In the fed-batch cultivation of Saccharomyces cerevisiae,excessive glucose addition leads to increased ethanol accumulation,which will reduce the efficiency of glucose utilization and inhibit product synthesis.Insuffi...In the fed-batch cultivation of Saccharomyces cerevisiae,excessive glucose addition leads to increased ethanol accumulation,which will reduce the efficiency of glucose utilization and inhibit product synthesis.Insufficient glucose addition limits cell growth.To properly regulate glucose feed,a different evolution algorithm based on self-adaptive control strategy was proposed,consisting of three modules(PID,system identification and parameter optimization).Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations.In the simulation,cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration,more stable ethanol concentration around the set-point(1.0 g·L^(-1)),and final biomass concentration of 34.5 g-DCW·L^(-1),29.2%higher than that with a conventional PID control strategy.In the experiment,the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations,as well as a final biomass concentration that was 37.4%higher than that using the conventional strategy.展开更多
Aimed at problems such as profile error increasing and acceleration enlarging and tool machine working instability and quality decreasing of workpiece surfaces in processing complicated curved surfaces because of seve...Aimed at problems such as profile error increasing and acceleration enlarging and tool machine working instability and quality decreasing of workpiece surfaces in processing complicated curved surfaces because of several variable curvatures, an improved method of NURBS interpolation is adopted. According to self-adaptive programming principles, self-adaptive control of profile errors and accelerations and speed-converting is realized with increasing or descending self-adaptive control strategy. This method meets real-time and high-precision requirements of high speed and precision processing, and solves various problems caused by several variable curvatures of a complicated surface.展开更多
A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the princi...A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.展开更多
Wire arc additive manufacturing(WAAM)has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost.However,in the process of automatically manufacturing the high-...Wire arc additive manufacturing(WAAM)has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost.However,in the process of automatically manufacturing the high-quality metal parts by WAAM,several problems about the heat build-up,the deposit-path optimization,and the stability of the process parameters need to be well addressed.To overcome these issues,a new WAAM method based on the double electrode micro plasma arc welding(DE-MPAW)was designed.The circuit principles of different metal-transfer models in the DE-MPAW deposition process were analyzed theoretically.The effects between the parameters,wire feed rate and torch stand-off distance,in the process of WAAM were investigated experimentally.In addition,a real-time DE-MPAW control system was developed to optimize and stabilize the deposition process by self-adaptively changing the wire feed rate and torch stand-off distance.Finally,a series of tests were performed to evaluate the control system’s performance.The results show that the capability against interferences in the process of WAAM has been enhanced by this self-adaptive adjustment system.Further,the deposition paths about the metal part’s layer heights in WAAM are simplified.Finally,the appearance of the WAAM-deposited metal layers is also improved with the use of the control system.展开更多
A self-adaptive control method is proposed based on an artificial neural network(ANN)with accelerated evolutionary programming(AEP)algorithm.The neural network is used to model the uncertainty process,from which the t...A self-adaptive control method is proposed based on an artificial neural network(ANN)with accelerated evolutionary programming(AEP)algorithm.The neural network is used to model the uncertainty process,from which the teacher signals are produced online to regulate the parameters of the controller.The accelerated evolutionary programming is used to train the neural network.The experiment results show that the method can obviously improve the dynamic performance of uncertainty systems.展开更多
Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to...Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network system.Finally, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.展开更多
This paper analyzes a self-adaptive Quality of Service (QoS) control architecture for cognitive networks (CNs) that is based on intelligent service awareness. In this architecture, packets can be identified and cl...This paper analyzes a self-adaptive Quality of Service (QoS) control architecture for cognitive networks (CNs) that is based on intelligent service awareness. In this architecture, packets can be identified and classified using an intelligent service-aware classification model. Drawing on Control Theory, network traffic can be controlled with a self-adaptive QoS control mechanism that has side-road collaboration. In this architecture, perception, analysis, correlation, feedback, decision making, allocation, and implementation QoS mechanisms are created automatically. These mechanisms can adjust resource allocation, adapt to a changeable network environment, optimize end-to-end performance of the network, and ensure QoS.展开更多
The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and wi...The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.展开更多
Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.展开更多
