The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-base...The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.展开更多
This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a termi...This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a terminal sliding mode is constructed.The upper bound of convergence time in the proposed scheme can be adjusted by the explicit parameters during the design process of the controller.In addition,it is proved that the attitude tracking error will converge within two periods of the preset time.These two periods are set between two ranges:From the initial values to the sliding mode surface and from the sliding mode surface to the region near the origin.Furthermore,an adaptive law is adopted to eliminate unknown external disturbances and the effects of the uncertainties in the quadrotor model,so it is unnecessary to require the prior knowledge of the upper bound of the perturbations.Simulation results are produced and comparative case studies are carried out to demonstrate that the proposed scheme has faster convergence speed and smaller tracking errors.展开更多
The current research of master cylinder pressure estimation mainly relies on hydraulic characteristic or vehicle dynamics.But they are not independently applicable to any environment and have their own scope of applic...The current research of master cylinder pressure estimation mainly relies on hydraulic characteristic or vehicle dynamics.But they are not independently applicable to any environment and have their own scope of application.In addition,about the master cylinder pressure control,there are few studies that can simultaneously balance pressure building accuracy,speed,and prevent pressure overshoot and jitter.In this paper,an adaptative fusion method based on electro-hydraulic characteristic and vehicle mode is proposed to estimate the master cylinder pressure.The fusion strategy is mainly based on the prediction performance of two algorithms under different vehicle speeds,pressures,and ABS states.Apart from this,this article also includes real-time prediction of the friction model based on RLS to improve the accuracy of the electro-hydraulic mode.In order to simultaneously balance pressure control accuracy,response speed,and prevent overshoot and jitter,this article proposes an adaptative LQR controller for MC pressure control which uses fuzzy-logic controller to adjust the weights of LQR controller based on target pressure and difference compared with actual pressure.Through mode-in-loop and hardware-in-loop tests in ramp,step and sinusoidal response,the whole estimation and control system is verified based on real hydraulic system and the performance is satisfactory under these scenes.This research proposes an adaptative pressure estimation and control architecture for integrated electro-hydraulic brake system which could eliminate pressure sensors in typical scenarios and ensure the comprehensive performance of pressure control.展开更多
This paper addresses the lane-keeping control problem for autonomous ground vehicles subject to input saturation and uncertain system parameters.An enhanced adaptive terminal sliding mode based prescribed performance ...This paper addresses the lane-keeping control problem for autonomous ground vehicles subject to input saturation and uncertain system parameters.An enhanced adaptive terminal sliding mode based prescribed performance control scheme is proposed,which enables the lateral position error of the vehicle to be kept within the prescribed performance boundaries all the time.This is achieved by firstly introducing an improved performance function into the controller design such that the stringent initial condition requirements can be relaxed,which further allows the global prescribed performance control result,and then,developing a multivariable adaptive terminal sliding mode based controller such that both input saturation and parameter uncertainties are handled effectively,which further ensures the robust lane-keeping control.Finally,the proposed control strategy is validated through numerical simulations,demonstrating its effectiveness.展开更多
Accurate prediction of parking spaces plays a crucial role in maximizing the efficiency of parking resources and optimizing traffic conditions.However,the majority of earlier research has used models based on past par...Accurate prediction of parking spaces plays a crucial role in maximizing the efficiency of parking resources and optimizing traffic conditions.However,the majority of earlier research has used models based on past parking data or the plethora of variables that influence parking prediction,which not only makes the data more complicated and costs more time to run but can also lead to poor model fits.To solve this problem,a hybrid parking prediction model combining complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)and gated recurrent unit(GRU)model is proposed to predict the number of parking spaces.In this model,CEEMDAN has the ability to gradually break down time series fluctuations or trends at various scales,producing a sequence of intrinsic mode functions(IMF)with various characteristic scales.Then,by keeping the majority of the original data’s content,removing superfluous information,and enhancing predicted response time,principal component analysis(PCA)decreases the dimensionality of the IMF series.Subsequently,the high-level abstract characteristics are entered into the GRU network,and the network is built,tested,and predicted based on the deep learning framework Keras.The validity of the presented model is verified by making use of real parking datasets from two three-dimensional parking lots.The test results reveal that the model outperforms the baseline model’s predictive accuracy,i.e.,a lower testing error.The real parking time series are most closely modeled by the CEEMDAN-PCA-GRU model.As a result,the method is superior to existing models for parking prediction.展开更多
