A fuzzy adaptive admittance control method based on real-time estimation is proposed for the motion of the hexapod wheeled-legged robot in various environments.Firstly,the mechanical structure of the robot is designed...A fuzzy adaptive admittance control method based on real-time estimation is proposed for the motion of the hexapod wheeled-legged robot in various environments.Firstly,the mechanical structure of the robot is designed,and a control system framework is proposed according to the different motion environments.To address the adaptability issue of the robot foot contact with the ground,a position-based admittance control method is proposed.Secondly,to improve the tracking performance of the robot foot contact force when the ground environment changes,a fuzzy adaptive admittance parameter adjustment method is proposed.Furthermore,to address the problem of sudden changes in the tracking difference of the foot contact force when the ground environment changes,a real-time estimation method is proposed to estimate the dynamic foot contact force.Finally,a simulation experiment is conducted in MATLAB and Simscape to verify the effectiveness of the robot motion control system,admittance control,fuzzy adaptive admittance parameters adjustment,and the realtime estimation method.Through multi-scenario experiments with the robot prototype,the control method demonstrates its effectiveness and adaptability in various environments.展开更多
This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an a...This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.展开更多
A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip ...A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.展开更多
Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic character...Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic characteristics,and multiple constraints,such as impact angle,limited measurement of line of sight(LOS)angle rate and nonlinear saturation of canard deflection.Initially,a strict feedback cascade model of IGC in longitudinal plane was established,and extended state observer(ESO)was designed to estimate LOS angle rate and uncertain disturbances with unknown boundary inside and outside of system,including aerodynamic parameters perturbation,target maneuver and model errors.Secondly,aiming at zeroing LOS angle tracking error and LOS angle rate in finite time,a nonsingular terminal sliding mode(NTSM)was designed with adaptive exponential reaching law.Furthermore,combining with dynamic surface,which prevented the complex differential of virtual control laws,the fuzzy adaptive systems were designed to approximate observation errors of uncertain disturbances and to reduce chatter of control law.Finally,the adaptive Nussbaum gain function was introduced to compensate nonlinear saturation of canard deflection.The LOS angle tracking error and LOS angle rate were convergent in finite time and whole system states were uniform ultimately bounded,rigorously proven by Lyapunov stability theory.Hardware-in-the-loop simulation(HILS)and digital simulation experiments both showed FADS provided guided projectile with good guidance performance while striking targets with different maneuvering forms.展开更多
The purpose of this research is to improve the robustness of the autonomous system in order to improve the position and velocity estimation of an Unmanned Aerial Vehicle(UAV).Therefore, new integrated SINS/GPS navigat...The purpose of this research is to improve the robustness of the autonomous system in order to improve the position and velocity estimation of an Unmanned Aerial Vehicle(UAV).Therefore, new integrated SINS/GPS navigation scheme based on Interacting Multiple Nonlinear Fuzzy Adaptive H_∞ Models(IMM-NFAH_∞) filtering technique for UAV is presented. The proposed IMM-NFAH_∞ strategy switches between two different Nonlinear Fuzzy Adaptive H_∞(NFAH_∞) filters and each NFAH_∞ filter is based on different fuzzy logic inference systems. The newly proposed technique takes into consideration the high order Taylor series terms and adapts the nonlinear H_∞ filter based on different fuzzy inference systems via adaptive filter bounds(di),along with disturbance attenuation parameter c. Simulation analysis validates the performance of the proposed algorithm, and the comparison with nonlinear H_∞(NH_∞) filter and that with different NFAH_∞ filters demonstrate the effectiveness of UAV localization utilizing IMM-NFAH_∞ filter.展开更多
A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation err...A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation error dynamics, the observer-based decentralized indirect adaptive fuzzy control scheme is presented for a class of large-scale nonlinear systems using the combination of H∞ tracking technique, a fuzzy adaptive observer and fuzzy inference systems. The output feedback and adaptation mechanisms are both robust and implementable indeed owing to their freedom from the unavailable observation error vector. All the signals of the closed-loop largescale system are guaranteed to stay uniformly bounded and the output errors take on H∞ tracking performance. Simulation results substantiate the effectiveness of the proposed scheme.展开更多
Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of g...Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control（FARC） strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative（PD） controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.展开更多
This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. ...This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.展开更多
Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobil...Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.展开更多