A self-adaptive resource provisioning on demand is a critical factor in cloud computing.The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests.Therefore,a self-adaptive...A self-adaptive resource provisioning on demand is a critical factor in cloud computing.The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests.Therefore,a self-adaptive strategy of resources is required to deal with dynamic nature of requests based on run time change in workload.In this paper we proposed a Cloud-based Adaptive Resource Scheduling Strategy(CARSS)Framework that formally addresses these issues and is more expressive than traditional approaches.The decision making in CARSS is based on more than one factors.TheMAPE-K based framework determines the state of the resources based on their current utilization.Timed-Arc Petri Net(TAPN)is used to model system formally and behaviour is expressed in TCTL,while TAPAAL model checker verifies the underline properties of the system.展开更多
The bulk/surface states of semiconductor photocatalysts are imperative parameters to maneuver their performance by significantly affecting the key processes of photocatalysis including light absorption,separation of c...The bulk/surface states of semiconductor photocatalysts are imperative parameters to maneuver their performance by significantly affecting the key processes of photocatalysis including light absorption,separation of charge carrier,and surface site reaction.Recent years have witnessed the encouraging progress of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z) for photocatalytic applications spanning various fields.However,despite the maturity of current research,the interaction between the bulk/surface state and the performance of Bi_(x)O_(y)Br_(z) has not yet been fully understood and highlighted.In this regard,a timely tutorial overview is quite urgent to summarize the most recent key progress and outline developing obstacles in this exciting area.Herein,the structural characteristics and fundamental principles of Bi_(x)O_(y)Br_(z)for driving photocatalytic reaction as well as related key issues are firstly reviewed.Then,we for the first time summarized different self-adaptive engineering processes over Bi_(x)O_(y)Br_(z)followed by a classification of the generation approaches towards diverse Bi_(x)O_(y)Br_(z)materials.The features of different strategies,the up-to-date characterization techniques to detect bulk/surface states,and the effect of bulk/surface states on improving the photoactivity of Bi_(x)O_(y)Br_(z)in expanded applications are further discussed.Finally,the present research status,challenges,and future research opportunities of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z)are prospected.It is anticipated that this critical review can trigger deeper investigations and attract upcoming innovative ideas on the rational design of Bi_(x)O_(y)Br_(z)-based photocatalysts.展开更多
Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and ...Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.展开更多
An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control...An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control algorithm can update the control law online through real-time data to make the controller adapt to the environment and improve the control precision.Specifically,based on the adaptive backstepping framework,virtual control laws and Lyapunov functions are designed for each subsystem.Three direction interference observers are designed to track the timevarying boundary disturbance.On this basis,the inverse of the dead zone and linear state transformation are used to compensate for the original system and eliminate the adverse effects of the dead zone.In addition,the stability of the closed-loop system is proven by Lyapunov stability theory.All the system states are bounded,and the vibration offset of the riser converges to a small area of the initial position.Finally,four examples of flexible marine risers are simulated in MATLAB to verify the effectiveness of the proposed controller.展开更多
The stamping-out strategy has been used to control highly pathogenic avian influenza viruses in many countries,driven by the belief that vaccination would not be successful against such viruses and fears that avian in...The stamping-out strategy has been used to control highly pathogenic avian influenza viruses in many countries,driven by the belief that vaccination would not be successful against such viruses and fears that avian influenza virus in vaccinated birds would evolve more rapidly and pose a greater risk to humans.In this review,we summarize the successes in controlling highly pathogenic avian influenza in China and make suggestions regarding the requirements for vaccine selection and effectiveness.In addition,we present evidence that vaccination of poultry not only eliminates human infection with avian influenza virus,but also significantly reduces and abolishes some harmful characteristics of avian influenza virus.展开更多
The paper discusses the features of the Biomass Boiler drum water level. Conventional PID Control System can not reach a satisfaction result in nonlinearity and time different from Biomass Boiler Drum Water Control Sy...The paper discusses the features of the Biomass Boiler drum water level. Conventional PID Control System can not reach a satisfaction result in nonlinearity and time different from Biomass Boiler Drum Water Control System. In this study, a kind of fuzzy self-adaptive PID controller is described and this controller is used in biomass boiler’s drum water level control system. Using the simulink tool of MATLAB simulation software to simulate the fuzzy adaptive PID and conventional PID control system, the result of the comparison shows that the fuzzy self-adaptive PID has the strong anti-jamming, flexibility and adaptability as well as the higher control precision in Biomass Boiler Drum Water.展开更多