To overcome nonlinear and 6-DOF(degrees of freedom)under-actuated problems for the attitude and position of quadrotor UAVs,an adaptive backstepping sliding mode method for flight attitude of quadrotor UAVs is proposed...To overcome nonlinear and 6-DOF(degrees of freedom)under-actuated problems for the attitude and position of quadrotor UAVs,an adaptive backstepping sliding mode method for flight attitude of quadrotor UAVs is proposed,in which an adaptive law is designed to online estimate the parameter variations and the upper bound of external disturbances and the assessments is utilized to compensate the backstepping sliding mode control.In addition,the tracking error of the design method is shown to asymptotically converge to zero by using Lyapunov theory.Finally,based on the numerical simulation of quadrotor UAVs using the setting parameters,the results show that the proposed control approach can stabilize the attitude and has hover flight capabilities under the parameter perturbations and external disturbances.展开更多
In this paper, an adaptive proportional-derivative sliding mode control(APD-SMC) law, is proposed for 2D underactuated overhead crane systems. The proposed controller has the advantages of simple structure, easy to im...In this paper, an adaptive proportional-derivative sliding mode control(APD-SMC) law, is proposed for 2D underactuated overhead crane systems. The proposed controller has the advantages of simple structure, easy to implement of PD control, strong robustness of SMC with respect to external disturbances and uncertain system parameters, and adaptation for unknown system dynamics associated with the feedforward parts. In the proposed APD-SMC law, the PD control part is used to stabilize the controlled system, the SMC part is used to compensate the external disturbances and system uncertainties,and the adaptive control part is utilized to estimate the unknown system parameters. The coupling behavior between the trolley movement and the payload swing is enhanced and, therefore, the transient performance of the proposed controller is improved.The Lyapunov techniques and the La Salle's invariance theorem are employed in to support the theoretical derivations. Experimental results are provided to validate the superior performance of the proposed control law.展开更多
A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backsteppin...A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backstepping with the sliding mode control strategy could guarantee the system’s stability and track desired signals under external disturbances and engine faults. Firstly, attitude mode description and the engine faulty model are given. Secondly, a nominal control law is designed.Thirdly, a sliding mode observer is given later in order to estimate both the information of engine faults and external disturbances. An adaptive sliding mode technology based on the previous nominal control law is developed via updating faulty parameters. Finally,analyze the system’s fault-tolerant performance and reliability through experiment simulation, which verifies the proposed design of fault-tolerant control can tolerate engine faults, as well as the strong robustness for external disturbance.展开更多
Wheel polygonal wear is a common and severe defect,which seriously threatens the running safety and reliability of a railway vehicle especially a locomotive.Due to non-stationary running conditions(e.g.,traction and b...Wheel polygonal wear is a common and severe defect,which seriously threatens the running safety and reliability of a railway vehicle especially a locomotive.Due to non-stationary running conditions(e.g.,traction and braking)of the locomotive,the passing frequencies of a polygonal wheel will exhibit time-varying behaviors,which makes it too difficult to effectively detect the wheel defect.Moreover,most existing methods only achieve qualitative fault diagnosis and they cannot accurately identify defect levels.To address these issues,this paper reports a novel quantitative method for fault detection of wheel polygonization under non-stationary conditions based on a recently proposed adaptive chirp mode decomposition(ACMD)approach.Firstly,a coarse-to-fine method based on the time–frequency ridge detection and ACMD is developed to accurately estimate a time-varying gear meshing frequency and thus obtain a wheel rotating frequency from a vibration acceleration signal of a motor.After the rotating frequency is obtained,signal resampling and order analysis techniques are applied to an acceleration signal of an axle box to identify harmonic orders related to polygonal wear.Finally,the ACMD is combined with an inertial algorithm to estimate polygonal wear amplitudes.Not only a dynamics simulation but a field test was carried out to show that the proposed method can effectively detect both harmonic orders and their amplitudes of the wheel polygonization under non-stationary conditions.展开更多
Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the ...Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.展开更多
This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher...This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.展开更多
An adaptive heat source mode is proposed to account for the keyhole effect and the characteristics of volumetric distribution along the direction of the workpiece thickness. Finite element analysis of the temperature ...An adaptive heat source mode is proposed to account for the keyhole effect and the characteristics of volumetric distribution along the direction of the workpiece thickness. Finite element analysis of the temperature field in keyhole plasma arc welding is conducted and the weld geometry is obtained. The predicted results are in agreement with the measured ones.展开更多
