This paper presents a multi-mode control scheme for a soft-switched flyback converter to achieve high efficiency and excellent load regulation over the entire load range. At heavy load, critical conduction mode with v...This paper presents a multi-mode control scheme for a soft-switched flyback converter to achieve high efficiency and excellent load regulation over the entire load range. At heavy load, critical conduction mode with valley switching (CCMVS) is employed to realize soft switching so as to reduce turn-on loss of power switch as well as conducted electromagnetic interference (EMI). At light load, the converter operates in discontinuous conduction mode (DCM) with valley switching and adaptive off-time control (AOT) to limit the switching frequency range and maintain load regulation. At extremely light load or in standby mode, burst mode operation is adopted to provide low power consumption through reducing both switching frequency and static power dissipation of the controller. The multi-mode control is implemented by an oscillator whose pulse duration is adjusted by output feedback. An accurate valley switching control circuit guarantees the minimum turn-on voltage drop of power switch. The pro-totype of the controller IC was fabricated in a 1.5-μm BiCMOS process and applied to a 310 V/20 V, 90 W flyback DC/DC converter circuitry. Experimental results showed that all expected functions were realized successfully. The flyback converter achieved a high efficiency of over 80% from full load down to 2.5 W, with the maximum reaching 88.8%, while the total power consumption in standby mode was about 300 mW.展开更多
The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick resp...The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick response time when the frequency bandwidth of each mode vibration is very different.The methodologies and various types of multi-mode classic and hybrid input shaping control schemes with positive impulses were introduced in this paper.Six types of two-mode hybrid input shapers with positive impulses of a 3 degree of freedom robot were established.The ability and robustness of these two-mode hybrid input shapers to suppress residual vibration were analyzed by vibration response curve and sensitivity curve via numerical simulation.The response time of the zero vibration-zero vibration and derivative(ZV-ZVD)input shaper is the fastest,but the robustness is the least.The robustness of the zero vibration and derivative-extra insensitive(ZVD-EI)input shaper is the best,while the response time is the longest.According to the frequency bandwidth at each mode and required system response time,the most appropriate multi-mode hybrid input shaper(MMHIS)can be selected in order to improve response time as much as possible under the condition of suppressing more residual vibration.展开更多
Vehicle collision avoidance(CA)has been widely studied to improve road traffic safety.However,most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-ma...Vehicle collision avoidance(CA)has been widely studied to improve road traffic safety.However,most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-machine interaction conflict.This paper introduces a novel multi-mode evasion assistance control(MEAC)method for intelligent distributed-drive electric vehicles.A reference safety area is established considering the vehicle safety and stability requirements,which serves as a guiding principle for evading obstacles.The proposed method includes two control modes:Shared-EAC(S-EAC)and Emergency-EAC(E-EAC).In S-EAC,an integrated human-machine authority allocation mechanism is designed to mitigate conflicts between human drivers and the control system during collision avoidance.The E-EAC mode is tailored for situations where the driver has no collision avoidance behavior and utilizes model predictive control to generate additional yaw moments for collision avoidance.Simulation and experimental results indicate that the proposed method reduces human-machine conflict and assists the driver in safe collision avoidance in the S-EAC mode under various driver conditions.In addition,it enhances the vehicle responsiveness and reduces the extent of emergency steering in the E-EAC mode while improving the safety and stability during the collision avoidance process.展开更多
With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intellig...With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.展开更多
In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are ...In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.展开更多
Firstly, a multi-field coupling finite element formulation of composited beam laminated with the photostrictive actuators is developed in this paper. Moreover, an optimal fuzzy active control algorithm is also propose...Firstly, a multi-field coupling finite element formulation of composited beam laminated with the photostrictive actuators is developed in this paper. Moreover, an optimal fuzzy active control algorithm is also proposed on the basis of the combination of optimal control and fuzzy one.This method opens a new avenue to resolve the contradiction between the linear system control method and nonlinear actuating characteristics of photostrictive actuators. The desired control for suppressing multi-modal vibration of photoelectric laminated beam is firstly obtained through optimal control and then the fuzzy control is used to approach the desired mechanical strain induced by photostrictive actuators. Thus, the multi-mode vibration control of beam is realized.In the design process of optimal fuzzy controller, the design of fuzzy control is independent of optimal control. The simulation results demonstrate that the proposed control method can effectively realize multi-modal vibration control of photoelectric laminated beams, and the control effect of optimal fuzzy control is better than that of optimal state feedback control.展开更多
