Under the partial shading conditions(PSC)of Photovoltaic(PV)modules in a PV hybrid system,the power output curve exhibits multiple peaks.This often causes traditional maximum power point tracking(MPPT)methods to fall ...Under the partial shading conditions(PSC)of Photovoltaic(PV)modules in a PV hybrid system,the power output curve exhibits multiple peaks.This often causes traditional maximum power point tracking(MPPT)methods to fall into local optima and fail to find the global optimum.To address this issue,a composite MPPT algorithm is proposed.It combines the improved kepler optimization algorithm(IKOA)with the optimized variable-step perturb and observe(OIP&O).The update probabilities,planetary velocity and position step coefficients of IKOA are nonlinearly and adaptively optimized.This adaptation meets the varying needs of the initial and later stages of the iterative process and accelerates convergence.During stochastic exploration,the refined position update formulas enhance diversity and global search capability.The improvements in the algorithmreduces the likelihood of falling into local optima.In the later stages,the OIP&O algorithm decreases oscillation and increases accuracy.compared with cuckoo search(CS)and gray wolf optimization(GWO),simulation tests of the PV hybrid inverter demonstrate that the proposed IKOA-OIP&O algorithm achieves faster convergence and greater stability under static,local and dynamic shading conditions.These results can confirm the feasibility and effectiveness of the proposed PV MPPT algorithm for PV hybrid systems.展开更多
The generation of electricity,considering environmental and eco-nomic factors is one of the most important challenges of recent years.In this article,a thermoelectric generator(TEG)is proposed to use the thermal energ...The generation of electricity,considering environmental and eco-nomic factors is one of the most important challenges of recent years.In this article,a thermoelectric generator(TEG)is proposed to use the thermal energy of an electric water heater(EWH)to generate electricity independently.To improve the energy conversion efficiency of the TEG,a fuzzy logic con-troller(FLC)-based perturb&observe(P&O)type maximum power point tracking(MPPT)control algorithm is used in this study.An EWH is one of the major electricity consuming household appliances which causes a higher electricity price for consumers.Also,a significant amount of thermal energy generated by EWH is wasted every day,especially during the winter season.In recent years,TEGs have been widely developed to convert surplus or unused thermal energy into usable electricity.In this context,the proposed model is designed to use the thermal energy stored in the EWH to generate electricity.In addition,the generated electricity can be easily stored in a battery storage system to supply electricity to various household appliances with low-power-consumption.The proposed MPPT control algorithm helps the system to quickly reach the optimal point corresponding to the maximum power output and maintains the system operating point at the maximum power output level.To validate the usefulness of the proposed scheme,a study model was developed in the MATLAB Simulink environment and its performance was investigated by simulation under steady state and transient conditions.The results of the study confirmed that the system is capable of generating adequate power from the available thermal energy of EWH.It was also found that the output power and efficiency of the system can be improved by maintaining a higher temperature difference at the input terminals of the TEG.Moreover,the real-time temperature data of Abha city in Saudi Arabia is considered to analyze the feasibility of the proposed system for practical implementation.展开更多
This paper presents an observer-based nonlinear control method that was developed and implemented to provide accurate tracking control of a limited angle torque motor following a 50Hz reference waveform. The method is...This paper presents an observer-based nonlinear control method that was developed and implemented to provide accurate tracking control of a limited angle torque motor following a 50Hz reference waveform. The method is based on a robust nonlinear observer, which is used to estimate system states and perturbations and then employ input-output feedbazk linearization to compensate for the system nonlinearities and uncertainties. The estimation of system states and perturbations allows input-output linearization of the nonlinear system without an accurate mathematical model of nominal plant. The simulation results show that the observer-based nonlinear control method is superior in comparison with the conventional model-based state feedback linearizing controller.展开更多
This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satell...This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.展开更多
Wind turbine employs pitch angle control to maintain captured power at its rated value when the wind speed is higher than rated value.This work adopts a perturbation observer based sliding-mode control(POSMC)strategy ...Wind turbine employs pitch angle control to maintain captured power at its rated value when the wind speed is higher than rated value.This work adopts a perturbation observer based sliding-mode control(POSMC)strategy to realize robust variable-pitch control of permanent magnet synchronous generator(PMSG).POSMC combines system nonlinearities,parametric uncertainties,unmodelled dynamics,and time-varying external disturbances into a perturbation,which aims to estimate the perturbation via a perturbation observer without an accurate system model.Subsequently,sliding mode control(SMC)is designed to completely compensate perturbation estimation in real-time for the sake of achieving a global consistent control performance and improving system robustness under complicated environments.Simulation results indicate that,compared with vector control(VC),feedback linearization control(FLC),and nonlinear adaptive control(NAC),POSMC has the best control performance in ramp wind and random wind and the highest robustness in terms of parameter uncertainty.Specially,the integral absolute error index of!m of POSMC is only 11.69%,12.10%and 15.14%of that of VC,FLC and NAC in random wind speed.展开更多