The control synthesis of the high-speed underwater vehicle faces many technical challenges due to its inherent structure and surrounding operational environment.In this paper,the dynamical behavior is firstly describe...The control synthesis of the high-speed underwater vehicle faces many technical challenges due to its inherent structure and surrounding operational environment.In this paper,the dynamical behavior is firstly described through a bifurcation analysis to give some insights for robust control synthesis.Then a novel adaptive fractional-order sliding mode controller(AFOSMC)is realized to effectively manipulate the supercavitating vehicle against payload changes,nonlinear planing force,and external disturbances.The fractional order(FO)calculus can offer more flexibility and more freedom for tuning active control synthesis than the integer-order counterpart.In addition,the adaptation law has been presented to directly handle the payload change effects.The stability of the controlled vehicle system is proven via Lyapunov stability theory.Next,the dynamic performance of the proposed controller is verified through extensive simulation results,which demonstrate the control accuracy with faster responses compared with existing integer-order controllers.Finally,the proposed fractional order controllers can provide higher performance than their integer order counterparts with control algorithms.展开更多
This paper presents an energy-efficient control strategy for electric vehicles(EVs)driven by in-wheel-motors(IWMs)based on discrete adaptive sliding mode control(DASMC).The nonlinear vehicle model,tire model and IWM m...This paper presents an energy-efficient control strategy for electric vehicles(EVs)driven by in-wheel-motors(IWMs)based on discrete adaptive sliding mode control(DASMC).The nonlinear vehicle model,tire model and IWM model are established at first to represent the operation mechanism of the whole system.Based on the modeling,two virtual control variables are used to represent the longitudinal and yaw control efforts to coordinate the vehicle motion control.Then DASMC method is applied to calculate the required total driving torque and yaw moment,which can improve the tracking performance as well as the system robustness.According to the vehicle nonlinear model,the additional yaw moment can be expressed as a function of longitudinal and lateral tire forces.For further control scheme development,a tire force estimator using an unscented Kalman filter is designed to estimate real-time tire forces.On these bases,energy efficient torque allocation method is developed to distribute the total driving torque and differential torque to each IWM,considering the motor energy consumption,the tire slip energy consumption,and the brake energy~?recovery.Simulation results of the proposed control strategy using the co-platform of Matlab/Simulink and CarSim way.展开更多
An adaptive sliding mode controller with a disturbance observer(ASMC-DO)is proposed for the control of a single-input and single-output(SISO)servo system which has uncertain parameters,nonlinear friction,disturbance a...An adaptive sliding mode controller with a disturbance observer(ASMC-DO)is proposed for the control of a single-input and single-output(SISO)servo system which has uncertain parameters,nonlinear friction,disturbance and input saturation.It is difficult to choose the suitable value of the parameters.The newly designed adaptive method is used to reduce the effects of system time-varying parameters,such as the moment of inertia and the damp coefficient.The robustness of object is improved.A DO is selected to approximate the compound disturbance and to render the estimate error convergent in finite time.The stability and the convergence of the closed-loop system are proved by using the Lyapunov theory.Experimental results show that the proposed ASMC-DO can better satisfy the influence of variable parameters and external disturbance to the control precision of the SISO servo system than other two controllers.The effectiveness of the proposed controller is showed.The control input stability and robust performances of is reduced.the input saturation system are enhanced and the chattering is reduced.展开更多
A new adaptive quasi-sliding mode control algorithm is developed for a class of nonlinear discrete-time systems, which is especially useful for nonlinear systems with vaguely known dynamics. This design is model-free,...A new adaptive quasi-sliding mode control algorithm is developed for a class of nonlinear discrete-time systems, which is especially useful for nonlinear systems with vaguely known dynamics. This design is model-free, and is based directly on pseudo-partial-derivatives derived on-line from the input and output information of the system using an improved recursive projection type of identification algorithm. The theoretical analysis and simulation results show that the adaptive quasi-sliding mode control system is stable and convergent.展开更多
In this paper,an adaptive sliding mode method was proposed for BTT autopilot of cruise missiles with variable-swept wings. To realize the whole state feedback,the roll angle,normal overloads and angular rates were con...In this paper,an adaptive sliding mode method was proposed for BTT autopilot of cruise missiles with variable-swept wings. To realize the whole state feedback,the roll angle,normal overloads and angular rates were considered as state variables of the autopilot,and a parametric sliding mode controller was designed via feedback linearization. A novel parametric adaptation law was put forward to estimate the nonlinear timevarying parameter perturbations in real time based on Lyapunov stability theory. A sliding mode boundary layer theory was adopted to smooth the discontinuity of control variables and eliminate the control chattering. The simulation was presented for the roll angle and overload commands tracking in different configuration schemes. The results indicated that the controlled system has robust dynamic tracking performance in condition of the large-scale aerodynamic parametric variety resulted from variable-swept wings.展开更多