In order to enhance forecasting precision of problems about nonlinear time series in a complex industry system,a new nonlinear fuzzy adaptive variable weight combined forecasting model was established by using concept...In order to enhance forecasting precision of problems about nonlinear time series in a complex industry system,a new nonlinear fuzzy adaptive variable weight combined forecasting model was established by using conceptions of the relative error,the change tendency of the forecasted object,gray basic weight and adaptive control coefficient on the basis of the method of fuzzy variable weight.Based on Visual Basic 6.0 platform,a fuzzy adaptive variable weight combined forecasting and management system was developed.The application results reveal that the forecasting precisions from the new nonlinear combined forecasting model are higher than those of other single combined forecasting models and the combined forecasting and management system is very powerful tool for the required decision in complex industry system.展开更多
Motivated by the autopilot of an unmanned aerial vehicle（UAV） with a wide flight envelope span experiencing large parametric variations in the presence of uncertainties, a fuzzy adaptive tracking controller（FATC） ...Motivated by the autopilot of an unmanned aerial vehicle（UAV） with a wide flight envelope span experiencing large parametric variations in the presence of uncertainties, a fuzzy adaptive tracking controller（FATC） is proposed. The controller consists of a fuzzy baseline controller and an adaptive increment, and the main highlight is that the fuzzy baseline controller and adaptation laws are both based on the fuzzy multiple Lyapunov function approach, which helps to reduce the conservatism for the large envelope and guarantees satisfactory tracking performances with strong robustness simultaneously within the whole envelope. The constraint condition of the fuzzy baseline controller is provided in the form of linear matrix inequality（LMI）, and it specifies the satisfactory tracking performances in the absence of uncertainties. The adaptive increment ensures the uniformly ultimately bounded（UUB） predication errors to recover satisfactory responses in the presence of uncertainties. Simulation results show that the proposed controller helps to achieve high-accuracy tracking of airspeed and altitude desirable commands with strong robustness to uncertainties throughout the entire flight envelope.展开更多
Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based en...Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.展开更多
To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership functi...To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.展开更多
The servo system actuated by oscillating pneumatic cylinder for X-Y plate is a multi-variable nonlinear control system. Its mathematical model is established, and nonlinear factors are analyzed. Due to the existence o...The servo system actuated by oscillating pneumatic cylinder for X-Y plate is a multi-variable nonlinear control system. Its mathematical model is established, and nonlinear factors are analyzed. Due to the existence of deadlock zone and the small damp of the pneumatic oscillating cylinder, it is likely to result in overshoot, and there is also certain steady-state error, so online modifying of proportion-integration-differentiation （PID） parameters is needed so as to achieve better control performance. Meanwhile considering the stability demand for long-term run, a fuzzy adaptive PID controller is designed. The result of hardware-inloop （HIL） test and real-time control experiment shows that the adaptive PID controller has desirable serfadaptability and robustness to external disturbance and to change of system parameters, and its control per- fonnance is better than that of traditional PID controllers.展开更多
To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is intro...To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is introduced and a fuzzy adaptive strong tracking cubature Kalman filter( FASTCKF) based on fuzzy logic controller is proposed. This method monitors residual absolute mean and standard deviation of each measurement component with fuzzy logic adaptive controller( FLAC),and adjusts the softening factor matrix dynamically by fuzzy rules,which is capable to modify suboptimal fading factor of STF adaptively and improve the filter's robust adaptive capacity. The simulation results show that the improved filtering performance is superior to the conventional square root cubature Kalman filter( SCKF) and the strong tracking square root cubature Kalman filter( STSCKF).展开更多
The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature.First,the so-called stochastic LaSalle theory is e...The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature.First,the so-called stochastic LaSalle theory is extended to some extent,and accordingly,the results of global ultimate boundedness for stochastic nonlinear systems are developed.Next,a new design scheme of fuzzy adaptive control is proposed.The advantage of it is that it does not require priori knowledge of virtual control gain function sign,which is usually demanded in many designs.At the same time,the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound.By theoretical analysis,the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.展开更多
Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that ca...Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that can be adjusted according to pressure feedback,thus enabling it to adapt to various body shapes.To improve the force tracking accuracy and prevent obvious force overshoot in the initial contact stage,a contact force control strategy based on fuzzy adaptive variable impedance is proposed.The proposed contact force control strategy achieves an average root-mean-square error of 0.024 and an average overshoot of 1.74%.Experimental results demonstrate that the designed deformable shield can fit the human body well,while the proposed control strategy enhances the contact force management and realizes the precise control of human-robot contact force.展开更多
In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of ...In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.展开更多
In this paper,an adaptive fuzzy state feedback control method is proposed for the single-link robotic manipulator system.The considered system contains unknown nonlinearfunction and actuator saturation.Fuzzy logic sys...In this paper,an adaptive fuzzy state feedback control method is proposed for the single-link robotic manipulator system.The considered system contains unknown nonlinearfunction and actuator saturation.Fuzzy logic systems(FLSs)and a smooth function are used to approximate the unknownnonlinearities and the actuator saturation,respectively.By com-bining the command-filter technique with the backsteppingdesign algorithm,a novel adaptive fuuzy tracking backsteppingcontrol method is developed.It is proved that the adaptive fuuzycontrol scheme can guarantee that all the variables in the closed-loop system are bounded,and the system output can track thegiven reference signal as close as possible.Simulation results areprovided to illustrate the effectiveness of the proposed approach.展开更多
This paper presents a fuzzy adaptive sliding mode controller(FASMC)for electrically driven wheeled mobile robot for trajectory tracking task in the presence of uncertainties and disturbances.First,a finite-time kinema...This paper presents a fuzzy adaptive sliding mode controller(FASMC)for electrically driven wheeled mobile robot for trajectory tracking task in the presence of uncertainties and disturbances.First,a finite-time kinematic controller is developed to compute the auxiliary velocity vector.Second,the FASMC,based on the nonlinear dynamic model of the robot and its actuators,is used to guarantee the stability and the convergence of the closed-loop system.Moreover,by employing the advantages of the fuzzy logic systems,the developed controller ensures the robustness of the system against dynamic disturbances and uncertainties,the smoothness of the computing voltage against the chattering phenomenon,and the optimal convergence of the velocity and posture errors.The Lyapunov theory is used to analyse the stability of this algorithm.In order to evaluate the effectiveness of the developed method,numerical simulations are done in the Mahlab/Simulink environment.展开更多
基金National Natural Science Foundation of China(No.U1831123)。
文摘A fuzzy adaptive admittance control method based on real-time estimation is proposed for the motion of the hexapod wheeled-legged robot in various environments.Firstly,the mechanical structure of the robot is designed,and a control system framework is proposed according to the different motion environments.To address the adaptability issue of the robot foot contact with the ground,a position-based admittance control method is proposed.Secondly,to improve the tracking performance of the robot foot contact force when the ground environment changes,a fuzzy adaptive admittance parameter adjustment method is proposed.Furthermore,to address the problem of sudden changes in the tracking difference of the foot contact force when the ground environment changes,a real-time estimation method is proposed to estimate the dynamic foot contact force.Finally,a simulation experiment is conducted in MATLAB and Simscape to verify the effectiveness of the robot motion control system,admittance control,fuzzy adaptive admittance parameters adjustment,and the realtime estimation method.Through multi-scenario experiments with the robot prototype,the control method demonstrates its effectiveness and adaptability in various environments.
基金supported by the National Natural Science Foundation of China under 62173172。
文摘This paper investigates the problem of fuzzy adaptive finite-time inverse optimal control for active suspension systems(ASSs).The fuzzy logic systems(FLSs)are utilized to learn the unknown non-linear dynamics and an auxiliary system is established.Based on the finite-time stability theory and inverse optimal theory,a fuzzy adaptive inverse finite-time inverse optimal control method is proposed.It is proven that the formulated control approach guarantees the stability of the controlled systems,while ensuring that errors converge to a small neighborhood of zero within finite time.Moreover,the optimized control performance can be achieved.Eventually,the simulation results demonstrate the effectiveness of the proposed fuzzy adaptive finite-time inverse optimal control scheme.
文摘A fuzzy adaptive control method is proposed for a flexible robot manipulator. Due to the structure characteristics of the flexible manipulator, the vibration modes must be controlled to realize the high-precision tip position. The Lagrangian principle is utilized to model the dynamic function of the single-degree flexible manipulator incorporating the assumed modes method. Simulation results of the fuzzy adaptive control method in the location control and the trajectory tracking with different tip disturbances are presented and compared with the results of the classic PD control. It shows that the controller can obtain the stable and robust performance.