The welding wire feed mechanism is an important component of welding equipment, both reliability and stabilization are the premise that the welding quality can be ensured. The PID is currently adapted to control the w...The welding wire feed mechanism is an important component of welding equipment, both reliability and stabilization are the premise that the welding quality can be ensured. The PID is currently adapted to control the welding wire feed mechanism, although the fuzzy PID has advantage of fast response and adaptation, the precision of fuzzy PID is lower. Accordingly, the fuzzy self-adaptive PID controller was proposed through changing fuzzy input variables and output variables based on variable universe, simple furwtion is adopted as scaling factor, the fuzzy PID controller parameters are adjusted to improve the precision and adjustment range. Simulation results show that control effects of fuzzy self-adaptive PID adopted by the welding wire feed mechanism have good adaptive ability and robustness based on variable universe, the welding experiments indicate that the welding quality met the requirements actually.展开更多
The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access cont...The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.展开更多
The fatigue damage caused by flow-induced vibration(FIV)is one of the major concerns for multiple cylindrical structures in many engineering applications.The FIV suppression is of great importance for the security of ...The fatigue damage caused by flow-induced vibration(FIV)is one of the major concerns for multiple cylindrical structures in many engineering applications.The FIV suppression is of great importance for the security of many cylindrical structures.Many active and passive control methods have been employed for the vibration suppression of an isolated cylinder undergoing vortex-induced vibrations(VIV).The FIV suppression methods are mainly extended to the multiple cylinders from the vibration control of the isolated cylinder.Due to the mutual interference between the multiple cylinders,the FIV mechanism is more complex than the VIV mechanism,which makes a great challenge for the FIV suppression.Some efforts have been devoted to vibration suppression of multiple cylinder systems undergoing FIV over the past two decades.The control methods,such as helical strakes,splitter plates,control rods and flexible sheets,are not always effective,depending on many influence factors,such as the spacing ratio,the arrangement geometrical shape,the flow velocity and the parameters of the vibration control devices.The FIV response,hydrodynamic features and wake patterns of the multiple cylinders equipped with vibration control devices are reviewed and summarized.The FIV suppression efficiency of the vibration control methods are analyzed and compared considering different influence factors.Further research on the FIV suppression of multiple cylinders is suggested to provide insight for the development of FIV control methods and promote engineering applications of FIV control methods.展开更多
This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control l...This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control logic based on an on-chip delay-locked loop(DLL).The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter(CDAC)than the synchronous and asynchronous SAR ADC.Therefore,the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent.In addition,the fore-ground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter(FIR-BPF)based least-mean-square(LMS)algorithm in an off-chip FPGA(field programmable gate array).Fabricated in 40-nm CMOS process,the proto-type ADC achieves 94.02-dB spurious-free dynamic range(SFDR),and 75.98-dB signal-to-noise-and-distortion ratio(SNDR)for a 2.88-MHz input under 18-MSPS sampling rate.展开更多
The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct facto...The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct factors such as ischemia,hypoxia,excitotoxicity,and toxicity of free hemoglobin and its degradation products,which trigger mitochondrial dysfunction.Dysfunctional mitochondria release large amounts of reactive oxygen species,inflammatory mediators,and apoptotic proteins that activate apoptotic pathways,further damaging cells.In response to this array of damage,cells have adopted multiple mitochondrial quality control mechanisms through evolution,including mitochondrial protein quality control,mitochondrial dynamics,mitophagy,mitochondrial biogenesis,and intercellular mitochondrial transfer,to maintain mitochondrial homeostasis under pathological conditions.Specific interventions targeting mitochondrial quality control mechanisms have emerged as promising therapeutic strategies for subarachnoid hemorrhage.This review provides an overview of recent research advances in mitochondrial pathophysiological processes after subarachnoid hemorrhage,particularly mitochondrial quality control mechanisms.It also presents potential therapeutic strategies to target mitochondrial quality control in subarachnoid hemorrhage.展开更多
文摘In the fed-batch cultivation of Saccharomyces cerevisiae,excessive glucose addition leads to increased ethanol accumulation,which will reduce the efficiency of glucose utilization and inhibit product synthesis.Insufficient glucose addition limits cell growth.To properly regulate glucose feed,a different evolution algorithm based on self-adaptive control strategy was proposed,consisting of three modules(PID,system identification and parameter optimization).Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations.In the simulation,cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration,more stable ethanol concentration around the set-point(1.0 g·L^(-1)),and final biomass concentration of 34.5 g-DCW·L^(-1),29.2%higher than that with a conventional PID control strategy.In the experiment,the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations,as well as a final biomass concentration that was 37.4%higher than that using the conventional strategy.
