Mountain glaciers have an obvious location advantage and tourist market condition over polar and high latitude glaciers. Due to the enormous economic benefit and heritage value, some mountain glaciers will always rece...Mountain glaciers have an obvious location advantage and tourist market condition over polar and high latitude glaciers. Due to the enormous economic benefit and heritage value, some mountain glaciers will always receive higher attention from commercial media, government departments and mountain tourists in China and abroad. At present, more than 100 glaciers have been devel- oped successfully as famous tourist destinations all over the world. However, global climate change seriously affects mountain glaciers and its surrounding environment. According to the current accelerated retreat trend, natural and cultural landscapes of some glaciers will be weakened, even disappear in the future. Climate change will also inevitably affect mountain ecosystems, and tourism routes under ice and glacier experience activities in these ecosystems. Simultaneously, the disappearance of mountain glaciers will also lead to a clear reduction of tourism and local economic benefits. Based on these reasons, this paper took Mr. Yulong Snow scenic area as an example and analyzed the retreat trend of a typical glacier. We then put forward some scientific and rational response mechanisms and adaptation models based on climate change in order to help future sustainable development of mountain glacier tourism.展开更多
Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction me...Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.展开更多
In this paper we deal with the problem of plants with large parameter variations under different operating modes.A novel intelligent control algorithm based on multiple models is proposed to improve the dynamical resp...In this paper we deal with the problem of plants with large parameter variations under different operating modes.A novel intelligent control algorithm based on multiple models is proposed to improve the dynamical response performance.At the same time adaptive model bank is applied to establish models without prior system information.Multiple models and corresponding controllers are automatically established on-line by a conventionally adaptive model and a re-initialized one.A best controller is chosen by the performance function at every instant.The closed-loop system's stability and asymptotical convergence of tracking error can be guaranteed.Simulation results have confirmed the validity of the proposed method.展开更多
The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range.A larger dynamic range indicates a greater probability of neuronal survival.In this study,the potential...The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range.A larger dynamic range indicates a greater probability of neuronal survival.In this study,the potential roles of adaptation mechanisms（ion currents） in modulating neuronal dynamic range were numerically investigated.Based on the adaptive exponential integrate-and-fire model,which includes two different adaptation mechanisms,i.e.subthreshold and suprathreshold（spike-triggered） adaptation,our results reveal that the two adaptation mechanisms exhibit rather different roles in regulating neuronal dynamic range.Specifically,subthreshold adaptation acts as a negative factor that observably decreases the neuronal dynamic range,while suprathreshold adaptation has little influence on the neuronal dynamic range.Moreover,when stochastic noise was introduced into the adaptation mechanisms,the dynamic range was apparently enhanced,regardless of what state the neuron was in,e.g.adaptive or non-adaptive.Our model results suggested that the neuronal dynamic range can be differentially modulated by different adaptation mechanisms.Additionally,noise was a non-ignorable factor,which could effectively modulate the neuronal dynamic range.展开更多
Objective:This study was to evaluate the quality of the randomized controlled trials on Roy adaptation model nursing in individuals suffering from acute myocardial infarction in China.Methods:We systematically searche...Objective:This study was to evaluate the quality of the randomized controlled trials on Roy adaptation model nursing in individuals suffering from acute myocardial infarction in China.Methods:We systematically searched the Cnki,Wanfang and Vipdatabases,to get randomized controlled trials on Roy adaptation model nursing in individuals suffering from acute myocardial infarction.The search period was from inception to October 2020.According to the Cochrane risk bias assessment tool,the quality of the studies included was appraised.Results:A total of 55 studies were retrieved,and 11 were eventually included in the study.Among the studies included,the first study was published in 2008.The overall quality of the 11 studies included was relatively low.Conclusions:The overall quality of the randomized controlled trials on Roy adaptation model nursing in individuals suffering from acute myocardial infarction was not high,which would hinder the evidence transformation as well as clinical practice.展开更多
