With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overc...With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control(ILC),a novel real-time iterative compensation(RIC)control framework is proposed for precision motion systems without changing the inner closed-loop controller.Specifically,the RIC method can be divided into two parts,i.e.,accurate model prediction and real-time iterative compensation.An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times.In light of predicted errors,a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation.Both the prediction and compen-sation processes are finished in a real-time motion control sampling period.The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions.Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability,which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.展开更多
A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by t...A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.展开更多
The contour error was analyzed based on CNC multi-axis motion control, the contour error model was obtained focused on beeline and different radius of curvature and common contour of curve, for a CNC biaxial motion co...The contour error was analyzed based on CNC multi-axis motion control, the contour error model was obtained focused on beeline and different radius of curvature and common contour of curve, for a CNC biaxial motion control system and the mechanism of producing contour error and the relationship between tracking error and contour error were presented. The theoretical and practical significance of modeling error and controlling error in motion control systems was carried out.展开更多
Digital twin can simulate and monitor the state and behavior of physical entities in the real world,helping enterprises to better understand and manage real-world physical systems,improve production efficiency,reduce ...Digital twin can simulate and monitor the state and behavior of physical entities in the real world,helping enterprises to better understand and manage real-world physical systems,improve production efficiency,reduce costs,and improve safety and reliability.In this paper,we use GTS motion control card and Unity engine to build a digital twin system,and control a virtual industrial automation handling platform including two screw servo axes and multiple sensors through the physical GTS motion control card.The control card program controls the motion of the virtual model through transmission control protocol(TCP)communication,and the virtual model system feeds back the signal to the control card program to achieve the virtual and real synchronous digital twin effect.The digital twin system uses Unity engine to create a highly realistic virtual environment,and can run on multi-platform terminals.展开更多
This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters,mismatched and matched disturbances.Different from the traditional adaptive results ...This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters,mismatched and matched disturbances.Different from the traditional adaptive results that are applied to dispose of unknown constant parameters only,the unique feature is that an adaptive-gain nonlinear term is introduced into the control design to handle unknown time-variant parameters.Concurrently both mismatched and matched disturbances existing in electro-hydraulic axis systems can also be addressed in this way.With skillful integration of the backstepping technique and the adaptive control,a synthesized controller framework is successfully developed for electro-hydraulic axis systems,in which the coupled interaction between parameter estimation and disturbance estimation is avoided.Accordingly,this designed controller has the capacity of low-computation costs and simpler parameter tuning when compared to the other ones that integrate the adaptive control and observer/estimator-based technique to dividually handle parameter uncertainties and disturbances.Also,a nonlinear filter is designed to eliminate the“explosion of complexity”issue existing in the classical back-stepping technique.The stability analysis uncovers that all the closed-loop signals are bounded and the asymptotic tracking performance is also assured.Finally,contrastive experiment results validate the superiority of the developed method as well.展开更多
Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt e...Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt effectively to diverse environments and traverse rugged terrains.This makes them well-suited for applications such as search and rescue,exploration,and transportation,with strong environmental adaptability,high flexibility,and broad application prospects.This paper discusses the current state of research on quadruped robots in terms of development status,gait trajectory planning methods,motion control strategies,reinforcement learning applications,and control algorithm integration.It highlights advancements in modeling,optimization,control,and data-driven approaches.The study identifies the adoption of efficient gait planning algorithms,the integration of reinforcement learning-based control technologies,and data-driven methods as key directions for the development of quadruped robots.The aim is to provide theoretical references for researchers in the field of quadruped robotics.展开更多