文摘Aimed at problems such as profile error increasing and acceleration enlarging and tool machine working instability and quality decreasing of workpiece surfaces in processing complicated curved surfaces because of several variable curvatures, an improved method of NURBS interpolation is adopted. According to self-adaptive programming principles, self-adaptive control of profile errors and accelerations and speed-converting is realized with increasing or descending self-adaptive control strategy. This method meets real-time and high-precision requirements of high speed and precision processing, and solves various problems caused by several variable curvatures of a complicated surface.
基金Supported by China Automobile Test Cycle Development Project(CATC2015)
文摘A variable parameter self-adaptive control strategy based on driving condition identification is proposed to take full advantage of the fuel saving potential of the plug-in hybrid electric bus(PHEB).Firstly,the principal component analysis(PCA)and the fuzzy c-means clustering(FCM)algorithm is used to construct the comprehensive driving cycle,congestion driving cycle,urban driving cycle and suburban driving cycle of Chinese urban buses.Secondly,an improved particle swarm optimization(IPSO)algorithm is proposed,and is used to optimize the control parameters of PHEB under different driving cycles,respectively.Then,the variable parameter self-adaptive control strategy based on driving condition identification is given.Finally,for an actual running vehicle,the driving condition is identified by relevance vector machine(RVM),and the corresponding control parameters are selected to control the vehicle.The simulation results show that the fuel consumption of using the variable parameter self-adaptive control strategy is reduced by 4.2% compared with that of the fixed parameter control strategy,and the feasibility of the variable parameter self-adaptive control strategy is verified.
基金Supported by National Natural Science Foundation of China(Grant No.51665034).
文摘Wire arc additive manufacturing(WAAM)has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost.However,in the process of automatically manufacturing the high-quality metal parts by WAAM,several problems about the heat build-up,the deposit-path optimization,and the stability of the process parameters need to be well addressed.To overcome these issues,a new WAAM method based on the double electrode micro plasma arc welding(DE-MPAW)was designed.The circuit principles of different metal-transfer models in the DE-MPAW deposition process were analyzed theoretically.The effects between the parameters,wire feed rate and torch stand-off distance,in the process of WAAM were investigated experimentally.In addition,a real-time DE-MPAW control system was developed to optimize and stabilize the deposition process by self-adaptively changing the wire feed rate and torch stand-off distance.Finally,a series of tests were performed to evaluate the control system’s performance.The results show that the capability against interferences in the process of WAAM has been enhanced by this self-adaptive adjustment system.Further,the deposition paths about the metal part’s layer heights in WAAM are simplified.Finally,the appearance of the WAAM-deposited metal layers is also improved with the use of the control system.
基金Key Equipment Project of China Petroleum & Chemical Corporation(SINOPEC)(No.J W05008)
文摘A self-adaptive control method is proposed based on an artificial neural network(ANN)with accelerated evolutionary programming(AEP)algorithm.The neural network is used to model the uncertainty process,from which the teacher signals are produced online to regulate the parameters of the controller.The accelerated evolutionary programming is used to train the neural network.The experiment results show that the method can obviously improve the dynamic performance of uncertainty systems.
基金the State Grid Liaoning Electric Power Supply Co.,Ltd.(Research on Scheduling Decision Technology Based on Interactive Reinforcement Learning for Adapting High Proportion of New Energy,No.2023YF-49).
文摘Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network system.Finally, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.