In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce...In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce the jitter.To enhance the immunity of the system,a disturbance observer is designed to observe and compensate for the disturbance to the sliding mode controller.In addition,considering that the controller parameters are difficult to adjust,and the traditional zebra optimization algorithm(ZOA)is prone to converge prematurely and fall into local optimum when solving the optimal solution,the improved zebra optimization algorithm(IZOA)is proposed,and the ability of the IZOA in practical applications is verified by using international standard test functions.To verify the performance of IZOA,firstly,the adjustment time of IZOA is reduced by 71.67%compared with ZOA through the step response,and secondly,the tracking error of IZOA is reduced by 51.52%compared with ZOA through the sinusoidal signal following.To verify the performance of the designed controller based on disturbance observer,the designed controller reduces the speed overshoot from 2.5%to 0.63%compared with the traditional NFTSMC in the speed mutation experiment,which is a performance improvement of 70.8%,and the designed controller outperforms the traditional NFTSMC in the load mutation experiment,which is a performance improvement of 60.0%in the case of sudden load addition,and a performance improvement of 90.0%in the case of load release,which verifies that the designed controller outperforms the traditional NFTSMC.展开更多
The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typic...The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typically input multiple time slices without deterministic dependencies.In this study,the CNOP for DLMs(CNOP-DL)is proposed as an extension of the CNOP in the time dimension.This method is useful for targeted observations as it indicates not only where but also when to deploy additional observations.The CNOP-DL is calculated for a forecast case of sea surface temperature in the South China Sea with a DLM.The CNOP-DL identifies a sensitive area northwest of Palawan Island at the last input time.Sensitivity experiments demonstrate that the sensitive area identified by the CNOP-DL is effective not only for the CNOP-DL itself,but also for random perturbations.Therefore,this approach holds potential for guiding practical field campaigns.Notably,forecast errors are more sensitive to time than to location in the sensitive area.It highlights the crucial role of identifying the time of the sensitive area in targeted observations,corroborating the usefulness of extending the CNOP in the time dimension.展开更多
Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at...Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at any moment within the VTW.However,different observation times demonstrate different cloud cover distributions,which exhibit different effects on the AEOS observation.Previous studies ignored pitch angles,discretized VTWs,or fixed cloud cover for every VTW,which led to the loss of intermediate observation states,thus these studies are not suitable for AEOS scheduling considering cloud cover distribution.In this study,a relationship formula between the cloud cover and observation time is proposed to calculate the cloud cover for every observation time,and a relationship formula between the observation time and pitch angle is designed to calculate the pitch angle for every observation time in the VTW.A refined model including the pitch angle,roll angle,and cloud cover distribution is established,which can make the scheme closer to the actual application of AEOSs.A hybrid genetic simulated annealing(HGSA)algorithm for AEOS scheduling is proposed,which integrates the advantages of genetic and simulated annealing algorithms and can effectively avoid falling into a local optimal solution.The experiments are conducted to compare the proposed algorithm with the traditional algorithms,the results verify that the proposed model and algorithm are efficient and effective for AEOS scheduling considering cloud cover distribution.展开更多
A comparative study is done in regards to the performance of the popular Perturb and Observe algorithm and the Genetic Assisted-Radial Basis Function-Neural Network (GA-RBF-NN) algorithm, both incorporating the Interl...A comparative study is done in regards to the performance of the popular Perturb and Observe algorithm and the Genetic Assisted-Radial Basis Function-Neural Network (GA-RBF-NN) algorithm, both incorporating the Interleaved Boost converter. The Perturb and Observe method (P&O) is inarguably the most commonly used algorithm as its advantages pertaining to its ease in implementation and simplicity enable to track the Maximum Power Point (MPP). However, it is absolutely unreliable when subjected to rapidly fluctuating irradiation and temperature levels. More importantly, the system has the tendency to swing back and forth about the Maximum Power Point without reaching stability. At this juncture, the implementation of the Genetic-Assisted Radial Basis Function (GA-RBF) algorithm helps the system achieve MPP at a shorter time when compared to the Perturb and Observe technique. The ever reliable and robust Levenberg-Marquardt algorithm is included along with the MPPT controller that minimizes the Mean Square Error (MSE) and aids in faster training of the neural network. This PV system drives a brushless DC motor (BLDC), employing rotor position sensors.展开更多