Calorific value is one of the most important properties of coal.Machine learning(ML)can be used in the prediction of calorific value to reduce experimental costs.China is one of the world’s largest coal production co...Calorific value is one of the most important properties of coal.Machine learning(ML)can be used in the prediction of calorific value to reduce experimental costs.China is one of the world’s largest coal production countries and coal occupies an important position in its national energy structure.However,ML models with a large database for the overall regions of China are still missing.Based on the extensive coal gasification practices in East China University of Science and Technology,we have built ML models with a large database for overall regions of China.An AutoML model was proposed and achieved a minimum MSE of 1.021.SHAP method was used to increase the model interpretability,and model validity was proved with literature data and additional in-house experiments.The model adaptability was discussed based on the databases of China and USA,showing that geography-specific ML models are essential.This study integrated a large coal database and AutoML method for accurate calorific value prediction and could offer key tools for Chinese coal industry.展开更多
To address the limitations of traditional manual highway guardrail inspections,this paper proposes an obstacle-crossing and collaborative tracking control method for a rail-mounted robot.Static and dynamic analyses ve...To address the limitations of traditional manual highway guardrail inspections,this paper proposes an obstacle-crossing and collaborative tracking control method for a rail-mounted robot.Static and dynamic analyses verify the robot's structural reliability and driving feasibility.Based on the leader-follower model,a triangular collaborative tracking model is developed,and a linear time-varying model predictive controll(LTV-MPC)is designed to achieve smooth and precise collaborative control.For obstacle crossing,an acceleration reference model and a gradient-based adaptive law are proposed,leading to a model reference adaptive controll(MRAC)that effectively suppresses vibrations and ensures synchronous control.Simulation results show that the MPC achieves a 0.415%overshoot and a 0.344 m steady-state accuracy,while also reducing the intensity of speed fluctuations by 35%.The MRAC ensures smooth obstacle-crossing speeds and adaptive strategy switching,validating the reliability and practicality of the rail-mounted robot under complex working conditions.展开更多
The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compe...The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compensator based on functional link neural network is used to deal with the engine nonlinearity and the hardware-in-loop simulation is also developed. The results show that the nonlinear MRAC controller has the adequate performance of compensating and adapting nonlinearity arising from the change of engine state or working environment. Such feature demonstrates potential practical applications of MRAC for aeroengine control system.展开更多
A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the...A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the model reference adaptive control law is designed and an adaptive compensator is used for improving its self-re- pairing capability. To enhance anti-interference capability of helicopter, quantum control feedforward is added be- tween fault and disturbance. Simulation results illustrate the effectiveness and feasibility of the approach.展开更多
The application of a simplifed model reference adaptive control(SMRAC) on a typical Pump controlled motor electrohydraulic servo system is studied here. The algorithm of first-order scalar SMRAC ac second-order vector...The application of a simplifed model reference adaptive control(SMRAC) on a typical Pump controlled motor electrohydraulic servo system is studied here. The algorithm of first-order scalar SMRAC ac second-order vector SMRAC are derived. Computer simulations of the algorithms are presented. Experimental results prove that the method of control adopted here perform satisfactorily over a wide range of operating conditions.展开更多
Based on a simplified model reference adaptive control(SMRAC) algorithm a parameter modification algorithm according to fuzzy laws is proposed in this paper. The method makes the adaptive parameters in SMRAC only rely...Based on a simplified model reference adaptive control(SMRAC) algorithm a parameter modification algorithm according to fuzzy laws is proposed in this paper. The method makes the adaptive parameters in SMRAC only rely on the status of performance error. Thus it eliminates the influences of gain coefficients in SMRAC and the amplitude of input signal on the dynamic characteristics. Experiments on various step amplitudes and loads show that the performances of SMRAC are improved by incorporating fuzzy modification method.展开更多