基金funded by the National High Technology Research and Development Planning ("863"Project) under Grant No. 2006AA01Z232, 2009AA01Z212, 2009AA01Z202the National Natural Science Foundation Project under Grant No. 61003237
文摘This paper analyzes a self-adaptive Quality of Service (QoS) control architecture for cognitive networks (CNs) that is based on intelligent service awareness. In this architecture, packets can be identified and classified using an intelligent service-aware classification model. Drawing on Control Theory, network traffic can be controlled with a self-adaptive QoS control mechanism that has side-road collaboration. In this architecture, perception, analysis, correlation, feedback, decision making, allocation, and implementation QoS mechanisms are created automatically. These mechanisms can adjust resource allocation, adapt to a changeable network environment, optimize end-to-end performance of the network, and ensure QoS.
基金Project(51090385) supported by the Major Program of National Natural Science Foundation of ChinaProject(2011IB001) supported by Yunnan Provincial Science and Technology Program,China+1 种基金Project(2012DFA70570) supported by the International Science & Technology Cooperation Program of ChinaProject(2011IA004) supported by the Yunnan Provincial International Cooperative Program,China
文摘The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design.
基金supported in part by the National Natural Science Foundation of China(62222301, 62073085, 62073158, 61890930-5, 62021003)the National Key Research and Development Program of China (2021ZD0112302, 2021ZD0112301, 2018YFC1900800-5)Beijing Natural Science Foundation (JQ19013)。
文摘Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, respectively.Then, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation significantly.Finally, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
文摘A self-adaptive resource provisioning on demand is a critical factor in cloud computing.The selection of accurate amount of resources at run time is not easy due to dynamic nature of requests.Therefore,a self-adaptive strategy of resources is required to deal with dynamic nature of requests based on run time change in workload.In this paper we proposed a Cloud-based Adaptive Resource Scheduling Strategy(CARSS)Framework that formally addresses these issues and is more expressive than traditional approaches.The decision making in CARSS is based on more than one factors.TheMAPE-K based framework determines the state of the resources based on their current utilization.Timed-Arc Petri Net(TAPN)is used to model system formally and behaviour is expressed in TCTL,while TAPAAL model checker verifies the underline properties of the system.
基金the National Natural Science Foundation of China(22102126)the Natural Science Foundation of Hubei Province(2020CFB124)+2 种基金the Key Laboratory of Hubei Province for Coal Conversion and New Carbon Materials(Wuhan University of Science and Technology)the Hubei Provincial Department of Education for the"Chutian Scholar"programthe support of the"CUG Scholar"Scientific Research Funds at China University of Geosciences(Wuhan)(Project No.2022187)。
文摘The bulk/surface states of semiconductor photocatalysts are imperative parameters to maneuver their performance by significantly affecting the key processes of photocatalysis including light absorption,separation of charge carrier,and surface site reaction.Recent years have witnessed the encouraging progress of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z) for photocatalytic applications spanning various fields.However,despite the maturity of current research,the interaction between the bulk/surface state and the performance of Bi_(x)O_(y)Br_(z) has not yet been fully understood and highlighted.In this regard,a timely tutorial overview is quite urgent to summarize the most recent key progress and outline developing obstacles in this exciting area.Herein,the structural characteristics and fundamental principles of Bi_(x)O_(y)Br_(z)for driving photocatalytic reaction as well as related key issues are firstly reviewed.Then,we for the first time summarized different self-adaptive engineering processes over Bi_(x)O_(y)Br_(z)followed by a classification of the generation approaches towards diverse Bi_(x)O_(y)Br_(z)materials.The features of different strategies,the up-to-date characterization techniques to detect bulk/surface states,and the effect of bulk/surface states on improving the photoactivity of Bi_(x)O_(y)Br_(z)in expanded applications are further discussed.Finally,the present research status,challenges,and future research opportunities of self-adaptive bulk/surface engineered Bi_(x)O_(y)Br_(z)are prospected.It is anticipated that this critical review can trigger deeper investigations and attract upcoming innovative ideas on the rational design of Bi_(x)O_(y)Br_(z)-based photocatalysts.
基金supported by the Postdoctoral Science Foundation of China under Grant No.2020M683736partly by the Teaching reform project of higher education in Heilongjiang Province under Grant No.SJGY20210456+2 种基金partly by the Natural Science Foundation of Heilongjiang Province of China under Grant No.LH2021F038partly by the Haiyan foundation of Harbin Medical University Cancer Hospital under Grant No.JJMS2021-28partly by the graduate academic innovation project of Harbin Normal University under Grant Nos.HSDSSCX2022-17,HSDSSCX2022-18 and HSDSSCX2022-19.