The intelligent vehicle corner module system,which integrates four-wheel independent drive,independent steering,independent braking and active suspension,can accurately and efficiently perform vehicle driving tasks an...The intelligent vehicle corner module system,which integrates four-wheel independent drive,independent steering,independent braking and active suspension,can accurately and efficiently perform vehicle driving tasks and is the best carrier of intelligent vehicles.Nevertheless,too many angle/torque control inputs make control difficult and non-real-time.In this paper,a hierarchical real-time motion control framework for corner module configuration intelligent electric vehicles is proposed.In the trajectory planning module,an improved driving risk field is designed to describe the surrounding environment’s driving risk.Combined with the kinematic vehicle-road model,model predictive control(MPC)method,spline curve method,the local reference trajectory of safety,comfort and smoothness is planned in real time.The optimal steering angle is determined using MPC method in path tracking module.In the motion control module,a feedforward-feedback controller assigns the optimal steering angle to the front/rear axles,and an angle allocation controller distributes the target angles of the front/rear axles to four steered wheels.Finally,the PreScan-Simulink-CarSim joint simulation environment is established for conducting the human-in-the-loop emergency obstacle avoidance experiment.It took only 0.005 s for the hierarchical motion control system to determine its average solution time.This proves the effectiveness of the hierarchical motion control system.展开更多
This paper is concerned with a non-intrusive anomaly detection method for carving machine systems with variant working conditions,and a novel unsupervised detection framework that integrates convolutional autoencoder(...This paper is concerned with a non-intrusive anomaly detection method for carving machine systems with variant working conditions,and a novel unsupervised detection framework that integrates convolutional autoencoder(CAE)and Gaussian mixture hidden Markov model(GMHMM)is proposed.Firstly,the built-in sensor information under normal conditions is recorded,and a 1D convolutional autoencoder is employed to compress high-dimensional time series,thereby transforming the anomaly detection problem in high-dimensional space into a density estimation problem in a latent low-dimensional space.Then,two separate estimation networks are utilized to predict the mixture memberships and state transition probabilities for each sample,enabling GMHMM to handle low-dimensional representations and multi-condition information.Furthermore,a cost function comprising CAE reconstruction and GMHMM probability assessment is constructed for the low-dimensional representation generation and subsequent density estimation in an end-to-end fashion,and the joint optimization effectively enhances the anomaly detection performance.Finally,experiments are carried out on a self-developed multi-axis carving machine platform to validate the effectiveness and superiority of the proposed method.展开更多
Model mismatches can cause multi-dimensional uncertainties for the receding horizon control strategies of automated vehicles(AVs).The uncertainties may lead to potentially hazardous behaviors when the AV tracks ideal ...Model mismatches can cause multi-dimensional uncertainties for the receding horizon control strategies of automated vehicles(AVs).The uncertainties may lead to potentially hazardous behaviors when the AV tracks ideal trajectories that are individually optimized by the AV's planning layer.To address this issue,this study proposes a safe motion planning and control(SMPAC)framework for AVs.For the control layer,a dynamic model including multi-dimensional uncertainties is established.A zonotopic tube-based robust model predictive control scheme is proposed to constrain the uncertain system in a bounded minimum robust positive invariant set.A flexible tube with varying cross-sections is constructed to reduce the controller conservatism.For the planning layer,a concept of safety sets,representing the geometric boundaries of the ego vehicle and obstacles under uncertainties,is proposed.The safety sets provide the basis for the subsequent evaluation and ranking of the generated trajectories.An efficient collision avoidance algorithm decides the desired trajectory through the intersection detection of the safety sets between the ego vehicle and obstacles.A numerical simulation and hardware-in-the-loop experiment validate the effectiveness and real-time performance of the SMPAC.The result of two driving scenarios indicates that the SMPAC can guarantee the safety of automated driving under multi-dimensional uncertainties.展开更多
Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Trac...Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking(HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance,multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase.The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.展开更多
This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing singl...This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.展开更多
The dynamic motion capability of humanoid robots is a key indicator for evaluating their performance.Jumping,as a typical dynamic motion,is of great significance for enhancing the robot’s flexibility and terrain adap...The dynamic motion capability of humanoid robots is a key indicator for evaluating their performance.Jumping,as a typical dynamic motion,is of great significance for enhancing the robot’s flexibility and terrain adaptability in unstructured environments.However,achieving high-dynamic jumping control of humanoid robots has become a challenge due to the high degree of freedom and strongly coupled dynamic characteristics.The idea for this paper originated from the human response process to jumping commands,aiming to achieve online trajectory optimization and jumping motion control of humanoid robots.Firstly,we employ nonlinear optimization in combination with the Single Rigid Body Model(SRBM)to generate a robot’s Center of Mass(CoM)trajectory that complies with physical constraints and minimizes the angular momentum of the CoM.Then,a Model Predictive Controller(MPC)is designed to track and control the CoM trajectory,obtaining the required contact forces at the robot’s feet.Finally,a Whole-Body Controller(WBC)is used to generate full-body joint motion trajectories and driving torques,based on the prioritized sequence of tasks designed for the jumping process.The control framework proposed in this paper considers the dynamic characteristics of the robot’s jumping process,with a focus on improving the real-time performance of trajectory optimization and the robustness of controller.Simulation and experimental results demonstrate that our robot successfully executed high jump motions,long jump motions and continuous jump motions under complex working conditions.展开更多
Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encounter...Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encountering difficulties with diverse industrial structures lacking standardized computer-aided design(CAD)models or in instances of deformation.Inspired by the multidimensional observation of humans,our study introduces a universal image acquisition paradigm tailored for robotics,seamlessly integrating multi-objective optimization trajectory planning and control scheme to harness measured point clouds for versatile,efficient,and highly accurate image acquisition across diverse structures and scenarios.Specifically,we introduce an energybased adaptive trajectory optimization(EBATO)method that combines deformation and deviation with dual-threshold optimization and adaptive weight adjustment to improve the smoothness and accuracy of imaging trajectory and posture.Additionally,a multi-optimization control scheme based on a meta-heuristic beetle antennal olfactory recurrent neural network(BAORNN)is proposed to track the imaging trajectory while addressing posture,obstacle avoidance,and physical constraints in industrial scenarios.Simulations,real-world experiments,and comparisons demonstrate the effectiveness and practicality of the proposed paradigm.展开更多
Although scientists have performed many studies in the Taklimakan Desert, few of them have reported the blown sand motion along the southern edge of the Taklimakan Desert Highway, which differs significantly from the ...Although scientists have performed many studies in the Taklimakan Desert, few of them have reported the blown sand motion along the southern edge of the Taklimakan Desert Highway, which differs significantly from the northern region in terms of aeolian sand geomorphology and formation environment. Based on the field ob- servation data of airflow and aeolian sand transport, continuous monitoring data of erosional and depositional processes between 14 April 2009 and 9 April 2011 and data of surface sand grains from the classical section along the southern edge of the Taklimakan Desert Highway, this paper reported the blown sand motion within the sand-control system of the highway. The main results are as follows： 1） The existing sand-control system is highly effective in preventing and controlling desertification. Wind velocities within the sand-control system were ap- proximately 33%-100% of those for the same height above the mobile sand surface. Aeolian sand fluxes were approximately 0-31.21% of those of the mobile sand surface. Sand grains inside the system, with a mean diameter of 2.89 q）, were finer than those （2.15 q）） outside the system. In addition, wind velocities basically followed a loga- rithmic law, but the airflow along the classical section was mainly determined by topography and vegetation. 2） There were obvious erosional and depositional phenomena above the surface within the sand-control system, and these phenomena have very consistent patterns for all observation points in the two observed years. The total thicknesses of erosion and deposition ranged from 0.30 to 14.60 cm, with a mean value of 3.67 cm. In contrast, the deposition thicknesses were 1.90-22.10 cm, with a mean value of 7.59 cm, and the erosion thicknesses were 3.51-15.10 cm, with a mean value of 8.75 cm. The results will aid our understanding of blown sand within the sand-control system and provide a strong foundation for optimizing the sand-control system.展开更多
This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm ha...This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.展开更多
Magnetism parameters vary with the position and the speed of electromagnetic actuator's motion parts.The measurement unit presented in the paper can be applied to get the position and the speed feedback informatio...Magnetism parameters vary with the position and the speed of electromagnetic actuator's motion parts.The measurement unit presented in the paper can be applied to get the position and the speed feedback information from the measurement of electromagnetism parameters,and can constitute the untouched feedback sensing unit in the closed-loop motion control,and it adapts to the diversified feedback control of electromagnetic actuator.The digital miniaturization meter,based on MSP430 single chip processor,which can do the multi-purpose measurement of Φ & B through the menu selection,can be used for the electromagnetic actuator's performance evaluation and improvement,and also the online quality control in production process.Both real-time data graph and data table can be displayed in the meter.The paper presents the system's structure,describes the principle,discusses the working modes,and shows the software flowchart and the measuring results.展开更多
To develop a control system of cantilever arm for barrels welding, a motion controller has been developed to fit the welding procedure. The main research fields of the controller are: (1) finding effective measures to...To develop a control system of cantilever arm for barrels welding, a motion controller has been developed to fit the welding procedure. The main research fields of the controller are: (1) finding effective measures to protect the controller against interferences; (2) decreasing welding current gradually in order to alleviate arc craters which are harmful to seam forming and welding quality; (3) planning the arm velocity to minimize the influence of the arm swing on arc length regulator; (4) adopting adaptive control algorithm with PD feedback and velocity feed-forward to reduce the influence of system inertia and velocity planning on the system transient performance.展开更多
Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for ...Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for helical microrobots to perform various tasks. In this study, an automatic control method is proposed to realize the axial docking of helical microrobots with arbitrarily placed cylindrical objects in liquid environments. The docking process is divided into ascent, approach, alignment, and insertion stages. First, a 3D docking path is planned according to the positions and orientations of the microrobot and the target object. Second, a steering-based 3D path-following controller guides the helical microrobot to rise away from the container bottom and approach the target along the path. Third, based on path design with gravity compensation and steering output limits, alignment of position and orientation can be accomplished simultaneously. Finally, the helical microrobot completes the docking under the rotating magnetic field along the target orientation. Experiments verified the automatic docking of the helical microrobot with static targets, including connecting with micro-shafts and inserting into micro-tubes. The object grasping of a reconfigurable helical microrobot aided by 3D automatic docking was also demonstrated. This method enables precise docking of helical microrobots with objects, which might be used for capture and sampling, in vivo navigation control, and functional assembly of microrobots.展开更多
The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the ...The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency domain.Despite being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.展开更多
The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low mov...The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low movement level on rough roads. In this paper, a novel and low-cost wheeled bipedal robot with an asymmetrical five-link mechanism is proposed, and the kinematics of the legs and the dynamics of the Wheeled Inverted Pendulum (WIP) are modeled. The primary balance controller of the wheeled bipedal robot is built based on the Linear Quadratic Regulator (LQR) and the compensation method of the virtual pitch angle adjusting the Center of Mass (CoM) position, then the whole-body hybrid torque-position control is established by combining attitude and leg controllers. The stability of the robot’s attitude control and motion is verified with simulations and prototype experiments, which confirm the robot’s ability to pass through complex terrain and resist external interference. The feasibility and reliability of the proposed control model are verified.展开更多
基金This work was supported in part by the National Nature Science Foundation of China(51922059)in part by the Beijing Natural Science Foundation(JQ19010)in part by the China Postdoctoral Science Foundation(2021T140371).
文摘With regard to precision/ultra-precision motion systems,it is important to achieve excellent tracking performance for various trajectory tracking tasks even under uncertain external disturbances.In this paper,to overcome the limitation of robustness to trajectory variations and external disturbances in offline feedforward compensation strategies such as iterative learning control(ILC),a novel real-time iterative compensation(RIC)control framework is proposed for precision motion systems without changing the inner closed-loop controller.Specifically,the RIC method can be divided into two parts,i.e.,accurate model prediction and real-time iterative compensation.An accurate prediction model considering lumped disturbances is firstly established to predict tracking errors at future sampling times.In light of predicted errors,a feedforward compensation term is developed to modify the following reference trajectory by real-time iterative calculation.Both the prediction and compen-sation processes are finished in a real-time motion control sampling period.The stability and convergence of the entire control system after real-time iterative compensation is analyzed for different conditions.Various simulation results consistently demonstrate that the proposed RIC framework possesses satisfactory dynamic regulation capability,which contributes to high tracking accuracy comparable to ILC or even better and strong robustness.
基金Project(51005086)supported by the National Natural Science Foundation of ChinaProject(2010MS085)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(DMETKF2013008)supported by the Open Project of the State Key Laboratory of Digital Manufacturing Equipment and Technology,China
文摘A layered modeling method is proposed to resolve the problems resulting from the complexity of the error model of a multi-axis motion control system. In this model, a low level layer can be used as a virtual axis by the high level layer. The first advantage of this model is that the complex error model of a four-axis motion control system can be divided into several simple layers and each layer has different coupling strength to match the real control system. The second advantage lies in the fact that the controller in each layer can be designed specifically for a certain purpose. In this research, a three-layered cross coupling scheme in a four-axis motion control system is proposed to compensate the contouring error of the motion control system. Simulation results show that the maximum contouring error is reduced from 0.208 mm to 0.022 mm and the integration of absolute error is reduced from 0.108 mm to 0.015 mm, which are respectively better than 0.027 mm and 0.037 mm by the traditional method. And in the bottom layer the proposed method also has remarkable ability to achieve high contouring accuracy.
基金supported by the Science Foundation of the Education Office of Gansu Province of Chinaunder Grant No.0914-01
文摘The contour error was analyzed based on CNC multi-axis motion control, the contour error model was obtained focused on beeline and different radius of curvature and common contour of curve, for a CNC biaxial motion control system and the mechanism of producing contour error and the relationship between tracking error and contour error were presented. The theoretical and practical significance of modeling error and controlling error in motion control systems was carried out.
基金Research Startup Project of Shenzhen Polytechnic University“Research and Development of High-Speed and High-Resolution 2D/3D Combined Vision Sensor”(Project No.6022312003K).