A new extension of the conventional adaptive fuzzy sliding mode control（AFSMC） scheme, for the case of under-actuated and uncertain affine multiple-input multiple-output（MIMO） systems, is presented. In particular,...A new extension of the conventional adaptive fuzzy sliding mode control（AFSMC） scheme, for the case of under-actuated and uncertain affine multiple-input multiple-output（MIMO） systems, is presented. In particular, the assumption for non-zero diagonal entries of the input gain matrix of the plant is relaxed. In other words, the control effect of one actuator can propagate from a subgroup of canonical state equations to the rest of equations in an indirect sense. The asymptotic stability of the proposed AFSM control method is proved using a Lyapunov-based methodology. The effectiveness of the proposed method for the case of under-actuated systems is investigated in the presence of plant uncertainties and disturbances, through simulation studies.展开更多
The complex nonlinear and non-stationary features exhibited in hydrologic sequences make hydrological analysis and forecasting difficult.Currently,some hydrologists employ the complete ensemble empirical mode decompos...The complex nonlinear and non-stationary features exhibited in hydrologic sequences make hydrological analysis and forecasting difficult.Currently,some hydrologists employ the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method,a new time-frequency analysis method based on the empirical mode decomposition(EMD)algorithm,to decompose non-stationary raw data in order to obtain relatively stationary components for further study.However,the endpoint effect in CEEMDAN is often neglected,which can lead to decomposition errors that reduce the accuracy of the research results.In this study,we processed an original runoff sequence using the radial basis function neural network(RBFNN)technique to obtain the extension sequence before utilizing CEEMDAN decomposition.Then,we compared the decomposition results of the original sequence,RBFNN extension sequence,and standard sequence to investigate the influence of the endpoint effect and RBFNN extension on the CEEMDAN method.The results indicated that the RBFNN extension technique effectively reduced the error of medium and low frequency components caused by the endpoint effect.At both ends of the components,the extension sequence more accurately reflected the true fluctuation characteristics and variation trends.These advances are of great significance to the subsequent study of hydrology.Therefore,the CEEMDAN method,combined with an appropriate extension of the original runoff series,can more precisely determine multi-time scale characteristics,and provide a credible basis for the analysis of hydrologic time series and hydrological forecasting.展开更多
In this paper, an adaptive full order sliding mode （FOSM） controller is proposed for strict feedback nonlinear systems with mismatched uncertainties. The design objective of the controller is to track a specified tr...In this paper, an adaptive full order sliding mode （FOSM） controller is proposed for strict feedback nonlinear systems with mismatched uncertainties. The design objective of the controller is to track a specified trajectory in presence of significant mismatched uncertainties. In the first step the dynamic model for the first state is considered by the desired tracking signal. After the first step the desired dynamic model for each state is defined by the previous one. An adaptive tuning law is developed for the FOSM controller to deal with the bounded system uncertainty. The major advantages offered by this adaptive FOSM controller are that advanced knowledge about the upper bound of the system uncertainties is not a necessary requirement and the proposed method is an effective solution for the chattering elimination from the control signal. The controller is designed considering the full-order sliding surface. System robustness and the stability of the controller are proved by using the Lyapunov technique. A systematic adaptive step by step design method using the full order sliding surface for mismatched nonlinear systems is presented, Simulation results validate the effectiveness of the proposed control law.展开更多
基金the China Scholarship Council(202106690037)the Natural Science Foundation of Anhui Province(19080885QE194)。
文摘The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.
文摘This paper proposes an adaptive predefined-time terminal sliding mode control(APTSMC)scheme for attitude tracking control of a quadrotor.To create this,an adaptive predefined-time stability controller based on a terminal sliding mode is constructed.The upper bound of convergence time in the proposed scheme can be adjusted by the explicit parameters during the design process of the controller.In addition,it is proved that the attitude tracking error will converge within two periods of the preset time.These two periods are set between two ranges:From the initial values to the sliding mode surface and from the sliding mode surface to the region near the origin.Furthermore,an adaptive law is adopted to eliminate unknown external disturbances and the effects of the uncertainties in the quadrotor model,so it is unnecessary to require the prior knowledge of the upper bound of the perturbations.Simulation results are produced and comparative case studies are carried out to demonstrate that the proposed scheme has faster convergence speed and smaller tracking errors.
基金Supported by National Natural Science Foundation of China(Grant Nos.52202494,52202495)Chongqing Special Project for Technological Innovation and Application Development(Grant No.CSTB2022TIAD-DEX0014).