Ultra-supercritical(USC) coal-fired unit is more and more popular in these years for its advantages.But the control of USC unit is a difficult issue for its characteristic of nonlinearity, large dead time and coupling...Ultra-supercritical(USC) coal-fired unit is more and more popular in these years for its advantages.But the control of USC unit is a difficult issue for its characteristic of nonlinearity, large dead time and coupling among inputs and outputs. In this paper, model predictive control(MPC) method based on multi-model and double layered optimization is introduced for coordinated control of USC unit running in sliding pressure mode and fixed pressure mode. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. output power, main steam temperature and main steam pressure). The step responses for the dynamic matrix control(DMC) are constructed using the three inputs by the three outputs under both pressure control mode. Piecewise models are built at selected operation points. In simulation, the output power follows load demand quickly and main steam temperature can be controlled around the setpoint closely in load tracking control. The simulation results show the effectiveness of the proposed methods.展开更多
Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional(2D) general predictive iterativ...Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional(2D) general predictive iterative learning control(2D-MGPILC) strategy based on the multi-model with time-varying weights was introduced for optimizing the tracking performance of desired temperature profile. This strategy was modeled based on an iterative learning control(ILC) algorithm for a 2D system and designed in the generalized predictive control(GPC) framework. Firstly, a multi-model structure with time-varying weights was developed to describe the complex operation of a general semi-batch reactor. Secondly, the 2 D-MGPILC algorithm was proposed to optimize simultaneously the dynamic performance along the time and batch axes. Finally, simulation for the controller design of a semi-batch reactor with multiple reactions was involved to demonstrate that the satisfactory performance could be achieved despite of the repetitive or non-repetitive disturbances.展开更多
The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy...The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy of hybrid vehicles becomes an issue.A unique multi-mode coupling(MMC)AWD hybrid system is presented to realize the distributed and centralized driving of the front and rear axles to achieve vectored distribution and full utilization of the system power between the axles of vehicles.Based on the parameters of the benchmarking model of a hybrid vehicle,the best model-predictive control-based energy management strategy is proposed.First,the drive system model was built after the analysis of the MMC-AWD’s drive modes.Next,three fundamental strategies were established to address power distribution adjustment and battery SOC maintenance when the SOC changed,which was followed by the design of a road driving force observer.Then,the energy consumption rate in the average time domain was processed before designing the minimum fuel consumption controller based on the equivalent fuel consumption coefficient.Finally,the advantage of the MMC-AWD was confirmed by comparison with the dynamic performance and economy of the BYD Song PLUS DMI-AWD.The findings indicate that,in comparison to the comparative hybrid system at road adhesion coefficients of 0.8 and 0.6,the MMC-AWD’s capacity to accelerate increases by 5.26%and 7.92%,respectively.When the road adhesion coefficient is 0.8,0.6,and 0.4,the maximum climbing ability increases by 14.22%,12.88%,and 4.55%,respectively.As a result,the dynamic performance is greatly enhanced,and the fuel savings rate per 100 km of mileage reaches 12.06%,which is also very economical.The proposed control strategies for the new hybrid AWD vehicle can optimize the power and economy simultaneously.展开更多
The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi...The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.展开更多
Because model switching system is a typical form of Takagi-Sugeno（T-S） model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical （ML...Because model switching system is a typical form of Takagi-Sugeno（T-S） model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical （MLD） system and use it in model predictive control （MPC） in this paper. Considering that each local model is only valid in each local region,we add local constraints to local models. The stability of proposed multi-model predictive control （MMPC） algorithm is analyzed, and the performance of MMPC is also demonstrated on an inulti-multi-output（MIMO） simulated pH neutralization process.展开更多
In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression ...In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results.展开更多
Low-carbon smart parks achieve selfbalanced carbon emission and absorption through the cooperative scheduling of direct current(DC)-based distributed photovoltaic,energy storage units,and loads.Direct current power li...Low-carbon smart parks achieve selfbalanced carbon emission and absorption through the cooperative scheduling of direct current(DC)-based distributed photovoltaic,energy storage units,and loads.Direct current power line communication(DC-PLC)enables real-time data transmission on DC power lines.With traffic adaptation,DC-PLC can be integrated with other complementary media such as 5G to reduce transmission delay and improve reliability.However,traffic adaptation for DC-PLC and 5G integration still faces the challenges such as coupling between traffic admission control and traffic partition,dimensionality curse,and the ignorance of extreme event occurrence.To address these challenges,we propose a deep reinforcement learning(DRL)-based delay sensitive and reliable traffic adaptation algorithm(DSRTA)to minimize the total queuing delay under the constraints of traffic admission control,queuing delay,and extreme events occurrence probability.DSRTA jointly optimizes traffic admission control and traffic partition,and enables learning-based intelligent traffic adaptation.The long-term constraints are incorporated into both state and bound of drift-pluspenalty to achieve delay awareness and enforce reliability guarantee.Simulation results show that DSRTA has lower queuing delay and more reliable quality of service(QoS)guarantee than other state-of-the-art algorithms.展开更多