This paper aims at rescheduling of observing spacecraft imaging plans under uncertainties. Firstly, uncertainties in spacecraft observation scheduling are analyzed. Then, considering the uncertainties with fuzzy featu...This paper aims at rescheduling of observing spacecraft imaging plans under uncertainties. Firstly, uncertainties in spacecraft observation scheduling are analyzed. Then, considering the uncertainties with fuzzy features, this paper proposes a fuzzy neural network and a hybrid rescheduling policy to deal with them. It then establishes a mathematical model and manages to solve the rescheduling problem by proposing an ant colony algorithm, which introduces an adaptive control mechanism and takes advantage of the information in an existing schedule. Finally, the above method is applied to solve the rescheduling problem of a certain type of earth-observing satellite. The computation of the example shows that the approach is feasible and effective in dealing with uncertainties in spacecraft observation scheduling. The approach designed here can be useful in solving the problem that the original schedule is contaminated by disturbances.展开更多
A variant constrained genetic algorithm （VCGA） for effective tracking of conditional nonlinear optimal perturbations （CNOPs） is presented. Compared with traditional constraint handling methods, the treatment of th...A variant constrained genetic algorithm （VCGA） for effective tracking of conditional nonlinear optimal perturbations （CNOPs） is presented. Compared with traditional constraint handling methods, the treatment of the constraint condition in VCGA is relatively easy to implement. Moreover, it does not require adjustments to indefinite pararneters. Using a hybrid crossover operator and the newly developed multi-ply mutation operator, VCGA improves the performance of GAs. To demonstrate the capability of VCGA to catch CNOPS in non-smooth cases, a partial differential equation, which has ＂on off＂ switches in its forcing term, is employed as the nonlinear model. To search global CNOPs of the nonlinear model, numerical experiments using VCGA, the traditional gradient descent algorithm based on the adjoint method （ADJ）, and a GA using tournament selection operation and the niching technique （GA-DEB） were performed. The results with various initial reference states showed that, in smooth cases, all three optimization methods are able to catch global CNOPs. Nevertheless, in non-smooth situations, a large proportion of CNOPs captured by the ADJ are local. Compared with ADJ, the performance of GA-DEB shows considerable improvement, but it is far below VCGA. Further, the impacts of population sizes on both VCGA and GA-DEB were investigated. The results were used to estimate the computation time of ~CGA and GA-DEB in obtaining CNOPs. The computational costs for VCGA, GA-DEB and ADJ to catch CNOPs of the nonlinear model are also compared.展开更多
In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic...In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic priority. However,the priority of the imaging task is dynamic in actual engineering. To supplement the research on imaging observation, this paper proposes the task priority model, dynamic scheduling strategy and Heuristic algorithm. At first, this paper analyzes the relevant theoretical basis of imaging observation, decomposes the task priority into four parts, including target priority, imaging task priority, track, telemetry & control(TT&C)requirement priority and data transmission requirement priority, summarizes the attribute factors that affect the above four types of priority in detail, and designs the corresponding priority model. Then, this paper takes the emergency tasks scheduling problem as the background, proposes the dynamic scheduling strategy and heuristic algorithm. Finally, the task priority model,dynamic scheduling strategy and heuristic algorithm are verified by experiments.展开更多
In the past few years, network RTK positioning technology, especially the VRS technology, has been widely used in some parts of China and in many countries around the world. The principle of the VRS technology is disc...In the past few years, network RTK positioning technology, especially the VRS technology, has been widely used in some parts of China and in many countries around the world. The principle of the VRS technology is discussed with corresponding formula deduction, and detailed descriptions and applications of VRS corrections and virtual observations generation algorithm are given.展开更多
In this paper, a disturbance observer-based safe tracking control scheme is proposed for a medium-scale unmanned helicopter with rotor flapping dynamics in the presence of partial state constraints and unknown externa...In this paper, a disturbance observer-based safe tracking control scheme is proposed for a medium-scale unmanned helicopter with rotor flapping dynamics in the presence of partial state constraints and unknown external disturbances. A safety protection algorithm is proposed to keep the constrained states within the given safe-set. A second-order disturbance observer technique is utilized to estimate the external disturbances. It is shown that the desired tracking performance of the controlled unmanned helicopter can be achieved with the application of the backstepping approach, dynamic surface control technique, and Lyapunov method. Finally, the availability of the proposed control scheme has been shown by simulation results.展开更多