文摘The current research of master cylinder pressure estimation mainly relies on hydraulic characteristic or vehicle dynamics.But they are not independently applicable to any environment and have their own scope of application.In addition,about the master cylinder pressure control,there are few studies that can simultaneously balance pressure building accuracy,speed,and prevent pressure overshoot and jitter.In this paper,an adaptative fusion method based on electro-hydraulic characteristic and vehicle mode is proposed to estimate the master cylinder pressure.The fusion strategy is mainly based on the prediction performance of two algorithms under different vehicle speeds,pressures,and ABS states.Apart from this,this article also includes real-time prediction of the friction model based on RLS to improve the accuracy of the electro-hydraulic mode.In order to simultaneously balance pressure control accuracy,response speed,and prevent overshoot and jitter,this article proposes an adaptative LQR controller for MC pressure control which uses fuzzy-logic controller to adjust the weights of LQR controller based on target pressure and difference compared with actual pressure.Through mode-in-loop and hardware-in-loop tests in ramp,step and sinusoidal response,the whole estimation and control system is verified based on real hydraulic system and the performance is satisfactory under these scenes.This research proposes an adaptative pressure estimation and control architecture for integrated electro-hydraulic brake system which could eliminate pressure sensors in typical scenarios and ensure the comprehensive performance of pressure control.
基金supported in part by the National Key Research and Development Program of China under Grant 2023YFA1011803in part by Natural Science Foundation of Chongqing,China under Grant CSTB2023NSCQ-MSX0588+2 种基金in part by the Fundamental Research Funds for the Central Universities,China under Grant 2023CDJKYJH047in part by the National Natural Science Foundation of China under Grant 62273064,Grant 61991400,Grant 61991403,Grant 61933012,Grant 62250710167,Grant 62203078in part by Innovation Support Program for International Students Returning to China under Grant cx2022016.
文摘This paper addresses the lane-keeping control problem for autonomous ground vehicles subject to input saturation and uncertain system parameters.An enhanced adaptive terminal sliding mode based prescribed performance control scheme is proposed,which enables the lateral position error of the vehicle to be kept within the prescribed performance boundaries all the time.This is achieved by firstly introducing an improved performance function into the controller design such that the stringent initial condition requirements can be relaxed,which further allows the global prescribed performance control result,and then,developing a multivariable adaptive terminal sliding mode based controller such that both input saturation and parameter uncertainties are handled effectively,which further ensures the robust lane-keeping control.Finally,the proposed control strategy is validated through numerical simulations,demonstrating its effectiveness.
基金the National Natural Science Foundation of China(No.52062027)the Key Research and Development Project of Gansu Province(No.22YF7GA142)+3 种基金the Soft Science Special Project of Gansu Basic Research Plan(No.22JR4ZA035)the Gansu Provincial Science and Technology Major Special Project-Enterprise Innovation Consortium Project(Nos.22ZD6GA010 and 21ZD3GA002)the Natural Science Foundation of Gansu Province(No.22JR5RA343)the Gansu Provincial Education Technology Innovation Project(No.2023CXZX-582)。
文摘Accurate prediction of parking spaces plays a crucial role in maximizing the efficiency of parking resources and optimizing traffic conditions.However,the majority of earlier research has used models based on past parking data or the plethora of variables that influence parking prediction,which not only makes the data more complicated and costs more time to run but can also lead to poor model fits.To solve this problem,a hybrid parking prediction model combining complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)and gated recurrent unit(GRU)model is proposed to predict the number of parking spaces.In this model,CEEMDAN has the ability to gradually break down time series fluctuations or trends at various scales,producing a sequence of intrinsic mode functions(IMF)with various characteristic scales.Then,by keeping the majority of the original data’s content,removing superfluous information,and enhancing predicted response time,principal component analysis(PCA)decreases the dimensionality of the IMF series.Subsequently,the high-level abstract characteristics are entered into the GRU network,and the network is built,tested,and predicted based on the deep learning framework Keras.The validity of the presented model is verified by making use of real parking datasets from two three-dimensional parking lots.The test results reveal that the model outperforms the baseline model’s predictive accuracy,i.e.,a lower testing error.The real parking time series are most closely modeled by the CEEMDAN-PCA-GRU model.As a result,the method is superior to existing models for parking prediction.
基金Project(61203021)supported by the National Natural Science Foundation of ChinaProject(2011216011)supported by the Scientific and Technological Project of Liaoning Province,China+1 种基金Project(2013020024)supported by the Natural Science Foundation of Liaoning Province,ChinaProjects(LJQ2015061,LR2015034)supported by the Program for Liaoning Excellent Talents in University,China
文摘To overcome nonlinear and 6-DOF(degrees of freedom)under-actuated problems for the attitude and position of quadrotor UAVs,an adaptive backstepping sliding mode method for flight attitude of quadrotor UAVs is proposed,in which an adaptive law is designed to online estimate the parameter variations and the upper bound of external disturbances and the assessments is utilized to compensate the backstepping sliding mode control.In addition,the tracking error of the design method is shown to asymptotically converge to zero by using Lyapunov theory.Finally,based on the numerical simulation of quadrotor UAVs using the setting parameters,the results show that the proposed control approach can stabilize the attitude and has hover flight capabilities under the parameter perturbations and external disturbances.