基金supported by Naval Weapons and Equipment Pre-Research Project(Grant No.3020801010105).
文摘Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic characteristics,and multiple constraints,such as impact angle,limited measurement of line of sight(LOS)angle rate and nonlinear saturation of canard deflection.Initially,a strict feedback cascade model of IGC in longitudinal plane was established,and extended state observer(ESO)was designed to estimate LOS angle rate and uncertain disturbances with unknown boundary inside and outside of system,including aerodynamic parameters perturbation,target maneuver and model errors.Secondly,aiming at zeroing LOS angle tracking error and LOS angle rate in finite time,a nonsingular terminal sliding mode(NTSM)was designed with adaptive exponential reaching law.Furthermore,combining with dynamic surface,which prevented the complex differential of virtual control laws,the fuzzy adaptive systems were designed to approximate observation errors of uncertain disturbances and to reduce chatter of control law.Finally,the adaptive Nussbaum gain function was introduced to compensate nonlinear saturation of canard deflection.The LOS angle tracking error and LOS angle rate were convergent in finite time and whole system states were uniform ultimately bounded,rigorously proven by Lyapunov stability theory.Hardware-in-the-loop simulation(HILS)and digital simulation experiments both showed FADS provided guided projectile with good guidance performance while striking targets with different maneuvering forms.
基金supported by a grant from the National Natural Science Foundation of China(No.61375082)
文摘The purpose of this research is to improve the robustness of the autonomous system in order to improve the position and velocity estimation of an Unmanned Aerial Vehicle(UAV).Therefore, new integrated SINS/GPS navigation scheme based on Interacting Multiple Nonlinear Fuzzy Adaptive H_∞ Models(IMM-NFAH_∞) filtering technique for UAV is presented. The proposed IMM-NFAH_∞ strategy switches between two different Nonlinear Fuzzy Adaptive H_∞(NFAH_∞) filters and each NFAH_∞ filter is based on different fuzzy logic inference systems. The newly proposed technique takes into consideration the high order Taylor series terms and adapts the nonlinear H_∞ filter based on different fuzzy inference systems via adaptive filter bounds(di),along with disturbance attenuation parameter c. Simulation analysis validates the performance of the proposed algorithm, and the comparison with nonlinear H_∞(NH_∞) filter and that with different NFAH_∞ filters demonstrate the effectiveness of UAV localization utilizing IMM-NFAH_∞ filter.
基金supported by the National Natural Science Foundation of China(90510010).
文摘A novel H∞ tracking-based decentralized indirect adaptive output feedback fuzzy controller for a class of uncertain large-scale nonlinear systems is developed. By virtue of the proper filtering of the observation error dynamics, the observer-based decentralized indirect adaptive fuzzy control scheme is presented for a class of large-scale nonlinear systems using the combination of H∞ tracking technique, a fuzzy adaptive observer and fuzzy inference systems. The output feedback and adaptation mechanisms are both robust and implementable indeed owing to their freedom from the unavailable observation error vector. All the signals of the closed-loop largescale system are guaranteed to stay uniformly bounded and the output errors take on H∞ tracking performance. Simulation results substantiate the effectiveness of the proposed scheme.
基金supported by the National High-tech Research and Development Program of China
文摘Space robot is assembled and tested in gravity environment, and completes on-orbit service（OOS） in microgravity environment. The kinematic and dynamic characteristic of the robot will change with the variations of gravity in different working condition. Fully considering the change of kinematic and dynamic models caused by the change of gravity environment, a fuzzy adaptive robust control（FARC） strategy which is adaptive to these model variations is put forward for trajectory tracking control of space robot. A fuzzy algorithm is employed to approximate the nonlinear uncertainties in the model, adaptive laws of the parameters are constructed, and the approximation error is compensated by using a robust control algorithm. The stability of the control system is guaranteed based on the Lyapunov theory and the trajectory tracking control simulation is performed. The simulation results are compared with the proportional plus derivative（PD） controller, and the effectiveness to achieve better trajectory tracking performance under different gravity environment without changing the control parameters and the advantage of the proposed controller are verified.
基金the National Natural Science Foundation of China under Grant U22A2043.
文摘This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.