文摘Digital twin can simulate and monitor the state and behavior of physical entities in the real world,helping enterprises to better understand and manage real-world physical systems,improve production efficiency,reduce costs,and improve safety and reliability.In this paper,we use GTS motion control card and Unity engine to build a digital twin system,and control a virtual industrial automation handling platform including two screw servo axes and multiple sensors through the physical GTS motion control card.The control card program controls the motion of the virtual model through transmission control protocol(TCP)communication,and the virtual model system feeds back the signal to the control card program to achieve the virtual and real synchronous digital twin effect.The digital twin system uses Unity engine to create a highly realistic virtual environment,and can run on multi-platform terminals.
基金supported in part by the National Key R&D Program of China(No.2021YFB2011300)the National Natural Science Foundation of China(No.52075262,51905271,52275062)+1 种基金the Fok Ying-Tong Education Foundation of China(No.171044)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.KYCX22_0471)。
文摘This article focuses on asymptotic precision motion control for electro-hydraulic axis systems under unknown time-variant parameters,mismatched and matched disturbances.Different from the traditional adaptive results that are applied to dispose of unknown constant parameters only,the unique feature is that an adaptive-gain nonlinear term is introduced into the control design to handle unknown time-variant parameters.Concurrently both mismatched and matched disturbances existing in electro-hydraulic axis systems can also be addressed in this way.With skillful integration of the backstepping technique and the adaptive control,a synthesized controller framework is successfully developed for electro-hydraulic axis systems,in which the coupled interaction between parameter estimation and disturbance estimation is avoided.Accordingly,this designed controller has the capacity of low-computation costs and simpler parameter tuning when compared to the other ones that integrate the adaptive control and observer/estimator-based technique to dividually handle parameter uncertainties and disturbances.Also,a nonlinear filter is designed to eliminate the“explosion of complexity”issue existing in the classical back-stepping technique.The stability analysis uncovers that all the closed-loop signals are bounded and the asymptotic tracking performance is also assured.Finally,contrastive experiment results validate the superiority of the developed method as well.
基金funded by the Natural Science Basis Research Plan in Shaanxi Province of China(Program No.2023-JC-QN-0659)General Specialized Scientific Research Program of the Shaanxi Provincial Department of Education(Program 23JK0349).
文摘Legged robots have always been a focal point of research for scholars domestically and internationally.Compared to other types of robots,quadruped robots exhibit superior balance and stability,enabling them to adapt effectively to diverse environments and traverse rugged terrains.This makes them well-suited for applications such as search and rescue,exploration,and transportation,with strong environmental adaptability,high flexibility,and broad application prospects.This paper discusses the current state of research on quadruped robots in terms of development status,gait trajectory planning methods,motion control strategies,reinforcement learning applications,and control algorithm integration.It highlights advancements in modeling,optimization,control,and data-driven approaches.The study identifies the adoption of efficient gait planning algorithms,the integration of reinforcement learning-based control technologies,and data-driven methods as key directions for the development of quadruped robots.The aim is to provide theoretical references for researchers in the field of quadruped robotics.
基金Supported by National Natural Science Foundation of China(Grant No.52332013)。
文摘The intelligent vehicle corner module system,which integrates four-wheel independent drive,independent steering,independent braking and active suspension,can accurately and efficiently perform vehicle driving tasks and is the best carrier of intelligent vehicles.Nevertheless,too many angle/torque control inputs make control difficult and non-real-time.In this paper,a hierarchical real-time motion control framework for corner module configuration intelligent electric vehicles is proposed.In the trajectory planning module,an improved driving risk field is designed to describe the surrounding environment’s driving risk.Combined with the kinematic vehicle-road model,model predictive control(MPC)method,spline curve method,the local reference trajectory of safety,comfort and smoothness is planned in real time.The optimal steering angle is determined using MPC method in path tracking module.In the motion control module,a feedforward-feedback controller assigns the optimal steering angle to the front/rear axles,and an angle allocation controller distributes the target angles of the front/rear axles to four steered wheels.Finally,the PreScan-Simulink-CarSim joint simulation environment is established for conducting the human-in-the-loop emergency obstacle avoidance experiment.It took only 0.005 s for the hierarchical motion control system to determine its average solution time.This proves the effectiveness of the hierarchical motion control system.
基金Supported by the National Natural Science Foundation of China(No.62203390).