基金supported in part by the National High Technology Research and Development Program of China(863 Program)(2015AA042307)Shandong Provincial Scientific and Technological Development Foundation(2014GGX103038)+3 种基金Shandong Provincial Independent Innovation and Achievement Transformation Special Foundation(2015ZDXX0101E01)National Natural Science Fundation of China(NSFC)Joint Fund of Shandong Province(U1706228)the Fundamental Research Funds of Shandong University(2015JC027)
文摘In this paper, an adaptive proportional-derivative sliding mode control(APD-SMC) law, is proposed for 2D underactuated overhead crane systems. The proposed controller has the advantages of simple structure, easy to implement of PD control, strong robustness of SMC with respect to external disturbances and uncertain system parameters, and adaptation for unknown system dynamics associated with the feedforward parts. In the proposed APD-SMC law, the PD control part is used to stabilize the controlled system, the SMC part is used to compensate the external disturbances and system uncertainties,and the adaptive control part is utilized to estimate the unknown system parameters. The coupling behavior between the trolley movement and the payload swing is enhanced and, therefore, the transient performance of the proposed controller is improved.The Lyapunov techniques and the La Salle's invariance theorem are employed in to support the theoretical derivations. Experimental results are provided to validate the superior performance of the proposed control law.
基金supported by the National Natural Science Foundation of China(6140321061601228+3 种基金61603191)the Natural Science Foundation of Jiangsu(BK20161021)the Nanjing University of Posts and Telecommunications Science Foundation(NY214173)the Open Program of Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing(3DL201607)
文摘A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backstepping with the sliding mode control strategy could guarantee the system’s stability and track desired signals under external disturbances and engine faults. Firstly, attitude mode description and the engine faulty model are given. Secondly, a nominal control law is designed.Thirdly, a sliding mode observer is given later in order to estimate both the information of engine faults and external disturbances. An adaptive sliding mode technology based on the previous nominal control law is developed via updating faulty parameters. Finally,analyze the system’s fault-tolerant performance and reliability through experiment simulation, which verifies the proposed design of fault-tolerant control can tolerate engine faults, as well as the strong robustness for external disturbance.
基金This work is supported by the National Natural Science Foundation of China(Grant Nos.52005416,51735012,and 51825504)the Sichuan Science and Technology Program(Grant No.2020YJ0213)+1 种基金the Fundamental Research Funds for the Central Universities,SWJTU(Grant No.2682021CX091)the State Key Laboratory of Traction Power(Grant No.2020TPL-T 11).
文摘Wheel polygonal wear is a common and severe defect,which seriously threatens the running safety and reliability of a railway vehicle especially a locomotive.Due to non-stationary running conditions(e.g.,traction and braking)of the locomotive,the passing frequencies of a polygonal wheel will exhibit time-varying behaviors,which makes it too difficult to effectively detect the wheel defect.Moreover,most existing methods only achieve qualitative fault diagnosis and they cannot accurately identify defect levels.To address these issues,this paper reports a novel quantitative method for fault detection of wheel polygonization under non-stationary conditions based on a recently proposed adaptive chirp mode decomposition(ACMD)approach.Firstly,a coarse-to-fine method based on the time–frequency ridge detection and ACMD is developed to accurately estimate a time-varying gear meshing frequency and thus obtain a wheel rotating frequency from a vibration acceleration signal of a motor.After the rotating frequency is obtained,signal resampling and order analysis techniques are applied to an acceleration signal of an axle box to identify harmonic orders related to polygonal wear.Finally,the ACMD is combined with an inertial algorithm to estimate polygonal wear amplitudes.Not only a dynamics simulation but a field test was carried out to show that the proposed method can effectively detect both harmonic orders and their amplitudes of the wheel polygonization under non-stationary conditions.
基金authorities of East Tehran Branch,Islamic Azad University,Tehran,Iran,for providing support and necessary facilities
文摘Reasons and realities such as being non-linear of dynamical equations,being lightweight and unstable nature of quadrotor,along with internal and external disturbances and parametric uncertainties,have caused that the controller design for these quadrotors is considered the challenging issue of the day.In this work,an adaptive sliding mode controller based on neural network is proposed to control the altitude of a quadrotor.The error and error derivative of the altitude of a quadrotor are the inputs of neural network and altitude sliding surface variable is its output.Neural network estimates the sliding surface variable adaptively according to the conditions of quadrotor and sets the altitude of a quadrotor equal to the desired value.The proposed controller stability has been proven by Lyapunov theory and it is shown that all system states reach to sliding surface and are remaining in it.The superiority of the proposed control method has been proven by comparison and simulation results.