Aiming at the needs of different lighting applications, combined with the characteristics of LED dimming and color control, and using MSP430 digital control technology, a novel LED intelligent dimming and color contro...Aiming at the needs of different lighting applications, combined with the characteristics of LED dimming and color control, and using MSP430 digital control technology, a novel LED intelligent dimming and color control system was designed. The system integrated Bluetooth remote, human infrared sensor, voice/gesture control and other control modes, which could achieve LED multi-mode dimming and color intelligent control. System hardware and software were designed to develop a prototype to experimental verification. The designed method proposes new ideas and information for LED control.展开更多
Carbon dots(CDs)-based composites have shown impressive performance in fields of information encryption and sensing,however,a great challenge is to simultaneously implement multi-mode luminescence and room-temperature...Carbon dots(CDs)-based composites have shown impressive performance in fields of information encryption and sensing,however,a great challenge is to simultaneously implement multi-mode luminescence and room-temperature phosphorescence(RTP)detection in single system due to the formidable synthesis.Herein,a multifunctional composite of Eu&CDs@p RHO has been designed by co-assembly strategy and prepared via a facile calcination and impregnation treatment.Eu&CDs@p RHO exhibits intense fluorescence(FL)and RTP coming from two individual luminous centers,Eu3+in the free pores and CDs in the interrupted structure of RHO zeolite.Unique four-mode color outputs including pink(Eu^(3+),ex.254 nm),light violet(CDs,ex.365 nm),blue(CDs,254 nm off),and green(CDs,365 nm off)could be realized,on the basis of it,a preliminary application of advanced information encoding has been demonstrated.Given the free pores of matrix and stable RTP in water of confined CDs,a visual RTP detection of Fe^(3+)ions is achieved with the detection limit as low as 9.8μmol/L.This work has opened up a new perspective for the strategic amalgamation of luminous vips with porous zeolite to construct the advanced functional materials.展开更多
We investigate the angular-dependent multi-mode resonance frequencies in CoZr magnetic thin films with a rotatable stripe domain structure.A variable range of multi-mode resonance frequencies from 1.86 GHz to 4.80 GHz...We investigate the angular-dependent multi-mode resonance frequencies in CoZr magnetic thin films with a rotatable stripe domain structure.A variable range of multi-mode resonance frequencies from 1.86 GHz to 4.80 GHz is achieved by pre-magnetizing the CoZr films along different azimuth directions,which can be ascribed to the competition between the uniaxial anisotropy caused by the oblique deposition and the rotatable anisotropy induced by the rotatable stripe domain.Furthermore,the regulating range of resonance frequency for the CoZr film can be adjusted by changing the oblique deposition angle.Our results might be beneficial for the applications of magnetic thin films in microwave devices.展开更多
Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials prov...Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials provide a promising prospect for imaging-guided precision therapy.Considering that tumor-derived alkaline phosphatase(ALP)is over-expressed in metastatic PCa,it makes a great chance to develop a theranostics system with ALP responsive in the TME.Herein,an ALP-responsive aggregationinduced emission luminogens(AIEgens)nanoprobe AMNF self-assembly was designed for enhancing the diagnosis and treatment of metastatic PCa.The nanoprobe exhibited self-aggregation in the presence of ALP resulted in aggregation-induced fluorescence,and enhanced accumulation and prolonged retention period at the tumor site.In terms of detection,the fluorescence(FL)/computed tomography(CT)/magnetic resonance(MR)multi-mode imaging effect of nanoprobe was significantly improved post-aggregation,enabling precise diagnosis through the amalgamation of multiple imaging modes.Enhanced CT/MR imaging can achieve assist preoperative tumor diagnosis,and enhanced FL imaging technology can achieve“intraoperative visual navigation”,showing its potential application value in clinical tumor detection and surgical guidance.In terms of treatment,AMNF showed strong absorption in the near infrared region after aggregation,which improved the photothermal treatment effect.Overall,our work developed an effective aggregation-enhanced theranostic strategy for ALP-related cancers.展开更多