文摘This paper is concerned with a non-intrusive anomaly detection method for carving machine systems with variant working conditions,and a novel unsupervised detection framework that integrates convolutional autoencoder(CAE)and Gaussian mixture hidden Markov model(GMHMM)is proposed.Firstly,the built-in sensor information under normal conditions is recorded,and a 1D convolutional autoencoder is employed to compress high-dimensional time series,thereby transforming the anomaly detection problem in high-dimensional space into a density estimation problem in a latent low-dimensional space.Then,two separate estimation networks are utilized to predict the mixture memberships and state transition probabilities for each sample,enabling GMHMM to handle low-dimensional representations and multi-condition information.Furthermore,a cost function comprising CAE reconstruction and GMHMM probability assessment is constructed for the low-dimensional representation generation and subsequent density estimation in an end-to-end fashion,and the joint optimization effectively enhances the anomaly detection performance.Finally,experiments are carried out on a self-developed multi-axis carving machine platform to validate the effectiveness and superiority of the proposed method.
基金supported by the National Natural Science Foundation of China(51875061)China Scholarship Council(202206050107)。
文摘Model mismatches can cause multi-dimensional uncertainties for the receding horizon control strategies of automated vehicles(AVs).The uncertainties may lead to potentially hazardous behaviors when the AV tracks ideal trajectories that are individually optimized by the AV's planning layer.To address this issue,this study proposes a safe motion planning and control(SMPAC)framework for AVs.For the control layer,a dynamic model including multi-dimensional uncertainties is established.A zonotopic tube-based robust model predictive control scheme is proposed to constrain the uncertain system in a bounded minimum robust positive invariant set.A flexible tube with varying cross-sections is constructed to reduce the controller conservatism.For the planning layer,a concept of safety sets,representing the geometric boundaries of the ego vehicle and obstacles under uncertainties,is proposed.The safety sets provide the basis for the subsequent evaluation and ranking of the generated trajectories.An efficient collision avoidance algorithm decides the desired trajectory through the intersection detection of the safety sets between the ego vehicle and obstacles.A numerical simulation and hardware-in-the-loop experiment validate the effectiveness and real-time performance of the SMPAC.The result of two driving scenarios indicates that the SMPAC can guarantee the safety of automated driving under multi-dimensional uncertainties.
基金the National Key Research and Development Plan,China(No.2019YFB1706502)the National Natural Science Foundation of China(Nos.62003366,12102077,12072059)+1 种基金the China Postdoctoral Science Foundation(No.2020M670744)the Natural Science Foundation of Liaoning Province,China(No.2010-ZD-0021)。
文摘Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking(HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance,multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase.The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.
基金supported in part by the National Natural Science Foundation of China (62373065,61873304,62173048,62106023)the Innovation and Entrepreneurship Talent funding Project of Jilin Province(2022QN04)+1 种基金the Changchun Science and Technology Project (21ZY41)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University (2024D09)。
文摘This paper presents a distributed scheme with limited communications, aiming to achieve cooperative motion control for multiple omnidirectional mobile manipulators(MOMMs).The proposed scheme extends the existing single-agent motion control to cater to scenarios involving the cooperative operation of MOMMs. Specifically, squeeze-free cooperative load transportation is achieved for the end-effectors of MOMMs by incorporating cooperative repetitive motion planning(CRMP), while guiding each individual to desired poses. Then, the distributed scheme is formulated as a time-varying quadratic programming(QP) and solved online utilizing a noise-tolerant zeroing neural network(NTZNN). Theoretical analysis shows that the NTZNN model converges globally to the optimal solution of QP in the presence of noise. Finally, the effectiveness of the control design is demonstrated by numerical simulations and physical platform experiments.
基金supported in part by the National Key Research and Development Program of China(2020YFB13134)Major Project of National Natural Science Foundation of China(U2013602)+2 种基金The National Nature Science Foundation of China(52075115)HIT Major Campus Cultivation Project(2023FRFK01001)National independent project(SKLRS202301A12).
文摘The dynamic motion capability of humanoid robots is a key indicator for evaluating their performance.Jumping,as a typical dynamic motion,is of great significance for enhancing the robot’s flexibility and terrain adaptability in unstructured environments.However,achieving high-dynamic jumping control of humanoid robots has become a challenge due to the high degree of freedom and strongly coupled dynamic characteristics.The idea for this paper originated from the human response process to jumping commands,aiming to achieve online trajectory optimization and jumping motion control of humanoid robots.Firstly,we employ nonlinear optimization in combination with the Single Rigid Body Model(SRBM)to generate a robot’s Center of Mass(CoM)trajectory that complies with physical constraints and minimizes the angular momentum of the CoM.Then,a Model Predictive Controller(MPC)is designed to track and control the CoM trajectory,obtaining the required contact forces at the robot’s feet.Finally,a Whole-Body Controller(WBC)is used to generate full-body joint motion trajectories and driving torques,based on the prioritized sequence of tasks designed for the jumping process.The control framework proposed in this paper considers the dynamic characteristics of the robot’s jumping process,with a focus on improving the real-time performance of trajectory optimization and the robustness of controller.Simulation and experimental results demonstrate that our robot successfully executed high jump motions,long jump motions and continuous jump motions under complex working conditions.