A new decentralized adaptive control scheme is presented for linear time invariant systems with first order interconnections. The proposed control scheme with “proportional plus integral” terms is used to improve ...A new decentralized adaptive control scheme is presented for linear time invariant systems with first order interconnections. The proposed control scheme with “proportional plus integral” terms is used to improve the convergence rate and the ultimate bound of the tracking error. It is important to note that the adaptive scheme uses lower adaptive gains and smaller control inputs to avoid input saturation and oscillatory behavior. Simulation results are illustrated for controlling a dual inverted pendulum and a multivariable turbofan engine using the proposed adaptive scheme. These simulations validate out conclusions.展开更多
Aim To present an adaptive missile control system adaped to the external disturbance and the mobility of target movement. Methods Model reference adaptive control (MRAC) was applied and modified in the light of the ...Aim To present an adaptive missile control system adaped to the external disturbance and the mobility of target movement. Methods Model reference adaptive control (MRAC) was applied and modified in the light of the traits of the anti tank missile. Results Simulation results demonstrated this control system satisfied the requirement of anti tank missile of dive overhead attack. Conclusion It is successful to use MRAC in missile control system design, the quality is better than that designed by classical control theory.展开更多
Aircraft passengers are more and demanding in terms of thermal comfort. But it is not yet easy for aircraft crew to control the environment control system （ECS） that satisfies the thermal comfort for most passengers...Aircraft passengers are more and demanding in terms of thermal comfort. But it is not yet easy for aircraft crew to control the environment control system （ECS） that satisfies the thermal comfort for most passengers due to a number of causes. This paper adopts a corrected predicted mean vote （PMV） model and an adaptive model to assess the thermal comfort conditions for 31 investigated flights and draws the conclusion that there does exist an uncomfortable thermal phe- nomenon in civil aircraft cabins, especially in some short-haul continental flights. It is necessary to develop an easy way to predict the thermal sensation of passengers and to direct the crew to con- trol ECS. Due to the assessment consistency of the corrected PMV model and the adaptive model, the adaptive model of thermal neutrality temperature can be used as a method to predict the cabin optimal operative temperature. Because only the mean outdoor effective temperature ET＊ of a departure city is an input variable for the adaptive model, this method can be easily understood and implemented by the crew and can satisfy 80-90% of the thermal acceptability levels of passen- gers.展开更多
A novel robust fault diagnosis scheme, which possesses fault estimate capability as well as fault diagnosis property, is proposed. The scheme is developed based on a suitable combination of the adaptive multiple model...A novel robust fault diagnosis scheme, which possesses fault estimate capability as well as fault diagnosis property, is proposed. The scheme is developed based on a suitable combination of the adaptive multiple model （AMM） and unknown input observer （UIO）. The main idea of the proposed scheme stems from the fact that the actuator Lock-in-Place fault is unknown （when and where the actuator gets locked are unknown）, and multiple models are used to describe different fault scenarios, then a bank of unknown input observers are designed to implement the disturbance de-coupling. According to Lyapunov theory, proof of the robustness of the newly developed scheme in the presence of faults and disturbances is derived. Numerical simulation results on an aircraft example show satisfactory performance of the proposed algorithm.展开更多
The existing methods for blade polishing mainly focus on robot polishing and manual grinding.Due to the difficulty in high-precision control of the polishing force,the blade surface precision is very low in robot poli...The existing methods for blade polishing mainly focus on robot polishing and manual grinding.Due to the difficulty in high-precision control of the polishing force,the blade surface precision is very low in robot polishing,in particular,quality of the inlet and exhaust edges can not satisfy the processing requirements.Manual grinding has low efficiency,high labor intensity and unstable processing quality,moreover,the polished surface is vulnerable to burn,and the surface precision and integrity are difficult to ensure.In order to further improve the profile accuracy and surface quality,a pneumatic flexible polishing force-exerting mechanism is designed and a dual-mode switching composite adaptive control(DSCAC) strategy is proposed,which combines Bang-Bang control and model reference adaptive control based on fuzzy neural network(MRACFNN) together.By the mode decision-making mechanism,Bang-Bang control is used to track the control command signal quickly when the actual polishing force is far away from the target value,and MRACFNN is utilized in smaller error ranges to improve the system robustness and control precision.Based on the mathematical model of the force-exerting mechanism,simulation analysis is implemented on DSCAC.Simulation results show that the output polishing force can better track the given signal.Finally,the blade polishing experiments are carried out on the designed polishing equipment.Experimental results show that DSCAC can effectively mitigate the influence of gas compressibility,valve dead-time effect,valve nonlinear flow,cylinder friction,measurement noise and other interference on the control precision of polishing force,which has high control precision,strong robustness,strong anti-interference ability and other advantages compared with MRACFNN.The proposed research achieves high-precision control of the polishing force,effectively improves the blade machining precision and surface consistency,and significantly reduces the surface roughness.展开更多