文摘This work deals with the development of a decentralized optimal control algorithm, along with a robust observer,for the relative motion control of spacecraft in leader-follower based formation. An adaptive gain higher order sliding mode observer has been proposed to estimate the velocity as well as unmeasured disturbances from the noisy position measurements.A differentiator structure containing the Lipschitz constant and Lebesgue measurable control input, is utilized for obtaining the estimates. Adaptive tuning algorithms are derived based on Lyapunov stability theory, for updating the observer gains,which will give enough flexibility in the choice of initial estimates.Moreover, it may help to cope with unexpected state jerks. The trajectory tracking problem is formulated as a finite horizon optimal control problem, which is solved online. The control constraints are incorporated by using a nonquadratic performance functional. An adaptive update law has been derived for tuning the step size in the optimization algorithm, which may help to improve the convergence speed. Moreover, it is an attractive alternative to the heuristic choice of step size for diverse operating conditions. The disturbance as well as state estimates from the higher order sliding mode observer are utilized by the plant output prediction model, which will improve the overall performance of the controller. The nonlinear dynamics defined in leader fixed Euler-Hill frame has been considered for the present work and the reference trajectories are generated using Hill-Clohessy-Wiltshire equations of unperturbed motion. The simulation results based on rigorous perturbation analysis are presented to confirm the robustness of the proposed approach.
文摘An adaptive heat source mode is proposed to account for the keyhole effect and the characteristics of volumetric distribution along the direction of the workpiece thickness. Finite element analysis of the temperature field in keyhole plasma arc welding is conducted and the weld geometry is obtained. The predicted results are in agreement with the measured ones.
文摘The control synthesis of the high-speed underwater vehicle faces many technical challenges due to its inherent structure and surrounding operational environment.In this paper,the dynamical behavior is firstly described through a bifurcation analysis to give some insights for robust control synthesis.Then a novel adaptive fractional-order sliding mode controller(AFOSMC)is realized to effectively manipulate the supercavitating vehicle against payload changes,nonlinear planing force,and external disturbances.The fractional order(FO)calculus can offer more flexibility and more freedom for tuning active control synthesis than the integer-order counterpart.In addition,the adaptation law has been presented to directly handle the payload change effects.The stability of the controlled vehicle system is proven via Lyapunov stability theory.Next,the dynamic performance of the proposed controller is verified through extensive simulation results,which demonstrate the control accuracy with faster responses compared with existing integer-order controllers.Finally,the proposed fractional order controllers can provide higher performance than their integer order counterparts with control algorithms.
基金Supported by Jiangsu Provincial Key R&D Plan (Grant No.BE2022053)Youth Fund of Jiangsu Provincial Natural Science Foundation (Grant No.BK20200423)National Natural Science Foundation of China (Grant No.5210120245)。
文摘This paper presents an energy-efficient control strategy for electric vehicles(EVs)driven by in-wheel-motors(IWMs)based on discrete adaptive sliding mode control(DASMC).The nonlinear vehicle model,tire model and IWM model are established at first to represent the operation mechanism of the whole system.Based on the modeling,two virtual control variables are used to represent the longitudinal and yaw control efforts to coordinate the vehicle motion control.Then DASMC method is applied to calculate the required total driving torque and yaw moment,which can improve the tracking performance as well as the system robustness.According to the vehicle nonlinear model,the additional yaw moment can be expressed as a function of longitudinal and lateral tire forces.For further control scheme development,a tire force estimator using an unscented Kalman filter is designed to estimate real-time tire forces.On these bases,energy efficient torque allocation method is developed to distribute the total driving torque and differential torque to each IWM,considering the motor energy consumption,the tire slip energy consumption,and the brake energy~?recovery.Simulation results of the proposed control strategy using the co-platform of Matlab/Simulink and CarSim way.
基金the National Natural Science Foundation of China(No.11472137)the Natural Science Foundation of Jiangsu Province(No.BK20140773)
文摘An adaptive sliding mode controller with a disturbance observer(ASMC-DO)is proposed for the control of a single-input and single-output(SISO)servo system which has uncertain parameters,nonlinear friction,disturbance and input saturation.It is difficult to choose the suitable value of the parameters.The newly designed adaptive method is used to reduce the effects of system time-varying parameters,such as the moment of inertia and the damp coefficient.The robustness of object is improved.A DO is selected to approximate the compound disturbance and to render the estimate error convergent in finite time.The stability and the convergence of the closed-loop system are proved by using the Lyapunov theory.Experimental results show that the proposed ASMC-DO can better satisfy the influence of variable parameters and external disturbance to the control precision of the SISO servo system than other two controllers.The effectiveness of the proposed controller is showed.The control input stability and robust performances of is reduced.the input saturation system are enhanced and the chattering is reduced.