This paper introduces a multi-model approach to design a robust supplementary damping controller. The designed fixed-order supplementary damping controller adjusts the voltage reference set point of SVC. There are two...This paper introduces a multi-model approach to design a robust supplementary damping controller. The designed fixed-order supplementary damping controller adjusts the voltage reference set point of SVC. There are two main objectives of the controller design, damping low frequencies oscillations and enhancing power system stability. This method relies on shaping the closed-loop sensitivity functions in the Nyquist plot under the constraints of these functions. These constraints can be linearized by choosing a desired open-loop transfer function. The robust controller is designed to minimize the error between the open-loop of the original plant model and the desired transfer functions. These outcomes can be achieved by using convex optimization methods. Convexity of the problem formulation ensures global optimality. One of the advantages of the proposed approach is that the approach accounts for multi-model uncertainty. In contrast to the methods available in the literature, the proposed approach deals with full-order model (i.e., model reduction is not required) with lower controller order. The issue of time delay of feedback signals has been addressed in this paper for different values of time delay by applying a multi-model optimization technique. The proposed approach is compared to other existing techniques to design a robust controller which is based on H2 under pole placement. Both techniques are applied to the 68-bus system to evaluate and validate the robust controller performance under different load scenarios and different wind generations.展开更多
The control strategy is one of the most important renewable technology,and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch(VS-VP)technology.The main objective of...The control strategy is one of the most important renewable technology,and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch(VS-VP)technology.The main objective of adopting a VS-VP technology is to improve the fast response speed and capture maximum energy.But the power generated by wind turbine changes rapidly because of the continuous fluctuation of wind speed and direction.At the same time,wind energy conversion systems are of high order,time delays and strong nonlinear characteristics because of many uncertain factors.Based on analyzing the all dynamic processes of wind turbine,a kind of layered multi-mode optimal control strategy is presented which is that three control strategies:bang-bang,fuzzy and adaptive proportional integral derivative(PID)are adopted according to different stages and expected performance of wind turbine to capture optimum wind power,compensate the nonlinearity and improve the wind turbine performance at low,rated and high wind speed.展开更多
A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is fir...A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is first built and decoupled according to the force analysis.The control set with corresponding precise model set is then optimized according to different working conditions.The multi-model switching strategy is studied using machine learning algorithm.The simulation experiments indicate that a multi-model controller comprised of the proportional-integral-derivative(PID),fuzzy PID(FPID)and model predictive controllers with support vector machine(SVM)switching strategy can realize the continuous submarine depth control under full working condition,showing a good control performance compared with a single PID controller.展开更多
基金the National Natural Science Foundation of China (No. 90707002)the Natural Science Foundation of Zheji-ang Province, China (No. Z104441)
文摘This paper presents a multi-mode control scheme for a soft-switched flyback converter to achieve high efficiency and excellent load regulation over the entire load range. At heavy load, critical conduction mode with valley switching (CCMVS) is employed to realize soft switching so as to reduce turn-on loss of power switch as well as conducted electromagnetic interference (EMI). At light load, the converter operates in discontinuous conduction mode (DCM) with valley switching and adaptive off-time control (AOT) to limit the switching frequency range and maintain load regulation. At extremely light load or in standby mode, burst mode operation is adopted to provide low power consumption through reducing both switching frequency and static power dissipation of the controller. The multi-mode control is implemented by an oscillator whose pulse duration is adjusted by output feedback. An accurate valley switching control circuit guarantees the minimum turn-on voltage drop of power switch. The pro-totype of the controller IC was fabricated in a 1.5-μm BiCMOS process and applied to a 310 V/20 V, 90 W flyback DC/DC converter circuitry. Experimental results showed that all expected functions were realized successfully. The flyback converter achieved a high efficiency of over 80% from full load down to 2.5 W, with the maximum reaching 88.8%, while the total power consumption in standby mode was about 300 mW.
基金Project(LQ12E05008)supported by Natural Science Foundation of Zhejiang Province,ChinaProject(201708330107)supported by China Scholarship Council
文摘The classic multi-mode input shapers(MMISs)are valid to decrease multi-mode residual vibration of manipulators or robots simultaneously.But these input shapers cannot suppress more residual vibration with a quick response time when the frequency bandwidth of each mode vibration is very different.The methodologies and various types of multi-mode classic and hybrid input shaping control schemes with positive impulses were introduced in this paper.Six types of two-mode hybrid input shapers with positive impulses of a 3 degree of freedom robot were established.The ability and robustness of these two-mode hybrid input shapers to suppress residual vibration were analyzed by vibration response curve and sensitivity curve via numerical simulation.The response time of the zero vibration-zero vibration and derivative(ZV-ZVD)input shaper is the fastest,but the robustness is the least.The robustness of the zero vibration and derivative-extra insensitive(ZVD-EI)input shaper is the best,while the response time is the longest.According to the frequency bandwidth at each mode and required system response time,the most appropriate multi-mode hybrid input shaper(MMHIS)can be selected in order to improve response time as much as possible under the condition of suppressing more residual vibration.
