the singular and infinite time-horizonal cases are also addressed.展开更多
Subject Code:F04 With the support by the National Natural Science Foundation of China,a study by the research group led by Prof.Wang Kaiyou(王开友)from the Institute of Semiconductors,Chinese Academy of Sciences demon...Subject Code:F04 With the support by the National Natural Science Foundation of China,a study by the research group led by Prof.Wang Kaiyou(王开友)from the Institute of Semiconductors,Chinese Academy of Sciences demonstrates all-electric and programmable manipulations of ferromagnetic bits without external展开更多
High-power lasers are vital for particle acceleration,imaging,fusion and materials processing,requiring precise control and high-energy delivery.Laser plasma accelerators(LPAs)demand laser positional stability at focu...High-power lasers are vital for particle acceleration,imaging,fusion and materials processing,requiring precise control and high-energy delivery.Laser plasma accelerators(LPAs)demand laser positional stability at focus to ensure consistent electron beams in applications such as X-ray free-electron lasers and high-energy colliders.Achieving this stability is especially challenging for the low-repetition-rate lasers in current LPAs.We present a machine learning method that predicts and corrects laser pointing instabilities in real-time using a high-frequency pilot beam.By preemptively adjusting a correction mirror,this approach overcomes traditional feedback limits.Demonstrated on the BELLA petawatt laser operating at the terawatt level(30 mJ amplification),our method achieved root mean square pointing stabilization of 0.34 and 0.59μrad in the x and y directions,reducing jitter by 65%and 47%,respectively.This is the first successful application of predictive control for shot-to-shot stabilization in low-repetition-rate laser systems,paving the way for full-energy petawatt lasers and transformative advances across science,industry and security.展开更多
文摘This paper analyzes PROFIBUS-DP network delay in detail and presents the calculational formula of its maximum time-delay, which is significant to the research of PROFIBUS-DP. At the same time, the paper puts forward a method of simplifying the network induced time-varying indeterminate system according to the features of the network. Through the analysis of a pump-control-motor system which is composed of PROFIBUS-DP network, it illustrates the network＇s influence on the performance of control systems. This method helps to design and analyze the network＇s influence on the performance of control systems, which is of considerable practical value in a time when network control systern is widely used.
基金supported by the National Natural Science Foundation of China(61273127U1534208)+2 种基金the Key Program of National Natural Science Foundation of China(61533014)the Key Laboratory for Fault Diagnosis and Maintenance of Spacecraft in Orbit(SDML-OF2015004)the Science and Technology Preject of Shaanxi Province(2016GY-108)
文摘The control problem for single-input single-output（SISO） systems in the presence of mixed uncertainties, both stochastic and deterministic uncertainties, is considered. The stochastic uncertainties are modeled as exogenous noises, while the deterministic uncertainties are time invariant and appear as the unknown parameters which lie in a bounded interval. Based on a subdivision for the continuous interval, a robust adaptive controller is designed. The controller can not only realize the system output to track the desired output, but also learn a more accurate interval which contains the true value of the unknown parameter with a learning error given in advance. An example is given finally to demonstrate the effectiveness of the proposed method.
基金Key Laboratory Ministry of Industry and Information Technology of China,Shenzhen Science and Technology Program(Nos.GXWD20220817124827001 and JCYJ20210324132406016)National Natural Science Foundation of China(Grant No.61732022)National Science Foundation of Guangdong Province(No.2023A1515030273).
文摘Deterministic databases are able to reduce coordination costs in a replication.This property has fostered a significant interest in the design of efficient deterministic concurrency control protocols.However,the state-of-the-art deterministic concurrency control protocol Aria has three issues.First,it is impractical to configure a suitable batch size when the read-write set is unknown.Second,Aria running in low-concurrency scenarios,e.g.,a single-thread scenario,suffers from the same conflicts as running in high-concurrency scenarios.Third,the single-version schema brings write-after-write conflicts.To address these issues,we propose Gria,an efficient deterministic concurrency control protocol.Gria has the following properties.First,the batch size of Gria is auto-scaling.Second,Gria’s conflict probability in low-concurrency scenarios is lower than that in high-concurrency scenarios.Third,Gria has no write-after-write conflicts by adopting a multi-version structure.To further reduce conflicts,we propose two optimizations:a reordering mechanism as well as a rechecking strategy.The evaluation result on two popular benchmarks shows that Gria outperforms Aria by 13x.
基金Lebesgue center of mathematics“Investissements d’avenir”program-ANR-11-LABX-0020-01,by CAESARS-ANR-15-CE05-0024MFG-ANR-16-CE40-0015-01.Tang acknowledges research supported by National Science Foundation of China(Grant No.11631004)Science and Technology Commission of Shanghai Municipality(Grant No.14XD1400400).
文摘In this paper,we consider the mixed optimal control of a linear stochastic system with a quadratic cost functional,with two controllers—one can choose only deterministic time functions,called the deterministic controller,while the other can choose adapted random processes,called the random controller.The optimal control is shown to exist under suitable assumptions.The optimal control is characterized via a system of fully coupled forward-backward stochastic differential equations(FBSDEs)of mean-field type.We solve the FBSDEs via solutions of two(but decoupled)Riccati equations,and give the respective optimal feedback law for both deterministic and random controllers,using solutions of both Riccati equations.The optimal state satisfies a linear stochastic differential equation(SDE)of mean-field type.Both the singular and infinite time-horizonal cases are also addressed.
文摘Subject Code:F04 With the support by the National Natural Science Foundation of China,a study by the research group led by Prof.Wang Kaiyou(王开友)from the Institute of Semiconductors,Chinese Academy of Sciences demonstrates all-electric and programmable manipulations of ferromagnetic bits without external
基金supported by the Office of Science,Office of High Energy Physics,of the US Department of Energythe Laboratory Directed Research and Development Program of Lawrence Berkeley National Laboratory under contract No.DE-AC02-05CH11231。
文摘High-power lasers are vital for particle acceleration,imaging,fusion and materials processing,requiring precise control and high-energy delivery.Laser plasma accelerators(LPAs)demand laser positional stability at focus to ensure consistent electron beams in applications such as X-ray free-electron lasers and high-energy colliders.Achieving this stability is especially challenging for the low-repetition-rate lasers in current LPAs.We present a machine learning method that predicts and corrects laser pointing instabilities in real-time using a high-frequency pilot beam.By preemptively adjusting a correction mirror,this approach overcomes traditional feedback limits.Demonstrated on the BELLA petawatt laser operating at the terawatt level(30 mJ amplification),our method achieved root mean square pointing stabilization of 0.34 and 0.59μrad in the x and y directions,reducing jitter by 65%and 47%,respectively.This is the first successful application of predictive control for shot-to-shot stabilization in low-repetition-rate laser systems,paving the way for full-energy petawatt lasers and transformative advances across science,industry and security.