In order to solve three kinds of fuzzy programm model, fuzzy chance-constrained programming mode ng models, i.e. fuzzy expected value and fuzzy dependent-chance programming model, a simultaneous perturbation stochast...In order to solve three kinds of fuzzy programm model, fuzzy chance-constrained programming mode ng models, i.e. fuzzy expected value and fuzzy dependent-chance programming model, a simultaneous perturbation stochastic approximation algorithm is proposed by integrating neural network with fuzzy simulation. At first, fuzzy simulation is used to generate a set of input-output data. Then a neural network is trained according to the set. Finally, the trained neural network is embedded in simultaneous perturbation stochastic approximation algorithm. Simultaneous perturbation stochastic approximation algorithm is used to search the optimal solution. Two numerical examples are presented to illustrate the effectiveness of the proposed algorithm.展开更多
In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint me...In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint method from providing correct gradient during the optimization process. To address this problem, the capture of CNOP, when the "on-off" switches are included in models, is treated as non-smooth optimization in this study, and the genetic algorithm (GA) is introduced. After detailed algorithm procedures are formulated using an idealized model with parameterization "on-off" switches in the forcing term, the impacts of "on-off" switches on the capture of CNOP are analyzed, and three numerical experiments are conducted to check the effectiveness of GA in capturing CNOP and to analyze the impacts of different initial populations on the optimization result. The result shows that GA is competent for the capture of CNOP in the context of the idealized model with parameterization ‘on-off’ switches in this study. Finally, the advantages and disadvantages of GA in capturing CNOP are analyzed in detail.展开更多
This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-s...This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-strip area,real time download request,and stereoscopic request) and complex satellite actions,such as observe action and data download action,are considered in this paper. Through reasonable analysis of specialties and operational constraints of agile satellites in observing process,the mission scheduling model under multiple objective conditions is constructed. A genetic algorithm combined with heuristic rules is designed to solve problem. Genetic algorithm is designed to arrange user missions and heuristic rules are used to arrange satellite actions. Experiment results suggest that our algorithm works well for the agile Earth-observing satellite scheduling problem.展开更多
In this work, approximate analytical solutions to the lid-driven square cavity flow problem, which satisfied two-dimensional unsteady incompressible Navier-Stokes equations, are presented using the kinetically reduced...In this work, approximate analytical solutions to the lid-driven square cavity flow problem, which satisfied two-dimensional unsteady incompressible Navier-Stokes equations, are presented using the kinetically reduced local Navier-Stokes equations. Reduced differential transform method and perturbation-iteration algorithm are applied to solve this problem. The convergence analysis was discussed for both methods. The numerical results of both methods are given at some Reynolds numbers and low Mach numbers, and compared with results of earlier studies in the review of the literatures. These two methods are easy and fast to implement, and the results are close to each other and other numerical results, so it can be said that these methods are useful in finding approximate analytical solutions to the unsteady incompressible flow problems at low Mach numbers.展开更多
This paper describes the design and implementation of a three-axis acceleration control autopilot for an asymmetric tail-controlled,skid-to-turn tactical missile.In an earlier flight test,degraded autopilot performanc...This paper describes the design and implementation of a three-axis acceleration control autopilot for an asymmetric tail-controlled,skid-to-turn tactical missile.In an earlier flight test,degraded autopilot performance was attributed to multiple disturbances and uncertainties and the presence of hidden coupling terms,giving rise to a miss distance of greater than 20 m.To address these issues,the missile dynamics are decomposed into the angular rate dynamics as fast and the acceleration dynamics as slow subsystem using the singular perturbation theory to analyze a multi-time-scale property.Multifrequency extended state observers are then incorporated into the gain scheduling technique to attenuate disturbances,thus enhancing the control performance significantly.In the proposed engineering/practical design framework for missile autopilot,simple,conventional,and explicit tuning rules are provided.And the proposed control scheme can achieve input-to-state stability across the entire flight envelope under unknown but bounded disturbances.The advantages of the method over existing benchmark approaches are shown through nonlinear numerical simulations.This is supported by evidence from a new flight test result with a miss distance of only 2 m.展开更多
基金funding from the Graduate Practice Innovation Program of Jiangsu University of Technology(XSJCX23_58)Changzhou Science and Technology Support Project(CE20235045)Open Project of Jiangsu Key Laboratory of Power Transmission&Distribution Equipment Technology(2021JSSPD12).