文摘Wireless sensor networks (WSNs) operate in complex and harshenvironments;thus, node faults are inevitable. Therefore, fault diagnosis ofthe WSNs node is essential. Affected by the harsh working environment ofWSNs and wireless data transmission, the data collected by WSNs containnoisy data, leading to unreliable data among the data features extracted duringfault diagnosis. To reduce the influence of unreliable data features on faultdiagnosis accuracy, this paper proposes a belief rule base (BRB) with a selfadaptivequality factor (BRB-SAQF) fault diagnosis model. First, the datafeatures required for WSN node fault diagnosis are extracted. Second, thequality factors of input attributes are introduced and calculated. Third, themodel inference process with an attribute quality factor is designed. Fourth,the projection covariance matrix adaptation evolution strategy (P-CMA-ES)algorithm is used to optimize the model’s initial parameters. Finally, the effectivenessof the proposed model is verified by comparing the commonly usedfault diagnosis methods for WSN nodes with the BRB method consideringstatic attribute reliability (BRB-Sr). The experimental results show that BRBSAQFcan reduce the influence of unreliable data features. The self-adaptivequality factor calculation method is more reasonable and accurate than thestatic attribute reliability method.
基金financially supported by the Sichuan Science and Technology Program(Grant No.2023NSFSC1980)。
文摘An observer-based adaptive backstepping boundary control is proposed for vibration control of flexible offshore riser systems with unknown nonlinear input dead zone and uncertain environmental disturbances.The control algorithm can update the control law online through real-time data to make the controller adapt to the environment and improve the control precision.Specifically,based on the adaptive backstepping framework,virtual control laws and Lyapunov functions are designed for each subsystem.Three direction interference observers are designed to track the timevarying boundary disturbance.On this basis,the inverse of the dead zone and linear state transformation are used to compensate for the original system and eliminate the adverse effects of the dead zone.In addition,the stability of the closed-loop system is proven by Lyapunov stability theory.All the system states are bounded,and the vibration offset of the riser converges to a small area of the initial position.Finally,four examples of flexible marine risers are simulated in MATLAB to verify the effectiveness of the proposed controller.
基金This work was supported by the National Key Research andDevelopment Programof China(2021YFD1800200 and2021YFC2301700).
文摘The stamping-out strategy has been used to control highly pathogenic avian influenza viruses in many countries,driven by the belief that vaccination would not be successful against such viruses and fears that avian influenza virus in vaccinated birds would evolve more rapidly and pose a greater risk to humans.In this review,we summarize the successes in controlling highly pathogenic avian influenza in China and make suggestions regarding the requirements for vaccine selection and effectiveness.In addition,we present evidence that vaccination of poultry not only eliminates human infection with avian influenza virus,but also significantly reduces and abolishes some harmful characteristics of avian influenza virus.
文摘The paper discusses the features of the Biomass Boiler drum water level. Conventional PID Control System can not reach a satisfaction result in nonlinearity and time different from Biomass Boiler Drum Water Control System. In this study, a kind of fuzzy self-adaptive PID controller is described and this controller is used in biomass boiler’s drum water level control system. Using the simulink tool of MATLAB simulation software to simulate the fuzzy adaptive PID and conventional PID control system, the result of the comparison shows that the fuzzy self-adaptive PID has the strong anti-jamming, flexibility and adaptability as well as the higher control precision in Biomass Boiler Drum Water.
文摘The welding wire feed mechanism is an important component of welding equipment, both reliability and stabilization are the premise that the welding quality can be ensured. The PID is currently adapted to control the welding wire feed mechanism, although the fuzzy PID has advantage of fast response and adaptation, the precision of fuzzy PID is lower. Accordingly, the fuzzy self-adaptive PID controller was proposed through changing fuzzy input variables and output variables based on variable universe, simple furwtion is adopted as scaling factor, the fuzzy PID controller parameters are adjusted to improve the precision and adjustment range. Simulation results show that control effects of fuzzy self-adaptive PID adopted by the welding wire feed mechanism have good adaptive ability and robustness based on variable universe, the welding experiments indicate that the welding quality met the requirements actually.