基金Project(2013AA06A411)supported by the National High Technology Research and Development Program of ChinaProject(CXZZ14_1374)supported by the Graduate Education Innovation Program of Jiangsu Province,ChinaProject supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions,China
文摘Pure inertial navigation system(INS) has divergent localization errors after a long time. In order to compensate the disadvantage, wireless sensor network(WSN) associated with the INS was applied to estimate the mobile target positioning. Taking traditional Kalman filter(KF) as the framework, the system equation of KF was established by the INS and the observation equation of position errors was built by the WSN. Meanwhile, the observation equation of velocity errors was established by the velocity difference between the INS and WSN, then the covariance matrix of Kalman filter measurement noise was adjusted with fuzzy inference system(FIS), and the fuzzy adaptive Kalman filter(FAKF) based on the INS/WSN was proposed. The simulation results show that the FAKF method has better accuracy and robustness than KF and EKF methods and shows good adaptive capacity with time-varying system noise. Finally, experimental results further prove that FAKF has the fast convergence error, in comparison with KF and EKF methods.
基金Project(08SK1002) supported by the Major Project of Science and Technology Department of Hunan Province,China
文摘In order to enhance forecasting precision of problems about nonlinear time series in a complex industry system,a new nonlinear fuzzy adaptive variable weight combined forecasting model was established by using conceptions of the relative error,the change tendency of the forecasted object,gray basic weight and adaptive control coefficient on the basis of the method of fuzzy variable weight.Based on Visual Basic 6.0 platform,a fuzzy adaptive variable weight combined forecasting and management system was developed.The application results reveal that the forecasting precisions from the new nonlinear combined forecasting model are higher than those of other single combined forecasting models and the combined forecasting and management system is very powerful tool for the required decision in complex industry system.
文摘Motivated by the autopilot of an unmanned aerial vehicle（UAV） with a wide flight envelope span experiencing large parametric variations in the presence of uncertainties, a fuzzy adaptive tracking controller（FATC） is proposed. The controller consists of a fuzzy baseline controller and an adaptive increment, and the main highlight is that the fuzzy baseline controller and adaptation laws are both based on the fuzzy multiple Lyapunov function approach, which helps to reduce the conservatism for the large envelope and guarantees satisfactory tracking performances with strong robustness simultaneously within the whole envelope. The constraint condition of the fuzzy baseline controller is provided in the form of linear matrix inequality（LMI）, and it specifies the satisfactory tracking performances in the absence of uncertainties. The adaptive increment ensures the uniformly ultimately bounded（UUB） predication errors to recover satisfactory responses in the presence of uncertainties. Simulation results show that the proposed controller helps to achieve high-accuracy tracking of airspeed and altitude desirable commands with strong robustness to uncertainties throughout the entire flight envelope.
基金supported by the National Natural Science Foundation of China(61673164)the Natural Science Foundation of Hunan Province(2020JJ6024)the Scientific Research Fund of Hunan Provincal Education Department(19K025).
文摘Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.
文摘To get simpler operation in modified fuzzy adaptive learning control network （FALCON） in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing （SA） learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived; and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.
基金Supported by Japanese SMC Corporation with contract (No. 05-07)
文摘The servo system actuated by oscillating pneumatic cylinder for X-Y plate is a multi-variable nonlinear control system. Its mathematical model is established, and nonlinear factors are analyzed. Due to the existence of deadlock zone and the small damp of the pneumatic oscillating cylinder, it is likely to result in overshoot, and there is also certain steady-state error, so online modifying of proportion-integration-differentiation （PID） parameters is needed so as to achieve better control performance. Meanwhile considering the stability demand for long-term run, a fuzzy adaptive PID controller is designed. The result of hardware-inloop （HIL） test and real-time control experiment shows that the adaptive PID controller has desirable serfadaptability and robustness to external disturbance and to change of system parameters, and its control per- fonnance is better than that of traditional PID controllers.
基金National Natural Science Foundations of China(Nos.51175082,60874092,51375088)
文摘To solve the problem that the choice of softening factor in conventional adaptive strong tracking filter( STF) greatly relies on the experience and computer simulation,a new concept of softening factor matrix is introduced and a fuzzy adaptive strong tracking cubature Kalman filter( FASTCKF) based on fuzzy logic controller is proposed. This method monitors residual absolute mean and standard deviation of each measurement component with fuzzy logic adaptive controller( FLAC),and adjusts the softening factor matrix dynamically by fuzzy rules,which is capable to modify suboptimal fading factor of STF adaptively and improve the filter's robust adaptive capacity. The simulation results show that the improved filtering performance is superior to the conventional square root cubature Kalman filter( SCKF) and the strong tracking square root cubature Kalman filter( STSCKF).