基金Supported by National Key Research and Development Program of China(Grant Nos.2022YFE0117100 and 2021YFB250120101)National Natural Science Foundation of China(Grant No.52325212)+1 种基金Shanghai Municipal Automotive Industry Science,Technology Development Foundation(Grant No.2203)the SAIC Motor Corporation Limited(Grant No.2023023).
文摘Vehicle collision avoidance(CA)has been widely studied to improve road traffic safety.However,most evasion assistance control methods face challenges in effectively coordinating collision avoidance safety and human-machine interaction conflict.This paper introduces a novel multi-mode evasion assistance control(MEAC)method for intelligent distributed-drive electric vehicles.A reference safety area is established considering the vehicle safety and stability requirements,which serves as a guiding principle for evading obstacles.The proposed method includes two control modes:Shared-EAC(S-EAC)and Emergency-EAC(E-EAC).In S-EAC,an integrated human-machine authority allocation mechanism is designed to mitigate conflicts between human drivers and the control system during collision avoidance.The E-EAC mode is tailored for situations where the driver has no collision avoidance behavior and utilizes model predictive control to generate additional yaw moments for collision avoidance.Simulation and experimental results indicate that the proposed method reduces human-machine conflict and assists the driver in safe collision avoidance in the S-EAC mode under various driver conditions.In addition,it enhances the vehicle responsiveness and reduces the extent of emergency steering in the E-EAC mode while improving the safety and stability during the collision avoidance process.
基金supported by the National Natural Science Foundation of China(Nos.62371323,62401380,U2433217,U2333209,and U20A20161)Natural Science Foundation of Sichuan Province,China(Nos.2025ZNSFSC1476)+2 种基金Sichuan Science and Technology Program,China(Nos.2024YFG0010 and 2024ZDZX0046)the Institutional Research Fund from Sichuan University(Nos.2024SCUQJTX030)the Open Fund of Key Laboratory of Flight Techniques and Flight Safety,CAAC(Nos.GY2024-01A).
文摘With the advent of the next-generation Air Traffic Control(ATC)system,there is growing interest in using Artificial Intelligence(AI)techniques to enhance Situation Awareness(SA)for ATC Controllers(ATCOs),i.e.,Intelligent SA(ISA).However,the existing AI-based SA approaches often rely on unimodal data and lack a comprehensive description and benchmark of the ISA tasks utilizing multi-modal data for real-time ATC environments.To address this gap,by analyzing the situation awareness procedure of the ATCOs,the ISA task is refined to the processing of the two primary elements,i.e.,spoken instructions and flight trajectories.Subsequently,the ISA is further formulated into Controlling Intent Understanding(CIU)and Flight Trajectory Prediction(FTP)tasks.For the CIU task,an innovative automatic speech recognition and understanding framework is designed to extract the controlling intent from unstructured and continuous ATC communications.For the FTP task,the single-and multi-horizon FTP approaches are investigated to support the high-precision prediction of the situation evolution.A total of 32 unimodal/multi-modal advanced methods with extensive evaluation metrics are introduced to conduct the benchmarks on the real-world multi-modal ATC situation dataset.Experimental results demonstrate the effectiveness of AI-based techniques in enhancing ISA for the ATC environment.
基金National Key Research and Development Program of China(Grant No.2020YFB2009702)National Natural Science Foundation of China(Grant Nos.52075055,U21A20124 and 52111530069)Chongqing Natural Science Foundation of China(Grant No.cstc2020jcyj-msxmX0780)。
文摘In mobile machinery,hydro-mechanical pumps are increasingly replaced by electronically controlled pumps to improve the automation level,but diversified control functions(e.g.,power limitation and pressure cut-off)are integrated into the electronic controller only from the pump level,leading to the potential instability of the overall system.To solve this problem,a multi-mode electrohydraulic load sensing(MELS)control scheme is proposed especially considering the switching stability from the system level,which includes four working modes of flow control,load sensing,power limitation,and pressure control.Depending on the actual working requirements,the switching rules for the different modes and the switching direction(i.e.,the modes can be switched bilaterally or unilaterally)are defined.The priority of different modes is also defined,from high to low:pressure control,power limitation,load sensing,and flow control.When multiple switching rules are satisfied at the same time,the system switches to the control mode with the highest priority.In addition,the switching stability between flow control and pressure control modes is analyzed,and the controller parameters that guarantee the switching stability are obtained.A comparative study is carried out based on a test rig with a 2-ton hydraulic excavator.The results show that the MELS controller can achieve the control functions of proper flow supplement,power limitation,and pressure cut-off,which has good stability performance when switching between different control modes.This research proposes the MELS control method that realizes the stability of multi-mode switching of the hydraulic system of mobile machinery under different working conditions.