文摘The Internet of Things(IoT)access controlmechanism may encounter security issues such as single point of failure and data tampering.To address these issues,a blockchain-based IoT reputation value attribute access control scheme is proposed.Firstly,writing the reputation value as an attribute into the access control policy,and then deploying the access control policy in the smart contract of the blockchain system can enable the system to provide more fine-grained access control;Secondly,storing a large amount of resources fromthe Internet of Things in Inter Planetary File System(IPFS)to improve system throughput;Finally,map resource access operations to qualification tokens to improve the performance of the access control system.Complete simulation experiments based on the Hyperledger Fabric platform.Fromthe simulation experimental results,it can be seen that the access control system can achieve more fine-grained and dynamic access control while maintaining high throughput and low time delay,providing sufficient reliability and security for access control of IoT devices.
基金financially supported by the National Natural Science Foundation of China(Grant Nos.U2106223,51979193,52301352)。
文摘The fatigue damage caused by flow-induced vibration(FIV)is one of the major concerns for multiple cylindrical structures in many engineering applications.The FIV suppression is of great importance for the security of many cylindrical structures.Many active and passive control methods have been employed for the vibration suppression of an isolated cylinder undergoing vortex-induced vibrations(VIV).The FIV suppression methods are mainly extended to the multiple cylinders from the vibration control of the isolated cylinder.Due to the mutual interference between the multiple cylinders,the FIV mechanism is more complex than the VIV mechanism,which makes a great challenge for the FIV suppression.Some efforts have been devoted to vibration suppression of multiple cylinder systems undergoing FIV over the past two decades.The control methods,such as helical strakes,splitter plates,control rods and flexible sheets,are not always effective,depending on many influence factors,such as the spacing ratio,the arrangement geometrical shape,the flow velocity and the parameters of the vibration control devices.The FIV response,hydrodynamic features and wake patterns of the multiple cylinders equipped with vibration control devices are reviewed and summarized.The FIV suppression efficiency of the vibration control methods are analyzed and compared considering different influence factors.Further research on the FIV suppression of multiple cylinders is suggested to provide insight for the development of FIV control methods and promote engineering applications of FIV control methods.
基金supported by Qingdao Hi-image Technologies Co., Ltdin part by the NSFC of China under Grant 62174149, 61974118, 62004156the National Key R&D Program of China under Grant 2022YFC2404902
文摘This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control logic based on an on-chip delay-locked loop(DLL).The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter(CDAC)than the synchronous and asynchronous SAR ADC.Therefore,the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent.In addition,the fore-ground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter(FIR-BPF)based least-mean-square(LMS)algorithm in an off-chip FPGA(field programmable gate array).Fabricated in 40-nm CMOS process,the proto-type ADC achieves 94.02-dB spurious-free dynamic range(SFDR),and 75.98-dB signal-to-noise-and-distortion ratio(SNDR)for a 2.88-MHz input under 18-MSPS sampling rate.
基金supported by the National Natural Science Foundation of China,Nos.82130037(to CH),81971122(to CH),82171323(to WL)the Natural Science Foundation of Jiangsu Province of China,No.BK20201113(to WL)。
文摘The dramatic increase in intracranial pressure after subarachnoid hemorrhage leads to a decrease in cerebral perfusion pressure and a reduction in cerebral blood flow.Mitochondria are directly affected by direct factors such as ischemia,hypoxia,excitotoxicity,and toxicity of free hemoglobin and its degradation products,which trigger mitochondrial dysfunction.Dysfunctional mitochondria release large amounts of reactive oxygen species,inflammatory mediators,and apoptotic proteins that activate apoptotic pathways,further damaging cells.In response to this array of damage,cells have adopted multiple mitochondrial quality control mechanisms through evolution,including mitochondrial protein quality control,mitochondrial dynamics,mitophagy,mitochondrial biogenesis,and intercellular mitochondrial transfer,to maintain mitochondrial homeostasis under pathological conditions.Specific interventions targeting mitochondrial quality control mechanisms have emerged as promising therapeutic strategies for subarachnoid hemorrhage.This review provides an overview of recent research advances in mitochondrial pathophysiological processes after subarachnoid hemorrhage,particularly mitochondrial quality control mechanisms.It also presents potential therapeutic strategies to target mitochondrial quality control in subarachnoid hemorrhage.