基金Supported by National Natural Science Foundation of P.R.China(60572070,60325311,60534010)Natural Science Foundation of Liaoning Province(20022030)
文摘The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature.First,the so-called stochastic LaSalle theory is extended to some extent,and accordingly,the results of global ultimate boundedness for stochastic nonlinear systems are developed.Next,a new design scheme of fuzzy adaptive control is proposed.The advantage of it is that it does not require priori knowledge of virtual control gain function sign,which is usually demanded in many designs.At the same time,the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound.By theoretical analysis,the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.
基金supported by grants from the National Key R and D Program of China(2022YFB4703300).
文摘Precise control of the contact force is crucial in the application of non-wearable defecation smart care(DSC)robot.A deformable shield equipped with a pressure sensing function is designed,with a bending angle that can be adjusted according to pressure feedback,thus enabling it to adapt to various body shapes.To improve the force tracking accuracy and prevent obvious force overshoot in the initial contact stage,a contact force control strategy based on fuzzy adaptive variable impedance is proposed.The proposed contact force control strategy achieves an average root-mean-square error of 0.024 and an average overshoot of 1.74%.Experimental results demonstrate that the designed deformable shield can fit the human body well,while the proposed control strategy enhances the contact force management and realizes the precise control of human-robot contact force.
基金Supported by National Key Research and Development Program of China(Grant No.2022YFB3403402)National Natural Science Foundation of China Basic Research Programme for PhD Students(Grant No.524B2049)。
文摘In the field of flexible polishing,the accuracy of contact force control directly affects processing quality and material removal uniformity.However,the complex dynamic contact model and inherent strong hysteresis of pneumatic systems can significantly impact the force control accuracy of pneumatic polishing system end-effectors.To enhance responsiveness and control precision during the flexible polishing process,this study proposes an observer-based fuzzy adaptive control(OBFAC)scheme.To ensure control accuracy under an uncertain dynamic contact model,a fuzzy state observer is designed to estimate unmeasured states,while fuzzy logic approximates the uncertain nonlinear functions in the model to improve control performance.Additionally,the integral barrier Lyapunov function is employed to ensure that all states remain within predefined constraints.The stability of the proposed control scheme is analyzed using the Lyapunov function,and a pneumatic polishing experimental platform is constructed to conduct polishing contact force control experiments under multiple scenarios.Experimental results demonstrate that the proposed OBFAC scheme achieves superior tracking control performance compared to existing control schemes.
基金This work was supported by the National Natural Science Foundation of China(61573175,61374113)Liaoning BaiQianWan Talents Program.
文摘In this paper,an adaptive fuzzy state feedback control method is proposed for the single-link robotic manipulator system.The considered system contains unknown nonlinearfunction and actuator saturation.Fuzzy logic systems(FLSs)and a smooth function are used to approximate the unknownnonlinearities and the actuator saturation,respectively.By com-bining the command-filter technique with the backsteppingdesign algorithm,a novel adaptive fuuzy tracking backsteppingcontrol method is developed.It is proved that the adaptive fuuzycontrol scheme can guarantee that all the variables in the closed-loop system are bounded,and the system output can track thegiven reference signal as close as possible.Simulation results areprovided to illustrate the effectiveness of the proposed approach.
文摘This paper presents a fuzzy adaptive sliding mode controller(FASMC)for electrically driven wheeled mobile robot for trajectory tracking task in the presence of uncertainties and disturbances.First,a finite-time kinematic controller is developed to compute the auxiliary velocity vector.Second,the FASMC,based on the nonlinear dynamic model of the robot and its actuators,is used to guarantee the stability and the convergence of the closed-loop system.Moreover,by employing the advantages of the fuzzy logic systems,the developed controller ensures the robustness of the system against dynamic disturbances and uncertainties,the smoothness of the computing voltage against the chattering phenomenon,and the optimal convergence of the velocity and posture errors.The Lyapunov theory is used to analyse the stability of this algorithm.In order to evaluate the effectiveness of the developed method,numerical simulations are done in the Mahlab/Simulink environment.
