Suffering from actuator failure and complex sideslip angle,the motion control of a sailboat becomes challenging.In this paper,an improved double finite-time observer-based line-of-sight guidance and finite-time contro...Suffering from actuator failure and complex sideslip angle,the motion control of a sailboat becomes challenging.In this paper,an improved double finite-time observer-based line-of-sight guidance and finite-time control(IDFLOS-FC)scheme is presented for path following of sailboats.The salient features of the proposed IDFLOS-FC scheme are as follows:(1)Considering the problem of actuator failure,an actuator failure model is introduced into the dynamics model of a sailboat.(2)The time-varying sideslip angle of the sailboat is accurately observed by the double finite-time sideslip observers(DFSOs),which reduces the error in line-of-sight(LOS)guidance.(3)A radial basis function(RBF)neural network is used to fit the uncertainty of the model,and the upper bound of the sum of fault effects and external disturbances is estimated based on adaptive theory,so that the controller has accurate tracking and interference suppression.(4)According to the Lyapunov method,the system is finite-time stable.Finally,simulation was used to validate the effectiveness of the method.展开更多
A wavecatcher type scramjet intake,that reduces the Mach number number from 4 to 1.552,is used as the basis for a study of flow starting/unstarting as affected by freestream angles of attack and sideslip.The intake de...A wavecatcher type scramjet intake,that reduces the Mach number number from 4 to 1.552,is used as the basis for a study of flow starting/unstarting as affected by freestream angles of attack and sideslip.The intake design is based on a morphed streamtube consisting of two conical flow streamlines using streamline tracing and osculating axisymmetric design theory.Intake flow and performance is modeled using the numerical CFD code and the k-e turbulence model.The intake unstarts at a sideslip angle of 2,a positive angle of attack of 1.Both positive angle of attack and sideslip angle have an adverse effect on the startability of the MBus intake.At negative angles,the intake initially unstarts at5angle of attack,due to the thickened shear layer induced by the streamwise vortex.Then it re-starts at8angle of attack,mainly due to the expansion fan formed at the leading edge,causing the shock wave structures inside the intake to be reestablished.展开更多
This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake robots.Firstly,finite-time stable sideslip differentiator and adaptive LOS guidance ...This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake robots.Firstly,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track velocity.The proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle approximately.In our method,the designed piecewise auxiliary function guarantees the finite-time stability of position errors.Secondly,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s robustness.The uniform ultimate boundedness of the closed-loop system is proved by analyzing stability.Additionally,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential velocity.At last,the availability and superiority of this work are shown through simulation and experiment results.展开更多
The behaviors of front vehicles are important factors that can influence the driving safety of autonomous vehicles on highways.This situation poses a serious threat to the security of autonomous vehicles,especially wh...The behaviors of front vehicles are important factors that can influence the driving safety of autonomous vehicles on highways.This situation poses a serious threat to the security of autonomous vehicles,especially when front vehicle sideslip occurs.To address this problem,a decision-making approach can be used to promote the emergency obstacle avoidance capability of autonomous vehicles.First,the front sideslip vehicle trajectory was predicted by the kinematic models Constant Acceleration(CA),Constant Turn Rate and Velocity(CTRV),and Constant Turn Rate and Acceleration(CTRA)based on the front vehicle sideslip identification results.The CTRA prediction approach is chosen by comparing the prediction errors of the three models.To enhance the obstacle avoidance ability of autonomous vehicles,a novel trajectory planning method based on a driving characteristic vector is proposed.Model prediction control(MPC)is used to track the planned trajectory.Finally,the cosimulation platform of Simulink and Carsim was built.The simulation results show that autonomous vehicles can avoid collisions with front sideslip vehicles through the proposed approach,and the proposed trajectory planning approach has better obstacle avoidance ability than does the traditional approach.展开更多
On highways,vehicles that swerve out of their lane due to sideslip can pose a serious threat to the safety of autonomous vehicles.To ensure their safety,predicting the sideslip trajectories of such vehicles is crucial...On highways,vehicles that swerve out of their lane due to sideslip can pose a serious threat to the safety of autonomous vehicles.To ensure their safety,predicting the sideslip trajectories of such vehicles is crucial.However,the scarcity of data on vehicle sideslip scenarios makes it challenging to apply data-driven methods for prediction.Hence,this study uses a physical model-based approach to predict vehicle sideslip trajectories.Nevertheless,the traditional physical model-based method relies on constant input assumption,making its long-term prediction accuracy poor.To address this challenge,this study presents the time-series analysis and interacting multiple model-based(IMM)sideslip trajectory prediction(TSIMMSTP)method,which encompasses time-series analysis and multi-physical model fusion,for the prediction of vehicle sideslip trajectories.Firstly,we use the proposed adaptive quadratic exponential smoothing method with damping(AQESD)in the time-series analysis module to predict the input state sequence required by kinematic models.Then,we employ an IMM approach to fuse the prediction results of various physical models.The implementation of these two methods allows us to significantly enhance the long-term predictive accuracy and reduce the uncertainty of sideslip trajectories.The proposed method is evaluated through numerical simulations in vehicle sideslip scenarios,and the results clearly demonstrate that it improves the long-term prediction accuracy and reduces the uncertainty compared to other model-based methods.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52271306,52025111,and 51939003)the Central Guidance on Local Science and Technology Development Fund(No.2023JH6/100100010)the Fundamental Research Funds for the Central Universities(No.3132023501),China.