文摘Under the partial shading conditions(PSC)of Photovoltaic(PV)modules in a PV hybrid system,the power output curve exhibits multiple peaks.This often causes traditional maximum power point tracking(MPPT)methods to fall into local optima and fail to find the global optimum.To address this issue,a composite MPPT algorithm is proposed.It combines the improved kepler optimization algorithm(IKOA)with the optimized variable-step perturb and observe(OIP&O).The update probabilities,planetary velocity and position step coefficients of IKOA are nonlinearly and adaptively optimized.This adaptation meets the varying needs of the initial and later stages of the iterative process and accelerates convergence.During stochastic exploration,the refined position update formulas enhance diversity and global search capability.The improvements in the algorithmreduces the likelihood of falling into local optima.In the later stages,the OIP&O algorithm decreases oscillation and increases accuracy.compared with cuckoo search(CS)and gray wolf optimization(GWO),simulation tests of the PV hybrid inverter demonstrate that the proposed IKOA-OIP&O algorithm achieves faster convergence and greater stability under static,local and dynamic shading conditions.These results can confirm the feasibility and effectiveness of the proposed PV MPPT algorithm for PV hybrid systems.
基金Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number (IF2-PSAU/2022/01/22797).
文摘The generation of electricity,considering environmental and eco-nomic factors is one of the most important challenges of recent years.In this article,a thermoelectric generator(TEG)is proposed to use the thermal energy of an electric water heater(EWH)to generate electricity independently.To improve the energy conversion efficiency of the TEG,a fuzzy logic con-troller(FLC)-based perturb&observe(P&O)type maximum power point tracking(MPPT)control algorithm is used in this study.An EWH is one of the major electricity consuming household appliances which causes a higher electricity price for consumers.Also,a significant amount of thermal energy generated by EWH is wasted every day,especially during the winter season.In recent years,TEGs have been widely developed to convert surplus or unused thermal energy into usable electricity.In this context,the proposed model is designed to use the thermal energy stored in the EWH to generate electricity.In addition,the generated electricity can be easily stored in a battery storage system to supply electricity to various household appliances with low-power-consumption.The proposed MPPT control algorithm helps the system to quickly reach the optimal point corresponding to the maximum power output and maintains the system operating point at the maximum power output level.To validate the usefulness of the proposed scheme,a study model was developed in the MATLAB Simulink environment and its performance was investigated by simulation under steady state and transient conditions.The results of the study confirmed that the system is capable of generating adequate power from the available thermal energy of EWH.It was also found that the output power and efficiency of the system can be improved by maintaining a higher temperature difference at the input terminals of the TEG.Moreover,the real-time temperature data of Abha city in Saudi Arabia is considered to analyze the feasibility of the proposed system for practical implementation.
文摘This paper presents an observer-based nonlinear control method that was developed and implemented to provide accurate tracking control of a limited angle torque motor following a 50Hz reference waveform. The method is based on a robust nonlinear observer, which is used to estimate system states and perturbations and then employ input-output feedbazk linearization to compensate for the system nonlinearities and uncertainties. The estimation of system states and perturbations allows input-output linearization of the nonlinear system without an accurate mathematical model of nominal plant. The simulation results show that the observer-based nonlinear control method is superior in comparison with the conventional model-based state feedback linearizing controller.
基金supported by the National Natural Science Foundation of China(7127106671171065+1 种基金71202168)the Natural Science Foundation of Heilongjiang Province(GC13D506)
文摘This study concentrates of the new generation of the agile （AEOS）. AEOS is a key study object on management problems earth observation satellite in many countries because of its many advantages over non-agile satellites. Hence, the mission planning and scheduling of AEOS is a popular research problem. This research investigates AEOS characteristics and establishes a mission planning model based on the working principle and constraints of AEOS as per analysis. To solve the scheduling issue of AEOS, several improved algorithms are developed. Simulation results suggest that these algorithms are effective.
基金support of the Noise problem of electric vehicle brushless DC motor starting(S202010641109).
文摘Wind turbine employs pitch angle control to maintain captured power at its rated value when the wind speed is higher than rated value.This work adopts a perturbation observer based sliding-mode control(POSMC)strategy to realize robust variable-pitch control of permanent magnet synchronous generator(PMSG).POSMC combines system nonlinearities,parametric uncertainties,unmodelled dynamics,and time-varying external disturbances into a perturbation,which aims to estimate the perturbation via a perturbation observer without an accurate system model.Subsequently,sliding mode control(SMC)is designed to completely compensate perturbation estimation in real-time for the sake of achieving a global consistent control performance and improving system robustness under complicated environments.Simulation results indicate that,compared with vector control(VC),feedback linearization control(FLC),and nonlinear adaptive control(NAC),POSMC has the best control performance in ramp wind and random wind and the highest robustness in terms of parameter uncertainty.Specially,the integral absolute error index of!m of POSMC is only 11.69%,12.10%and 15.14%of that of VC,FLC and NAC in random wind speed.
基金supported by the Key Technology of Flexible Regulation of Energy in Green High-Efficiency/Carbon-Efficient Buildings under the Smart Park System of PowerChina Guiyang Co.,Ltd.(YJ2022-12)the Science and Technology Support Plan of Guizhou Province“Research and Application Development of Key Technologies for Flexible Regulation of Energy in High-Efficiency/Carbon-Efficient Buildings”(Guizhou Science and Technology Cooperation Support[2023]General 409).