As one of the core issues of the mobile robot motion control, trajectory tracking has received extensive attention. At present, the solution of the problem only takes kinematic or dynamic model into account separately...As one of the core issues of the mobile robot motion control, trajectory tracking has received extensive attention. At present, the solution of the problem only takes kinematic or dynamic model into account separately, so that the presented strategy is difficult to realize satisfactory tracking quality in practical application. Considering the unknown parameters of two models, this paper presents an adaptive controller for solving the trajectory tracking problem of a mobile robot. Firstly, an adaptive kinematic controller utilized to generate the command of velocity is designed based on Backstepping method. Then, in order to make the real velocity of mobile robot reach the desired velocity asymptotically, a dynamic adaptive controller is proposed adopting reference model and Lyapunov stability theory. Finally, through simulating typical trajectories including circular trajectory, fold line and parabola trajectory in normal and perturbed cases, the results illustrate that the control scheme can solve the tracking problem effectively. The proposed control law, which can tune the kinematic and dynamic model parameters online and overcome external disturbances, provides a novel method for improving trajectory tracking performance of the mobile robot.展开更多
Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique an...Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique and adaptive trade-off model, named ATMDE, is proposed to solve constrained optimization problems. The proposed ATMDE algorithm employs an improved differential evolution as the search optimizer to generate new offspring individuals into evolutionary population. For the con- straints, the adaptive trade-off model as one of the most important constraint-handling techniques is employed to select better individuals to retain into the next population, which could effectively handle multiple constraints. Then the shrinking space technique is designed to shrink the search region according to feedback information in order to improve computational efficiency without losing accuracy. The improved DE algorithm introduces three different mutant strategies to generate different offspring into evo- lutionary population. Moreover, a new mutant strategy called ＂DE/rand/best/l＂ is constructed to generate new individuals according to the feasibility proportion ofcurrent population. Finally, the effectiveness of the pro- posed method is verified by a suite of benchmark functions and practical engineering problems. This research presents a constrained evolutionary algorithm with high efficiency and accuracy for constrained optimization problems.展开更多
In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support ve...In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.展开更多
基金funded by the open fund (SKLCS2011-04) from Stake Key Laboratory of Cryospheric Sciences and National Social Science Foundation of China(12BJY127)
文摘Mountain glaciers have an obvious location advantage and tourist market condition over polar and high latitude glaciers. Due to the enormous economic benefit and heritage value, some mountain glaciers will always receive higher attention from commercial media, government departments and mountain tourists in China and abroad. At present, more than 100 glaciers have been devel- oped successfully as famous tourist destinations all over the world. However, global climate change seriously affects mountain glaciers and its surrounding environment. According to the current accelerated retreat trend, natural and cultural landscapes of some glaciers will be weakened, even disappear in the future. Climate change will also inevitably affect mountain ecosystems, and tourism routes under ice and glacier experience activities in these ecosystems. Simultaneously, the disappearance of mountain glaciers will also lead to a clear reduction of tourism and local economic benefits. Based on these reasons, this paper took Mr. Yulong Snow scenic area as an example and analyzed the retreat trend of a typical glacier. We then put forward some scientific and rational response mechanisms and adaptation models based on climate change in order to help future sustainable development of mountain glacier tourism.