基金supported by the National Natural Science Foundation of China, China (No. 11572151)
文摘Firstly, a multi-field coupling finite element formulation of composited beam laminated with the photostrictive actuators is developed in this paper. Moreover, an optimal fuzzy active control algorithm is also proposed on the basis of the combination of optimal control and fuzzy one.This method opens a new avenue to resolve the contradiction between the linear system control method and nonlinear actuating characteristics of photostrictive actuators. The desired control for suppressing multi-modal vibration of photoelectric laminated beam is firstly obtained through optimal control and then the fuzzy control is used to approach the desired mechanical strain induced by photostrictive actuators. Thus, the multi-mode vibration control of beam is realized.In the design process of optimal fuzzy controller, the design of fuzzy control is independent of optimal control. The simulation results demonstrate that the proposed control method can effectively realize multi-modal vibration control of photoelectric laminated beams, and the control effect of optimal fuzzy control is better than that of optimal state feedback control.
基金the National Nature Science Foundation of China(No.60974119)the Subject Construction of Shanghai University of Engineering Science(No.2018xk-B-09)the Young Teacher Training Scheme of Shanghai Universities(No.ZZGCD15007)
文摘Ultra-supercritical(USC) coal-fired unit is more and more popular in these years for its advantages.But the control of USC unit is a difficult issue for its characteristic of nonlinearity, large dead time and coupling among inputs and outputs. In this paper, model predictive control(MPC) method based on multi-model and double layered optimization is introduced for coordinated control of USC unit running in sliding pressure mode and fixed pressure mode. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. output power, main steam temperature and main steam pressure). The step responses for the dynamic matrix control(DMC) are constructed using the three inputs by the three outputs under both pressure control mode. Piecewise models are built at selected operation points. In simulation, the output power follows load demand quickly and main steam temperature can be controlled around the setpoint closely in load tracking control. The simulation results show the effectiveness of the proposed methods.
基金Projects(61673205,21727818,61503180)supported by the National Natural Science Foundation of ChinaProject(2017YFB0307304)supported by National Key R&D Program of ChinaProject(BK20141461)supported by the Natural Science Foundation of Jiangsu Province,China
文摘Batch to batch temperature control of a semi-batch chemical reactor with heating/cooling system was discussed in this study. Without extensive modeling investigations, a two-dimensional(2D) general predictive iterative learning control(2D-MGPILC) strategy based on the multi-model with time-varying weights was introduced for optimizing the tracking performance of desired temperature profile. This strategy was modeled based on an iterative learning control(ILC) algorithm for a 2D system and designed in the generalized predictive control(GPC) framework. Firstly, a multi-model structure with time-varying weights was developed to describe the complex operation of a general semi-batch reactor. Secondly, the 2 D-MGPILC algorithm was proposed to optimize simultaneously the dynamic performance along the time and batch axes. Finally, simulation for the controller design of a semi-batch reactor with multiple reactions was involved to demonstrate that the satisfactory performance could be achieved despite of the repetitive or non-repetitive disturbances.
基金Supported by Hebei Provincial Natural Science Foundation of China(Grant Nos.E2020203174,E2020203078)S&T Program of Hebei Province of China(Grant No.226Z2202G)Science Research Project of Hebei Provincial Education Department of China(Grant No.ZD2022029).
文摘The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy of hybrid vehicles becomes an issue.A unique multi-mode coupling(MMC)AWD hybrid system is presented to realize the distributed and centralized driving of the front and rear axles to achieve vectored distribution and full utilization of the system power between the axles of vehicles.Based on the parameters of the benchmarking model of a hybrid vehicle,the best model-predictive control-based energy management strategy is proposed.First,the drive system model was built after the analysis of the MMC-AWD’s drive modes.Next,three fundamental strategies were established to address power distribution adjustment and battery SOC maintenance when the SOC changed,which was followed by the design of a road driving force observer.Then,the energy consumption rate in the average time domain was processed before designing the minimum fuel consumption controller based on the equivalent fuel consumption coefficient.Finally,the advantage of the MMC-AWD was confirmed by comparison with the dynamic performance and economy of the BYD Song PLUS DMI-AWD.The findings indicate that,in comparison to the comparative hybrid system at road adhesion coefficients of 0.8 and 0.6,the MMC-AWD’s capacity to accelerate increases by 5.26%and 7.92%,respectively.When the road adhesion coefficient is 0.8,0.6,and 0.4,the maximum climbing ability increases by 14.22%,12.88%,and 4.55%,respectively.As a result,the dynamic performance is greatly enhanced,and the fuel savings rate per 100 km of mileage reaches 12.06%,which is also very economical.The proposed control strategies for the new hybrid AWD vehicle can optimize the power and economy simultaneously.