文摘In permanent magnet synchronous motor(PMSM)control,the jitter problem affects the system performance,so a novel reaching lawis proposed to construct a non-singular fast terminal slidingmode controller(NFTSMC)to reduce the jitter.To enhance the immunity of the system,a disturbance observer is designed to observe and compensate for the disturbance to the sliding mode controller.In addition,considering that the controller parameters are difficult to adjust,and the traditional zebra optimization algorithm(ZOA)is prone to converge prematurely and fall into local optimum when solving the optimal solution,the improved zebra optimization algorithm(IZOA)is proposed,and the ability of the IZOA in practical applications is verified by using international standard test functions.To verify the performance of IZOA,firstly,the adjustment time of IZOA is reduced by 71.67%compared with ZOA through the step response,and secondly,the tracking error of IZOA is reduced by 51.52%compared with ZOA through the sinusoidal signal following.To verify the performance of the designed controller based on disturbance observer,the designed controller reduces the speed overshoot from 2.5%to 0.63%compared with the traditional NFTSMC in the speed mutation experiment,which is a performance improvement of 70.8%,and the designed controller outperforms the traditional NFTSMC in the load mutation experiment,which is a performance improvement of 60.0%in the case of sudden load addition,and a performance improvement of 90.0%in the case of load release,which verifies that the designed controller outperforms the traditional NFTSMC.
基金supported by the National Natural Science Foundation of China (Grant No. 42288101, 42375062, 42476192, 42275158)the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (Earth Lab)the GHfund C (202407036001)
文摘The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typically input multiple time slices without deterministic dependencies.In this study,the CNOP for DLMs(CNOP-DL)is proposed as an extension of the CNOP in the time dimension.This method is useful for targeted observations as it indicates not only where but also when to deploy additional observations.The CNOP-DL is calculated for a forecast case of sea surface temperature in the South China Sea with a DLM.The CNOP-DL identifies a sensitive area northwest of Palawan Island at the last input time.Sensitivity experiments demonstrate that the sensitive area identified by the CNOP-DL is effective not only for the CNOP-DL itself,but also for random perturbations.Therefore,this approach holds potential for guiding practical field campaigns.Notably,forecast errors are more sensitive to time than to location in the sensitive area.It highlights the crucial role of identifying the time of the sensitive area in targeted observations,corroborating the usefulness of extending the CNOP in the time dimension.
基金supported by the National Natural Science Foundation of China(72071064,72271074,72001004)the Anhui Provincial Natural Science Foundation(2408085QG221).
文摘Agile earth observation satellites(AEOSs)represent a new generation of satellites with three degrees of freedom(pitch,roll,and yaw);they possess a long visible time window(VTW)for ground targets and support imaging at any moment within the VTW.However,different observation times demonstrate different cloud cover distributions,which exhibit different effects on the AEOS observation.Previous studies ignored pitch angles,discretized VTWs,or fixed cloud cover for every VTW,which led to the loss of intermediate observation states,thus these studies are not suitable for AEOS scheduling considering cloud cover distribution.In this study,a relationship formula between the cloud cover and observation time is proposed to calculate the cloud cover for every observation time,and a relationship formula between the observation time and pitch angle is designed to calculate the pitch angle for every observation time in the VTW.A refined model including the pitch angle,roll angle,and cloud cover distribution is established,which can make the scheme closer to the actual application of AEOSs.A hybrid genetic simulated annealing(HGSA)algorithm for AEOS scheduling is proposed,which integrates the advantages of genetic and simulated annealing algorithms and can effectively avoid falling into a local optimal solution.The experiments are conducted to compare the proposed algorithm with the traditional algorithms,the results verify that the proposed model and algorithm are efficient and effective for AEOS scheduling considering cloud cover distribution.
文摘A comparative study is done in regards to the performance of the popular Perturb and Observe algorithm and the Genetic Assisted-Radial Basis Function-Neural Network (GA-RBF-NN) algorithm, both incorporating the Interleaved Boost converter. The Perturb and Observe method (P&O) is inarguably the most commonly used algorithm as its advantages pertaining to its ease in implementation and simplicity enable to track the Maximum Power Point (MPP). However, it is absolutely unreliable when subjected to rapidly fluctuating irradiation and temperature levels. More importantly, the system has the tendency to swing back and forth about the Maximum Power Point without reaching stability. At this juncture, the implementation of the Genetic-Assisted Radial Basis Function (GA-RBF) algorithm helps the system achieve MPP at a shorter time when compared to the Perturb and Observe technique. The ever reliable and robust Levenberg-Marquardt algorithm is included along with the MPPT controller that minimizes the Mean Square Error (MSE) and aids in faster training of the neural network. This PV system drives a brushless DC motor (BLDC), employing rotor position sensors.