基金Project supported by the National Natural Science Foundation of China(Nos.12272211,12072181,12121002)。
文摘Interval model updating(IMU)methods have been widely used in uncertain model updating due to their low requirements for sample data.However,the surrogate model in IMU methods mostly adopts the one-time construction method.This makes the accuracy of the surrogate model highly dependent on the experience of users and affects the accuracy of IMU methods.Therefore,an improved IMU method via the adaptive Kriging models is proposed.This method transforms the objective function of the IMU problem into two deterministic global optimization problems about the upper bound and the interval diameter through universal grey numbers.These optimization problems are addressed through the adaptive Kriging models and the particle swarm optimization(PSO)method to quantify the uncertain parameters,and the IMU is accomplished.During the construction of these adaptive Kriging models,the sample space is gridded according to sensitivity information.Local sampling is then performed in key subspaces based on the maximum mean square error(MMSE)criterion.The interval division coefficient and random sampling coefficient are adaptively adjusted without human interference until the model meets accuracy requirements.The effectiveness of the proposed method is demonstrated by a numerical example of a three-degree-of-freedom mass-spring system and an experimental example of a butted cylindrical shell.The results show that the updated results of the interval model are in good agreement with the experimental results.
基金supported by National Natural Science Foundation of China(No.60574006)the Specialized Research Fund for DoctoralProgram of Higher Education of China(No.20030286013)+1 种基金Provincial Natural Science Foundation of Jiangsu(No.BK2003405)GraduateInnovative Project of Jiangsu Province(2005).
文摘In this paper we deal with the problem of plants with large parameter variations under different operating modes.A novel intelligent control algorithm based on multiple models is proposed to improve the dynamical response performance.At the same time adaptive model bank is applied to establish models without prior system information.Multiple models and corresponding controllers are automatically established on-line by a conventionally adaptive model and a re-initialized one.A best controller is chosen by the performance function at every instant.The closed-loop system's stability and asymptotical convergence of tracking error can be guaranteed.Simulation results have confirmed the validity of the proposed method.
基金supported by a grant from Beijing Municipal Commission of Science and Technology of China,No.Z151100000915070
文摘The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range.A larger dynamic range indicates a greater probability of neuronal survival.In this study,the potential roles of adaptation mechanisms（ion currents） in modulating neuronal dynamic range were numerically investigated.Based on the adaptive exponential integrate-and-fire model,which includes two different adaptation mechanisms,i.e.subthreshold and suprathreshold（spike-triggered） adaptation,our results reveal that the two adaptation mechanisms exhibit rather different roles in regulating neuronal dynamic range.Specifically,subthreshold adaptation acts as a negative factor that observably decreases the neuronal dynamic range,while suprathreshold adaptation has little influence on the neuronal dynamic range.Moreover,when stochastic noise was introduced into the adaptation mechanisms,the dynamic range was apparently enhanced,regardless of what state the neuron was in,e.g.adaptive or non-adaptive.Our model results suggested that the neuronal dynamic range can be differentially modulated by different adaptation mechanisms.Additionally,noise was a non-ignorable factor,which could effectively modulate the neuronal dynamic range.
基金This research was supported by National Natural Science Foundation of China(No.81603565)Tianjin University of Traditional Chinese Medicine Postgraduate Research Innovation Project(YJSKC-20201032).
文摘Objective:This study was to evaluate the quality of the randomized controlled trials on Roy adaptation model nursing in individuals suffering from acute myocardial infarction in China.Methods:We systematically searched the Cnki,Wanfang and Vipdatabases,to get randomized controlled trials on Roy adaptation model nursing in individuals suffering from acute myocardial infarction.The search period was from inception to October 2020.According to the Cochrane risk bias assessment tool,the quality of the studies included was appraised.Results:A total of 55 studies were retrieved,and 11 were eventually included in the study.Among the studies included,the first study was published in 2008.The overall quality of the 11 studies included was relatively low.Conclusions:The overall quality of the randomized controlled trials on Roy adaptation model nursing in individuals suffering from acute myocardial infarction was not high,which would hinder the evidence transformation as well as clinical practice.