文摘Suffering from actuator failure and complex sideslip angle,the motion control of a sailboat becomes challenging.In this paper,an improved double finite-time observer-based line-of-sight guidance and finite-time control(IDFLOS-FC)scheme is presented for path following of sailboats.The salient features of the proposed IDFLOS-FC scheme are as follows:(1)Considering the problem of actuator failure,an actuator failure model is introduced into the dynamics model of a sailboat.(2)The time-varying sideslip angle of the sailboat is accurately observed by the double finite-time sideslip observers(DFSOs),which reduces the error in line-of-sight(LOS)guidance.(3)A radial basis function(RBF)neural network is used to fit the uncertainty of the model,and the upper bound of the sum of fault effects and external disturbances is estimated based on adaptive theory,so that the controller has accurate tracking and interference suppression.(4)According to the Lyapunov method,the system is finite-time stable.Finally,simulation was used to validate the effectiveness of the method.
基金National Natural Science Foundation of China(No.:12002261)National Postdoctoral Program for Innovative Talents of China(No.:BX20200267)+2 种基金Young Talent fund of University Association for Science and Technology in Shaanxi of China(No.:20200501)China Postdoctoral Science Foundation(No.:2020M673411)the Fundamental Research Funds for the Central Universities of China(No.:xzy012020096).G.Chen are grateful for the support of National Natural Science Foundation of China(No.:11872293).
文摘A wavecatcher type scramjet intake,that reduces the Mach number number from 4 to 1.552,is used as the basis for a study of flow starting/unstarting as affected by freestream angles of attack and sideslip.The intake design is based on a morphed streamtube consisting of two conical flow streamlines using streamline tracing and osculating axisymmetric design theory.Intake flow and performance is modeled using the numerical CFD code and the k-e turbulence model.The intake unstarts at a sideslip angle of 2,a positive angle of attack of 1.Both positive angle of attack and sideslip angle have an adverse effect on the startability of the MBus intake.At negative angles,the intake initially unstarts at5angle of attack,due to the thickened shear layer induced by the streamwise vortex.Then it re-starts at8angle of attack,mainly due to the expansion fan formed at the leading edge,causing the shock wave structures inside the intake to be reestablished.
基金supported in part by the National Natural Science Foundation of China(61825305,62171274,U1933125,U2241228,62273019)the Shanghai Science and Technology Major Project(2021SHZDZX)+2 种基金the National Natural Science Foundation of China through the Main Research Projecton Machine Behavior and Human-Machine Collaborated Decision Making Methodology(72192820)the Third Research Projecton Human Behavior in HumanMachine Collaboration(72192822)the China Postdoctoral Science Foundation(2022M710093)。
文摘This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake robots.Firstly,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track velocity.The proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle approximately.In our method,the designed piecewise auxiliary function guarantees the finite-time stability of position errors.Secondly,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s robustness.The uniform ultimate boundedness of the closed-loop system is proved by analyzing stability.Additionally,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential velocity.At last,the availability and superiority of this work are shown through simulation and experiment results.
基金supported by the National Key R&D Program of China(Grant No.2022YFE0101000).
文摘The behaviors of front vehicles are important factors that can influence the driving safety of autonomous vehicles on highways.This situation poses a serious threat to the security of autonomous vehicles,especially when front vehicle sideslip occurs.To address this problem,a decision-making approach can be used to promote the emergency obstacle avoidance capability of autonomous vehicles.First,the front sideslip vehicle trajectory was predicted by the kinematic models Constant Acceleration(CA),Constant Turn Rate and Velocity(CTRV),and Constant Turn Rate and Acceleration(CTRA)based on the front vehicle sideslip identification results.The CTRA prediction approach is chosen by comparing the prediction errors of the three models.To enhance the obstacle avoidance ability of autonomous vehicles,a novel trajectory planning method based on a driving characteristic vector is proposed.Model prediction control(MPC)is used to track the planned trajectory.Finally,the cosimulation platform of Simulink and Carsim was built.The simulation results show that autonomous vehicles can avoid collisions with front sideslip vehicles through the proposed approach,and the proposed trajectory planning approach has better obstacle avoidance ability than does the traditional approach.
基金supported by the National Natural Science Foundation of China(Grant No.51975310).
文摘On highways,vehicles that swerve out of their lane due to sideslip can pose a serious threat to the safety of autonomous vehicles.To ensure their safety,predicting the sideslip trajectories of such vehicles is crucial.However,the scarcity of data on vehicle sideslip scenarios makes it challenging to apply data-driven methods for prediction.Hence,this study uses a physical model-based approach to predict vehicle sideslip trajectories.Nevertheless,the traditional physical model-based method relies on constant input assumption,making its long-term prediction accuracy poor.To address this challenge,this study presents the time-series analysis and interacting multiple model-based(IMM)sideslip trajectory prediction(TSIMMSTP)method,which encompasses time-series analysis and multi-physical model fusion,for the prediction of vehicle sideslip trajectories.Firstly,we use the proposed adaptive quadratic exponential smoothing method with damping(AQESD)in the time-series analysis module to predict the input state sequence required by kinematic models.Then,we employ an IMM approach to fuse the prediction results of various physical models.The implementation of these two methods allows us to significantly enhance the long-term predictive accuracy and reduce the uncertainty of sideslip trajectories.The proposed method is evaluated through numerical simulations in vehicle sideslip scenarios,and the results clearly demonstrate that it improves the long-term prediction accuracy and reduces the uncertainty compared to other model-based methods.