文摘A new adaptive quasi-sliding mode control algorithm is developed for a class of nonlinear discrete-time systems, which is especially useful for nonlinear systems with vaguely known dynamics. This design is model-free, and is based directly on pseudo-partial-derivatives derived on-line from the input and output information of the system using an improved recursive projection type of identification algorithm. The theoretical analysis and simulation results show that the adaptive quasi-sliding mode control system is stable and convergent.
基金Sponsored by the National Natural Science Foundation of China(Grant No.11176012)Aviation Science Foundation of China(Grant No.20110159001)
文摘In this paper,an adaptive sliding mode method was proposed for BTT autopilot of cruise missiles with variable-swept wings. To realize the whole state feedback,the roll angle,normal overloads and angular rates were considered as state variables of the autopilot,and a parametric sliding mode controller was designed via feedback linearization. A novel parametric adaptation law was put forward to estimate the nonlinear timevarying parameter perturbations in real time based on Lyapunov stability theory. A sliding mode boundary layer theory was adopted to smooth the discontinuity of control variables and eliminate the control chattering. The simulation was presented for the roll angle and overload commands tracking in different configuration schemes. The results indicated that the controlled system has robust dynamic tracking performance in condition of the large-scale aerodynamic parametric variety resulted from variable-swept wings.
文摘A new extension of the conventional adaptive fuzzy sliding mode control（AFSMC） scheme, for the case of under-actuated and uncertain affine multiple-input multiple-output（MIMO） systems, is presented. In particular, the assumption for non-zero diagonal entries of the input gain matrix of the plant is relaxed. In other words, the control effect of one actuator can propagate from a subgroup of canonical state equations to the rest of equations in an indirect sense. The asymptotic stability of the proposed AFSM control method is proved using a Lyapunov-based methodology. The effectiveness of the proposed method for the case of under-actuated systems is investigated in the presence of plant uncertainties and disturbances, through simulation studies.
基金supported by the National Key R&D Program of China(Grant No.2018YFC0406501)Outstanding Young Talent Research Fund of Zhengzhou Uni-versity(Grant No.1521323002)+2 种基金Program for Innovative Talents(in Science and Technology)at University of Henan Province(Grant No.18HASTIT014)State Key Laboratory of Hydraulic Engineering Simulation and Safety,Tianjin University(Grant No.HESS-1717)Foundation for University Youth Key Teacher of Henan Province(Grant No.2017GGJS006).
文摘The complex nonlinear and non-stationary features exhibited in hydrologic sequences make hydrological analysis and forecasting difficult.Currently,some hydrologists employ the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method,a new time-frequency analysis method based on the empirical mode decomposition(EMD)algorithm,to decompose non-stationary raw data in order to obtain relatively stationary components for further study.However,the endpoint effect in CEEMDAN is often neglected,which can lead to decomposition errors that reduce the accuracy of the research results.In this study,we processed an original runoff sequence using the radial basis function neural network(RBFNN)technique to obtain the extension sequence before utilizing CEEMDAN decomposition.Then,we compared the decomposition results of the original sequence,RBFNN extension sequence,and standard sequence to investigate the influence of the endpoint effect and RBFNN extension on the CEEMDAN method.The results indicated that the RBFNN extension technique effectively reduced the error of medium and low frequency components caused by the endpoint effect.At both ends of the components,the extension sequence more accurately reflected the true fluctuation characteristics and variation trends.These advances are of great significance to the subsequent study of hydrology.Therefore,the CEEMDAN method,combined with an appropriate extension of the original runoff series,can more precisely determine multi-time scale characteristics,and provide a credible basis for the analysis of hydrologic time series and hydrological forecasting.
文摘In this paper, an adaptive full order sliding mode （FOSM） controller is proposed for strict feedback nonlinear systems with mismatched uncertainties. The design objective of the controller is to track a specified trajectory in presence of significant mismatched uncertainties. In the first step the dynamic model for the first state is considered by the desired tracking signal. After the first step the desired dynamic model for each state is defined by the previous one. An adaptive tuning law is developed for the FOSM controller to deal with the bounded system uncertainty. The major advantages offered by this adaptive FOSM controller are that advanced knowledge about the upper bound of the system uncertainties is not a necessary requirement and the proposed method is an effective solution for the chattering elimination from the control signal. The controller is designed considering the full-order sliding surface. System robustness and the stability of the controller are proved by using the Lyapunov technique. A systematic adaptive step by step design method using the full order sliding surface for mismatched nonlinear systems is presented, Simulation results validate the effectiveness of the proposed control law.