基金Shanghai Yangfan Program,22YF1410300,Yunfei GaoNational Natural Science Foundation of China,22208104,Yunfei Gao+1 种基金Shanghai Chenguang Program,21CGA35,Yunfei GaoNational Key Research and Development Program of China,2022YFA1504701,Yunfei Gao,2022YFB4101900,Yunfei Gao。
文摘Calorific value is one of the most important properties of coal.Machine learning(ML)can be used in the prediction of calorific value to reduce experimental costs.China is one of the world’s largest coal production countries and coal occupies an important position in its national energy structure.However,ML models with a large database for the overall regions of China are still missing.Based on the extensive coal gasification practices in East China University of Science and Technology,we have built ML models with a large database for overall regions of China.An AutoML model was proposed and achieved a minimum MSE of 1.021.SHAP method was used to increase the model interpretability,and model validity was proved with literature data and additional in-house experiments.The model adaptability was discussed based on the databases of China and USA,showing that geography-specific ML models are essential.This study integrated a large coal database and AutoML method for accurate calorific value prediction and could offer key tools for Chinese coal industry.
基金Supported by the Shaanxi Provincial Key Research and Development Program(2024GX-YBXM-288)the Science and Technology Project of Shaanxi Provincial Transportation Department(21-20K)the National Natural Science Foundation of China(52172324)。
文摘To address the limitations of traditional manual highway guardrail inspections,this paper proposes an obstacle-crossing and collaborative tracking control method for a rail-mounted robot.Static and dynamic analyses verify the robot's structural reliability and driving feasibility.Based on the leader-follower model,a triangular collaborative tracking model is developed,and a linear time-varying model predictive controll(LTV-MPC)is designed to achieve smooth and precise collaborative control.For obstacle crossing,an acceleration reference model and a gradient-based adaptive law are proposed,leading to a model reference adaptive controll(MRAC)that effectively suppresses vibrations and ensures synchronous control.Simulation results show that the MPC achieves a 0.415%overshoot and a 0.344 m steady-state accuracy,while also reducing the intensity of speed fluctuations by 35%.The MRAC ensures smooth obstacle-crossing speeds and adaptive strategy switching,validating the reliability and practicality of the rail-mounted robot under complex working conditions.
文摘The design of a turbofan rotor speed control system, using model reference adaptive control（MRAC） method with input and output measurements, is discussed for the purpose of practical application. The nonlinear compensator based on functional link neural network is used to deal with the engine nonlinearity and the hardware-in-loop simulation is also developed. The results show that the nonlinear MRAC controller has the adequate performance of compensating and adapting nonlinearity arising from the change of engine state or working environment. Such feature demonstrates potential practical applications of MRAC for aeroengine control system.
基金Supported by the National Natural Science Foundation of China(61074080)the Innovation Foundation for Aeronautical Science and Technology(08C52001)~~
文摘A direct self-repairing control approach is proposed for helicopter via quantum control techniques and adaptive compensator when some complex faults occur. For a linear varying-parameter helicopter control system, the model reference adaptive control law is designed and an adaptive compensator is used for improving its self-re- pairing capability. To enhance anti-interference capability of helicopter, quantum control feedforward is added be- tween fault and disturbance. Simulation results illustrate the effectiveness and feasibility of the approach.
文摘The application of a simplifed model reference adaptive control(SMRAC) on a typical Pump controlled motor electrohydraulic servo system is studied here. The algorithm of first-order scalar SMRAC ac second-order vector SMRAC are derived. Computer simulations of the algorithms are presented. Experimental results prove that the method of control adopted here perform satisfactorily over a wide range of operating conditions.
文摘Based on a simplified model reference adaptive control(SMRAC) algorithm a parameter modification algorithm according to fuzzy laws is proposed in this paper. The method makes the adaptive parameters in SMRAC only rely on the status of performance error. Thus it eliminates the influences of gain coefficients in SMRAC and the amplitude of input signal on the dynamic characteristics. Experiments on various step amplitudes and loads show that the performances of SMRAC are improved by incorporating fuzzy modification method.