基金supported by the National Natural Science Foundation of China (No. 61203151)the National Basic Research Program of China (973 Program) (No. 2012CB720003)+2 种基金the Postdoctoral Science Foundation of China (20100471044)the Fundamental Research Funds for the Central Universities of China (No. HIT.NSRIF.2013038)the Key Laboratory Opening Funding of China (No. HIT.KLOF.2009071)
文摘This paper aims at rescheduling of observing spacecraft imaging plans under uncertainties. Firstly, uncertainties in spacecraft observation scheduling are analyzed. Then, considering the uncertainties with fuzzy features, this paper proposes a fuzzy neural network and a hybrid rescheduling policy to deal with them. It then establishes a mathematical model and manages to solve the rescheduling problem by proposing an ant colony algorithm, which introduces an adaptive control mechanism and takes advantage of the information in an existing schedule. Finally, the above method is applied to solve the rescheduling problem of a certain type of earth-observing satellite. The computation of the example shows that the approach is feasible and effective in dealing with uncertainties in spacecraft observation scheduling. The approach designed here can be useful in solving the problem that the original schedule is contaminated by disturbances.
基金supported by the National Natural Science Foundation of China(Grant No.40975063)the National Natural Science Foundation of China(Grant No.41331174)
文摘A variant constrained genetic algorithm （VCGA） for effective tracking of conditional nonlinear optimal perturbations （CNOPs） is presented. Compared with traditional constraint handling methods, the treatment of the constraint condition in VCGA is relatively easy to implement. Moreover, it does not require adjustments to indefinite pararneters. Using a hybrid crossover operator and the newly developed multi-ply mutation operator, VCGA improves the performance of GAs. To demonstrate the capability of VCGA to catch CNOPS in non-smooth cases, a partial differential equation, which has ＂on off＂ switches in its forcing term, is employed as the nonlinear model. To search global CNOPs of the nonlinear model, numerical experiments using VCGA, the traditional gradient descent algorithm based on the adjoint method （ADJ）, and a GA using tournament selection operation and the niching technique （GA-DEB） were performed. The results with various initial reference states showed that, in smooth cases, all three optimization methods are able to catch global CNOPs. Nevertheless, in non-smooth situations, a large proportion of CNOPs captured by the ADJ are local. Compared with ADJ, the performance of GA-DEB shows considerable improvement, but it is far below VCGA. Further, the impacts of population sizes on both VCGA and GA-DEB were investigated. The results were used to estimate the computation time of ~CGA and GA-DEB in obtaining CNOPs. The computational costs for VCGA, GA-DEB and ADJ to catch CNOPs of the nonlinear model are also compared.
基金supported by the National Natural Science Foundation of China(61773120,61473301,71501180,71501179,61603400)。
文摘In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic priority. However,the priority of the imaging task is dynamic in actual engineering. To supplement the research on imaging observation, this paper proposes the task priority model, dynamic scheduling strategy and Heuristic algorithm. At first, this paper analyzes the relevant theoretical basis of imaging observation, decomposes the task priority into four parts, including target priority, imaging task priority, track, telemetry & control(TT&C)requirement priority and data transmission requirement priority, summarizes the attribute factors that affect the above four types of priority in detail, and designs the corresponding priority model. Then, this paper takes the emergency tasks scheduling problem as the background, proposes the dynamic scheduling strategy and heuristic algorithm. Finally, the task priority model,dynamic scheduling strategy and heuristic algorithm are verified by experiments.
基金Funded by the National 973 Program of China (No. 2006CB701301)the Basic Research of Geomatics and Geodesy of the Key Laboratory of Geo-space Environment and Geodesy, Ministry of Education, China (No. 03-04-10)the Project of University Education and Research of Hubei Province(No.20053039).
文摘In the past few years, network RTK positioning technology, especially the VRS technology, has been widely used in some parts of China and in many countries around the world. The principle of the VRS technology is discussed with corresponding formula deduction, and detailed descriptions and applications of VRS corrections and virtual observations generation algorithm are given.