基金supported in part by the National Natural Science Foundation of China(62303457,U21A20482)China Postdoctoral Science Foundation(2023M733737)the National Key Research and Development Program of China(2022YFB3303800)。
文摘Image acquisition stands as a prerequisite for scrutinizing surfaces inspection in industrial high-end manufacturing.Current imaging systems often exhibit inflexibility,being confined to specific objects and encountering difficulties with diverse industrial structures lacking standardized computer-aided design(CAD)models or in instances of deformation.Inspired by the multidimensional observation of humans,our study introduces a universal image acquisition paradigm tailored for robotics,seamlessly integrating multi-objective optimization trajectory planning and control scheme to harness measured point clouds for versatile,efficient,and highly accurate image acquisition across diverse structures and scenarios.Specifically,we introduce an energybased adaptive trajectory optimization(EBATO)method that combines deformation and deviation with dual-threshold optimization and adaptive weight adjustment to improve the smoothness and accuracy of imaging trajectory and posture.Additionally,a multi-optimization control scheme based on a meta-heuristic beetle antennal olfactory recurrent neural network(BAORNN)is proposed to track the imaging trajectory while addressing posture,obstacle avoidance,and physical constraints in industrial scenarios.Simulations,real-world experiments,and comparisons demonstrate the effectiveness and practicality of the proposed paradigm.
基金supported by the National Natural Science Foundation of China (41271020, 41330746)CERS-China Equipment and Education Resources System (CERS-1-109)
文摘Although scientists have performed many studies in the Taklimakan Desert, few of them have reported the blown sand motion along the southern edge of the Taklimakan Desert Highway, which differs significantly from the northern region in terms of aeolian sand geomorphology and formation environment. Based on the field ob- servation data of airflow and aeolian sand transport, continuous monitoring data of erosional and depositional processes between 14 April 2009 and 9 April 2011 and data of surface sand grains from the classical section along the southern edge of the Taklimakan Desert Highway, this paper reported the blown sand motion within the sand-control system of the highway. The main results are as follows： 1） The existing sand-control system is highly effective in preventing and controlling desertification. Wind velocities within the sand-control system were ap- proximately 33%-100% of those for the same height above the mobile sand surface. Aeolian sand fluxes were approximately 0-31.21% of those of the mobile sand surface. Sand grains inside the system, with a mean diameter of 2.89 q）, were finer than those （2.15 q）） outside the system. In addition, wind velocities basically followed a loga- rithmic law, but the airflow along the classical section was mainly determined by topography and vegetation. 2） There were obvious erosional and depositional phenomena above the surface within the sand-control system, and these phenomena have very consistent patterns for all observation points in the two observed years. The total thicknesses of erosion and deposition ranged from 0.30 to 14.60 cm, with a mean value of 3.67 cm. In contrast, the deposition thicknesses were 1.90-22.10 cm, with a mean value of 7.59 cm, and the erosion thicknesses were 3.51-15.10 cm, with a mean value of 8.75 cm. The results will aid our understanding of blown sand within the sand-control system and provide a strong foundation for optimizing the sand-control system.
文摘This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method.In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.
基金Sponsored by the Multidiscipline Scientific Research Foundation of Harbin Institute of Technology(Grant No.HIT.MD2002.13).
文摘Magnetism parameters vary with the position and the speed of electromagnetic actuator's motion parts.The measurement unit presented in the paper can be applied to get the position and the speed feedback information from the measurement of electromagnetism parameters,and can constitute the untouched feedback sensing unit in the closed-loop motion control,and it adapts to the diversified feedback control of electromagnetic actuator.The digital miniaturization meter,based on MSP430 single chip processor,which can do the multi-purpose measurement of Φ & B through the menu selection,can be used for the electromagnetic actuator's performance evaluation and improvement,and also the online quality control in production process.Both real-time data graph and data table can be displayed in the meter.The paper presents the system's structure,describes the principle,discusses the working modes,and shows the software flowchart and the measuring results.