文摘A new decentralized adaptive control scheme is presented for linear time invariant systems with first order interconnections. The proposed control scheme with “proportional plus integral” terms is used to improve the convergence rate and the ultimate bound of the tracking error. It is important to note that the adaptive scheme uses lower adaptive gains and smaller control inputs to avoid input saturation and oscillatory behavior. Simulation results are illustrated for controlling a dual inverted pendulum and a multivariable turbofan engine using the proposed adaptive scheme. These simulations validate out conclusions.
文摘Aim To present an adaptive missile control system adaped to the external disturbance and the mobility of target movement. Methods Model reference adaptive control (MRAC) was applied and modified in the light of the traits of the anti tank missile. Results Simulation results demonstrated this control system satisfied the requirement of anti tank missile of dive overhead attack. Conclusion It is successful to use MRAC in missile control system design, the quality is better than that designed by classical control theory.
基金supported by the Civil Aircraft Pre-research Project of China
文摘Aircraft passengers are more and demanding in terms of thermal comfort. But it is not yet easy for aircraft crew to control the environment control system （ECS） that satisfies the thermal comfort for most passengers due to a number of causes. This paper adopts a corrected predicted mean vote （PMV） model and an adaptive model to assess the thermal comfort conditions for 31 investigated flights and draws the conclusion that there does exist an uncomfortable thermal phe- nomenon in civil aircraft cabins, especially in some short-haul continental flights. It is necessary to develop an easy way to predict the thermal sensation of passengers and to direct the crew to con- trol ECS. Due to the assessment consistency of the corrected PMV model and the adaptive model, the adaptive model of thermal neutrality temperature can be used as a method to predict the cabin optimal operative temperature. Because only the mean outdoor effective temperature ET＊ of a departure city is an input variable for the adaptive model, this method can be easily understood and implemented by the crew and can satisfy 80-90% of the thermal acceptability levels of passen- gers.
基金the National Natural Science Foundation of China (60574083)Aeronautics Science Foun-dation of China (2007ZC52039)
文摘A novel robust fault diagnosis scheme, which possesses fault estimate capability as well as fault diagnosis property, is proposed. The scheme is developed based on a suitable combination of the adaptive multiple model （AMM） and unknown input observer （UIO）. The main idea of the proposed scheme stems from the fact that the actuator Lock-in-Place fault is unknown （when and where the actuator gets locked are unknown）, and multiple models are used to describe different fault scenarios, then a bank of unknown input observers are designed to implement the disturbance de-coupling. According to Lyapunov theory, proof of the robustness of the newly developed scheme in the presence of faults and disturbances is derived. Numerical simulation results on an aircraft example show satisfactory performance of the proposed algorithm.
基金supported by National Natural Science Foundation of China(Grant No.51005184)National Science and Technology Major Project of Ministry of Science and Technology of China(Grant No.2009ZX04014-053)
文摘The existing methods for blade polishing mainly focus on robot polishing and manual grinding.Due to the difficulty in high-precision control of the polishing force,the blade surface precision is very low in robot polishing,in particular,quality of the inlet and exhaust edges can not satisfy the processing requirements.Manual grinding has low efficiency,high labor intensity and unstable processing quality,moreover,the polished surface is vulnerable to burn,and the surface precision and integrity are difficult to ensure.In order to further improve the profile accuracy and surface quality,a pneumatic flexible polishing force-exerting mechanism is designed and a dual-mode switching composite adaptive control(DSCAC) strategy is proposed,which combines Bang-Bang control and model reference adaptive control based on fuzzy neural network(MRACFNN) together.By the mode decision-making mechanism,Bang-Bang control is used to track the control command signal quickly when the actual polishing force is far away from the target value,and MRACFNN is utilized in smaller error ranges to improve the system robustness and control precision.Based on the mathematical model of the force-exerting mechanism,simulation analysis is implemented on DSCAC.Simulation results show that the output polishing force can better track the given signal.Finally,the blade polishing experiments are carried out on the designed polishing equipment.Experimental results show that DSCAC can effectively mitigate the influence of gas compressibility,valve dead-time effect,valve nonlinear flow,cylinder friction,measurement noise and other interference on the control precision of polishing force,which has high control precision,strong robustness,strong anti-interference ability and other advantages compared with MRACFNN.The proposed research achieves high-precision control of the polishing force,effectively improves the blade machining precision and surface consistency,and significantly reduces the surface roughness.