基金Supported by the National Natural Science Foundation of China(60974119)
文摘The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.
文摘Because model switching system is a typical form of Takagi-Sugeno（T-S） model which is an universal approximator of continuous nonlinear systems, we describe the model switching system as mixed logical dynamical （MLD） system and use it in model predictive control （MPC） in this paper. Considering that each local model is only valid in each local region,we add local constraints to local models. The stability of proposed multi-model predictive control （MMPC） algorithm is analyzed, and the performance of MMPC is also demonstrated on an inulti-multi-output（MIMO） simulated pH neutralization process.
基金the 973 Program of China (No.2002CB312200)the National Science Foundation of China (No.60574019)
文摘In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results.
基金supported by the Science and Technology Project of State Grid Corporation of China under grant 52094021N010(5400-202199534A-0-5-ZN)。
文摘Low-carbon smart parks achieve selfbalanced carbon emission and absorption through the cooperative scheduling of direct current(DC)-based distributed photovoltaic,energy storage units,and loads.Direct current power line communication(DC-PLC)enables real-time data transmission on DC power lines.With traffic adaptation,DC-PLC can be integrated with other complementary media such as 5G to reduce transmission delay and improve reliability.However,traffic adaptation for DC-PLC and 5G integration still faces the challenges such as coupling between traffic admission control and traffic partition,dimensionality curse,and the ignorance of extreme event occurrence.To address these challenges,we propose a deep reinforcement learning(DRL)-based delay sensitive and reliable traffic adaptation algorithm(DSRTA)to minimize the total queuing delay under the constraints of traffic admission control,queuing delay,and extreme events occurrence probability.DSRTA jointly optimizes traffic admission control and traffic partition,and enables learning-based intelligent traffic adaptation.The long-term constraints are incorporated into both state and bound of drift-pluspenalty to achieve delay awareness and enforce reliability guarantee.Simulation results show that DSRTA has lower queuing delay and more reliable quality of service(QoS)guarantee than other state-of-the-art algorithms.
文摘Aiming at the needs of different lighting applications, combined with the characteristics of LED dimming and color control, and using MSP430 digital control technology, a novel LED intelligent dimming and color control system was designed. The system integrated Bluetooth remote, human infrared sensor, voice/gesture control and other control modes, which could achieve LED multi-mode dimming and color intelligent control. System hardware and software were designed to develop a prototype to experimental verification. The designed method proposes new ideas and information for LED control.
基金supported by the National Natural Science Foundation of China(No.22288101)the 111 Project(No.B17020)。
文摘Carbon dots(CDs)-based composites have shown impressive performance in fields of information encryption and sensing,however,a great challenge is to simultaneously implement multi-mode luminescence and room-temperature phosphorescence(RTP)detection in single system due to the formidable synthesis.Herein,a multifunctional composite of Eu&CDs@p RHO has been designed by co-assembly strategy and prepared via a facile calcination and impregnation treatment.Eu&CDs@p RHO exhibits intense fluorescence(FL)and RTP coming from two individual luminous centers,Eu3+in the free pores and CDs in the interrupted structure of RHO zeolite.Unique four-mode color outputs including pink(Eu^(3+),ex.254 nm),light violet(CDs,ex.365 nm),blue(CDs,254 nm off),and green(CDs,365 nm off)could be realized,on the basis of it,a preliminary application of advanced information encoding has been demonstrated.Given the free pores of matrix and stable RTP in water of confined CDs,a visual RTP detection of Fe^(3+)ions is achieved with the detection limit as low as 9.8μmol/L.This work has opened up a new perspective for the strategic amalgamation of luminous vips with porous zeolite to construct the advanced functional materials.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51871117 and 51671099)the Program for Changjiang Scholars and Innovative Research Team in University,China(Grant No.IRT-16R35)the Gansu Provincial Science Foundation for Distinguished Young Scholars,China(Grant No.20JR10RA649).
文摘We investigate the angular-dependent multi-mode resonance frequencies in CoZr magnetic thin films with a rotatable stripe domain structure.A variable range of multi-mode resonance frequencies from 1.86 GHz to 4.80 GHz is achieved by pre-magnetizing the CoZr films along different azimuth directions,which can be ascribed to the competition between the uniaxial anisotropy caused by the oblique deposition and the rotatable anisotropy induced by the rotatable stripe domain.Furthermore,the regulating range of resonance frequency for the CoZr film can be adjusted by changing the oblique deposition angle.Our results might be beneficial for the applications of magnetic thin films in microwave devices.