文摘To develop a control system of cantilever arm for barrels welding, a motion controller has been developed to fit the welding procedure. The main research fields of the controller are: (1) finding effective measures to protect the controller against interferences; (2) decreasing welding current gradually in order to alleviate arc craters which are harmful to seam forming and welding quality; (3) planning the arm velocity to minimize the influence of the arm swing on arc length regulator; (4) adopting adaptive control algorithm with PD feedback and velocity feed-forward to reduce the influence of system inertia and velocity planning on the system transient performance.
基金supported by the National Natural Science Foundation of China(No.62273117)Pre-research Task(No.SKLRS202418B)of State Key Laboratory of Robotics and Systems(HIT).
文摘Bio-inspired magnetic helical microrobots have great potential for biomedical and micromanipulation applications. Precise interaction with objects in liquid environments is an important prerequisite and challenge for helical microrobots to perform various tasks. In this study, an automatic control method is proposed to realize the axial docking of helical microrobots with arbitrarily placed cylindrical objects in liquid environments. The docking process is divided into ascent, approach, alignment, and insertion stages. First, a 3D docking path is planned according to the positions and orientations of the microrobot and the target object. Second, a steering-based 3D path-following controller guides the helical microrobot to rise away from the container bottom and approach the target along the path. Third, based on path design with gravity compensation and steering output limits, alignment of position and orientation can be accomplished simultaneously. Finally, the helical microrobot completes the docking under the rotating magnetic field along the target orientation. Experiments verified the automatic docking of the helical microrobot with static targets, including connecting with micro-shafts and inserting into micro-tubes. The object grasping of a reconfigurable helical microrobot aided by 3D automatic docking was also demonstrated. This method enables precise docking of helical microrobots with objects, which might be used for capture and sampling, in vivo navigation control, and functional assembly of microrobots.
基金supported by National Natural Science Foundation of China(52375530,52075132)Natural Science Foundation of Heilongjiang Province(YQ2022E025)+4 种基金State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment(Guangdong University of Technology)(JMDZ202312)Fundamental Research Funds for the Central Universities(HIT.OCEF.2024034)China Postdoctoral Science Foundation(2019M651278,2020T130155)Heilongjiang Province Postdoctoral Science Foundation(LBH-Z19066)Space Drive and Manipulation Mechanism Laboratory of BICE and National Key Laboratory of Space Intelligent Control,No BICE-SDMM-2024-01
文摘The increasingly stringent performance requirement in integrated circuit manufacturing, characterized by smaller feature sizes and higher productivity, necessitates the wafer stage executing a extreme motion with the accuracy in terms of nanometers. This demanding requirement witnesses a widespread application of iterative learning control(ILC), given the repetitive nature of wafer scanning. ILC enables substantial performance improvement by using past measurement data in combination with the system model knowledge. However, challenges arise in cases where the data is contaminated by the stochastic noise, or when the system model exhibits significant uncertainties, constraining the achievable performance. In response to this issue, an extended state observer(ESO) based adaptive ILC approach is proposed in the frequency domain.Despite being model-based, it utilizes only a rough system model and then compensates for the resulting model uncertainties using an ESO, thereby achieving high robustness against uncertainties with minimal modeling effort. Additionally, an adaptive learning law is developed to mitigate the limited performance in the presence of stochastic noise, yielding high convergence accuracy yet without compromising convergence speed. Simulation and experimental comparisons with existing model-based and data-driven inversion-based ILC validate the effectiveness as well as the superiority of the proposed method.
基金supported in part by the National Natural Science Foundationof China under Grant(61801122)Natural Science Foundation of FujianProvince(2022J01542).
文摘The wheeled bipedal robots have great application potential in environments with a mixture of structured and unstructured terrain. However, wheeled bipedal robots have problems such as poor balance ability and low movement level on rough roads. In this paper, a novel and low-cost wheeled bipedal robot with an asymmetrical five-link mechanism is proposed, and the kinematics of the legs and the dynamics of the Wheeled Inverted Pendulum (WIP) are modeled. The primary balance controller of the wheeled bipedal robot is built based on the Linear Quadratic Regulator (LQR) and the compensation method of the virtual pitch angle adjusting the Center of Mass (CoM) position, then the whole-body hybrid torque-position control is established by combining attitude and leg controllers. The stability of the robot’s attitude control and motion is verified with simulations and prototype experiments, which confirm the robot’s ability to pass through complex terrain and resist external interference. The feasibility and reliability of the proposed control model are verified.