基金supported by State Key Laboratory of Robotics and System of China (Grant No. SKLR-2010 -MS - 14)State Key Lab of Embedded System and Service Computing of China(Grant No. 2010-11)
文摘As one of the core issues of the mobile robot motion control, trajectory tracking has received extensive attention. At present, the solution of the problem only takes kinematic or dynamic model into account separately, so that the presented strategy is difficult to realize satisfactory tracking quality in practical application. Considering the unknown parameters of two models, this paper presents an adaptive controller for solving the trajectory tracking problem of a mobile robot. Firstly, an adaptive kinematic controller utilized to generate the command of velocity is designed based on Backstepping method. Then, in order to make the real velocity of mobile robot reach the desired velocity asymptotically, a dynamic adaptive controller is proposed adopting reference model and Lyapunov stability theory. Finally, through simulating typical trajectories including circular trajectory, fold line and parabola trajectory in normal and perturbed cases, the results illustrate that the control scheme can solve the tracking problem effectively. The proposed control law, which can tune the kinematic and dynamic model parameters online and overcome external disturbances, provides a novel method for improving trajectory tracking performance of the mobile robot.
基金Supported by National Science Foundation for Excellent Young Scholars,China(Grant No.51222502)Funds for Distinguished Young Scientists of Hunan Province,China(Grant No.14JJ1016)Major Program of National Natural Science Foundation of China(Grant No.51490662)
文摘Most of the current evolutionary algorithms for constrained optimization algorithm are low computational efficiency. In order to improve efficiency, an improved differential evolution with shrinking space technique and adaptive trade-off model, named ATMDE, is proposed to solve constrained optimization problems. The proposed ATMDE algorithm employs an improved differential evolution as the search optimizer to generate new offspring individuals into evolutionary population. For the con- straints, the adaptive trade-off model as one of the most important constraint-handling techniques is employed to select better individuals to retain into the next population, which could effectively handle multiple constraints. Then the shrinking space technique is designed to shrink the search region according to feedback information in order to improve computational efficiency without losing accuracy. The improved DE algorithm introduces three different mutant strategies to generate different offspring into evo- lutionary population. Moreover, a new mutant strategy called ＂DE/rand/best/l＂ is constructed to generate new individuals according to the feasibility proportion ofcurrent population. Finally, the effectiveness of the pro- posed method is verified by a suite of benchmark functions and practical engineering problems. This research presents a constrained evolutionary algorithm with high efficiency and accuracy for constrained optimization problems.
基金co-supported by Aeronautical Science Foundation of China (No. 2010ZB52011)Funding of Jiangsu Innovation Program for Graduate Education (No.CXLX11_0213)
文摘In order to establish an adaptive turbo-shaft engine model with high accuracy, a new modeling method based on parameter selection （PS） algorithm and multi-input multi-output recursive reduced least square support vector regression （MRR-LSSVR） machine is proposed. Firstly, the PS algorithm is designed to choose the most reasonable inputs of the adaptive module. During this process, a wrapper criterion based on least square support vector regression （LSSVR） machine is adopted, which can not only reduce computational complexity but also enhance generalization performance. Secondly, with the input variables determined by the PS algorithm, a mapping model of engine parameter estimation is trained off-line using MRR-LSSVR, which has a satisfying accuracy within 5＆. Finally, based on a numerical simulation platform of an integrated helicopter/ turbo-shaft engine system, an adaptive turbo-shaft engine model is developed and tested in a certain flight envelope. Under the condition of single or multiple engine components being degraded, many simulation experiments are carried out, and the simulation results show the effectiveness and validity of the proposed adaptive modeling method.