基金supported in part by the National Natural ScienceFoundation of China (U2013201)the National Science Fund for Distinguished Young Scholars (61825302)the Postgraduate Research&Practice Innovation Program of Jiangsu Province (KYCX20_0208)。
文摘In this paper, a disturbance observer-based safe tracking control scheme is proposed for a medium-scale unmanned helicopter with rotor flapping dynamics in the presence of partial state constraints and unknown external disturbances. A safety protection algorithm is proposed to keep the constrained states within the given safe-set. A second-order disturbance observer technique is utilized to estimate the external disturbances. It is shown that the desired tracking performance of the controlled unmanned helicopter can be achieved with the application of the backstepping approach, dynamic surface control technique, and Lyapunov method. Finally, the availability of the proposed control scheme has been shown by simulation results.
基金National Natural Science Foundation of China (No.70471049)China Postdoctoral Science Foundation (No. 20060400704)
文摘In order to solve three kinds of fuzzy programm model, fuzzy chance-constrained programming mode ng models, i.e. fuzzy expected value and fuzzy dependent-chance programming model, a simultaneous perturbation stochastic approximation algorithm is proposed by integrating neural network with fuzzy simulation. At first, fuzzy simulation is used to generate a set of input-output data. Then a neural network is trained according to the set. Finally, the trained neural network is embedded in simultaneous perturbation stochastic approximation algorithm. Simultaneous perturbation stochastic approximation algorithm is used to search the optimal solution. Two numerical examples are presented to illustrate the effectiveness of the proposed algorithm.
基金Application investigation of conditional nonlinear optimal perturbation in typhoon adaptive observation (40830955)
文摘In the typhoon adaptive observation based on conditional nonlinear optimal perturbation (CNOP), the ‘on-off’ switch caused by moist physical parameterization in prediction models prevents the conventional adjoint method from providing correct gradient during the optimization process. To address this problem, the capture of CNOP, when the "on-off" switches are included in models, is treated as non-smooth optimization in this study, and the genetic algorithm (GA) is introduced. After detailed algorithm procedures are formulated using an idealized model with parameterization "on-off" switches in the forcing term, the impacts of "on-off" switches on the capture of CNOP are analyzed, and three numerical experiments are conducted to check the effectiveness of GA in capturing CNOP and to analyze the impacts of different initial populations on the optimization result. The result shows that GA is competent for the capture of CNOP in the context of the idealized model with parameterization ‘on-off’ switches in this study. Finally, the advantages and disadvantages of GA in capturing CNOP are analyzed in detail.
基金Sponsored by the National Natural Science Foundation of China(Grant No.70601035 and 70801062)
文摘This paper concerns the mission scheduling problem for an agile Earth-observing satellite. Mission planning and action planning for the satellite are both taking into account. Multiple mission types( including multi-strip area,real time download request,and stereoscopic request) and complex satellite actions,such as observe action and data download action,are considered in this paper. Through reasonable analysis of specialties and operational constraints of agile satellites in observing process,the mission scheduling model under multiple objective conditions is constructed. A genetic algorithm combined with heuristic rules is designed to solve problem. Genetic algorithm is designed to arrange user missions and heuristic rules are used to arrange satellite actions. Experiment results suggest that our algorithm works well for the agile Earth-observing satellite scheduling problem.
文摘In this work, approximate analytical solutions to the lid-driven square cavity flow problem, which satisfied two-dimensional unsteady incompressible Navier-Stokes equations, are presented using the kinetically reduced local Navier-Stokes equations. Reduced differential transform method and perturbation-iteration algorithm are applied to solve this problem. The convergence analysis was discussed for both methods. The numerical results of both methods are given at some Reynolds numbers and low Mach numbers, and compared with results of earlier studies in the review of the literatures. These two methods are easy and fast to implement, and the results are close to each other and other numerical results, so it can be said that these methods are useful in finding approximate analytical solutions to the unsteady incompressible flow problems at low Mach numbers.
基金the support of the National Natural Science Foundation of China(No.U21B6003)。
文摘This paper describes the design and implementation of a three-axis acceleration control autopilot for an asymmetric tail-controlled,skid-to-turn tactical missile.In an earlier flight test,degraded autopilot performance was attributed to multiple disturbances and uncertainties and the presence of hidden coupling terms,giving rise to a miss distance of greater than 20 m.To address these issues,the missile dynamics are decomposed into the angular rate dynamics as fast and the acceleration dynamics as slow subsystem using the singular perturbation theory to analyze a multi-time-scale property.Multifrequency extended state observers are then incorporated into the gain scheduling technique to attenuate disturbances,thus enhancing the control performance significantly.In the proposed engineering/practical design framework for missile autopilot,simple,conventional,and explicit tuning rules are provided.And the proposed control scheme can achieve input-to-state stability across the entire flight envelope under unknown but bounded disturbances.The advantages of the method over existing benchmark approaches are shown through nonlinear numerical simulations.This is supported by evidence from a new flight test result with a miss distance of only 2 m.