基金supported by Natural Science Foundation of Jilin Province(No.SKL202302002)Key Research and Development project of Jilin Provincial Science and Technology Department(No.20210204142YY)+2 种基金The Science and Technology Development Program of Jilin Province(No.2020122256JC)Beijing Kechuang Medical Development Foundation Fund of China(No.KC2023-JX-0186BQ079)Talent Reserve Program(TRP),the First Hospital of Jilin University(No.JDYY-TRP-2024007)。
文摘Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials provide a promising prospect for imaging-guided precision therapy.Considering that tumor-derived alkaline phosphatase(ALP)is over-expressed in metastatic PCa,it makes a great chance to develop a theranostics system with ALP responsive in the TME.Herein,an ALP-responsive aggregationinduced emission luminogens(AIEgens)nanoprobe AMNF self-assembly was designed for enhancing the diagnosis and treatment of metastatic PCa.The nanoprobe exhibited self-aggregation in the presence of ALP resulted in aggregation-induced fluorescence,and enhanced accumulation and prolonged retention period at the tumor site.In terms of detection,the fluorescence(FL)/computed tomography(CT)/magnetic resonance(MR)multi-mode imaging effect of nanoprobe was significantly improved post-aggregation,enabling precise diagnosis through the amalgamation of multiple imaging modes.Enhanced CT/MR imaging can achieve assist preoperative tumor diagnosis,and enhanced FL imaging technology can achieve“intraoperative visual navigation”,showing its potential application value in clinical tumor detection and surgical guidance.In terms of treatment,AMNF showed strong absorption in the near infrared region after aggregation,which improved the photothermal treatment effect.Overall,our work developed an effective aggregation-enhanced theranostic strategy for ALP-related cancers.
文摘This paper introduces a multi-model approach to design a robust supplementary damping controller. The designed fixed-order supplementary damping controller adjusts the voltage reference set point of SVC. There are two main objectives of the controller design, damping low frequencies oscillations and enhancing power system stability. This method relies on shaping the closed-loop sensitivity functions in the Nyquist plot under the constraints of these functions. These constraints can be linearized by choosing a desired open-loop transfer function. The robust controller is designed to minimize the error between the open-loop of the original plant model and the desired transfer functions. These outcomes can be achieved by using convex optimization methods. Convexity of the problem formulation ensures global optimality. One of the advantages of the proposed approach is that the approach accounts for multi-model uncertainty. In contrast to the methods available in the literature, the proposed approach deals with full-order model (i.e., model reduction is not required) with lower controller order. The issue of time delay of feedback signals has been addressed in this paper for different values of time delay by applying a multi-model optimization technique. The proposed approach is compared to other existing techniques to design a robust controller which is based on H2 under pole placement. Both techniques are applied to the 68-bus system to evaluate and validate the robust controller performance under different load scenarios and different wind generations.
基金Science & Technology Development Foundation of Shanghai,China(No.062158017)Postdoctoral Foundation of Shanghai,China(No.05R214133)Postdoctoral Foundation of China(No.2005038435)
文摘The control strategy is one of the most important renewable technology,and an increasing number of multi-MW wind turbines are being developed with a variable speed-variable pitch(VS-VP)technology.The main objective of adopting a VS-VP technology is to improve the fast response speed and capture maximum energy.But the power generated by wind turbine changes rapidly because of the continuous fluctuation of wind speed and direction.At the same time,wind energy conversion systems are of high order,time delays and strong nonlinear characteristics because of many uncertain factors.Based on analyzing the all dynamic processes of wind turbine,a kind of layered multi-mode optimal control strategy is presented which is that three control strategies:bang-bang,fuzzy and adaptive proportional integral derivative(PID)are adopted according to different stages and expected performance of wind turbine to capture optimum wind power,compensate the nonlinearity and improve the wind turbine performance at low,rated and high wind speed.
基金the National Natural Science Foundation of China(No.51579201)。
文摘A continuous submarine depth control strategy based on multi-model and machine learning switching method under full working condition is proposed in this paper.A submarine motion model with six-degree-offreedom is first built and decoupled according to the force analysis.The control set with corresponding precise model set is then optimized according to different working conditions.The multi-model switching strategy is studied using machine learning algorithm.The simulation experiments indicate that a multi-model controller comprised of the proportional-integral-derivative(PID),fuzzy PID(FPID)and model predictive controllers with support vector machine(SVM)switching strategy can realize the continuous submarine depth control under full working condition,showing a good control performance compared with a single PID controller.
