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
This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in tradition...This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in traditional feedback control,to the domain of motion planning for autonomous vehicles.Thus,closed-loop system uncertainty can be preemptively addressed during vehicle motion planning.This involves selecting collision-free trajectories to minimize the volume of robust invariant tubes.Furthermore,constraints on state and control variables are translated into constraints on the RCI tubes of the closed-loop system,ensuring that motion planning produces a safe and optimal trajectory while maintaining flexibility,rather than solely optimizing for the open-loop nominal model.Additionally,to expedite the solving process,we were inspired by L2gain to parameterize the RCI tubes and developed a parameterized explicit iterative expression for propagating ellipsoidal uncertainty sets within closedloop systems.Furthermore,we applied the pseudospectral orthogonal collocation method to parameterize the optimization problem of transcribing trajectories using high-order Lagrangian polynomials.Finally,under various operating conditions,we incorporate both the kinematic and dynamic models of the vehicle and also conduct simulations and analyses of uncertainties such as heading angle measurement,chassis response,and steering hysteresis.Our proposed robust motion planning framework has been validated to effectively address nearly all bounded uncertainties while anticipating potential tracking errors in control during the planning phase.This ensures fast,closed-loop safety and robustness in vehicle motion planning.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
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
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
The prediction and compensation control of marine ship motion is crucial for ensuring the safety of offshore wind turbine loading and unloading operations.However,the accuracy of prediction and control is significantl...The prediction and compensation control of marine ship motion is crucial for ensuring the safety of offshore wind turbine loading and unloading operations.However,the accuracy of prediction and control is significantly affected by the hysteresis phenomenon in the wave compensation system.To address this issue,a ship heave motion prediction is proposed in this paper on the basis of the Gauss-DeepAR(AR stands for autoregressive recurrent)model and the Hilbert−Huang time-delay compensation control strategy.Initially,the zero upward traveling wave period of the level 4−6 sea state ship heave motion is analyzed,which serves as the input sliding window for the Gauss-DeepAR prediction model,and probability predictions at different wave direction angles are conducted.Next,considering the hysteresis characteristics of the ship heave motion compensation platform,the Hilbert−Huang transform is employed to analyze and calculate the hysteresis delay of the compensation platform.After the optimal control action value is subsequently calculated,simulations and hardware platform tests are conducted.The simulation results demonstrated that the Gauss-DeepAR model outperforms autoregressive integrated moving average model(ARIMA),support vector machine(SVM),and longshort-term memory(LSTM)in predicting non-independent identically distributed datasets at a 90°wave direction angle in the level 4−6 sea states.Furthermore,the model has good predictive performance and generalizability for non-independent and non-uniformly distributed datasets at a 180°wave direction angle.The hardware platform compensation test results revealed that the Hilbert–Huang method has an outstanding effect on determining the hysteretic delay and selecting the optimal control action value,and the compensation efficiency was higher than 90%in the level 4−6 sea states.展开更多
The maneuverability and stealth of aerial-aquatic vehicles(AAVs)is of significant importance for future integrated air-sea combat missions.To improve the maneuverability and stealth of AAVs near the water surface,this...The maneuverability and stealth of aerial-aquatic vehicles(AAVs)is of significant importance for future integrated air-sea combat missions.To improve the maneuverability and stealth of AAVs near the water surface,this paper proposed a high-maneuverability skipping motion strategy for the tandem twin-rotor AAV,inspired by the motion behavior of the flying fish to avoid aquatic and aerial predators near the water surface.The novel tandem twin-rotor AAV was employed as the research subject and a strategybased ADRC control method for validation,comparing it with a strategy-based PID control method.The results indicate that both control methods enable the designed AAV to achieve high stealth and maneuverability near the water surface with robust control stability.The strategy-based ADRC control method exhibits a certain advantage in controlling height,pitch angle,and reducing impact force.This motion strategy will offer an inspiring approach for the practical application of AAVs to some extent.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
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
Electronic line-shafting （ELS） is the most popular control strategy for printing machines with shaftless drives. A sliding-mode controller for tracking control is designed in this study as the first step towards an ...Electronic line-shafting （ELS） is the most popular control strategy for printing machines with shaftless drives. A sliding-mode controller for tracking control is designed in this study as the first step towards an improved ELS control scheme. This controller can eliminate the negative effects on synchronization precision resulting from the friction at low speed present in the pre-registration step of a shaftless driven printing machine. Moreover, it can eliminate the synchronization error of the printing process resulting from nonlinearities and load disturbances. Based on observer techniques, the unknown components of load torque and system parameter variations are estimated. On this basis, a novel ELS control method using equivalent load-torque observers is proposed. Experimental results demonstrate the effectiveness of the proposed control system for four-axis position control.展开更多
The position synchronization control(PSC) problem is studied for networked multi-axis servo systems(NMASSs) with time-varying delay that is smaller than one sampling period. To improve the control performance of the s...The position synchronization control(PSC) problem is studied for networked multi-axis servo systems(NMASSs) with time-varying delay that is smaller than one sampling period. To improve the control performance of the system, time-varying delays, modeling uncertainties, and external disturbances are first modeled as a lumped disturbance. Then, a linear extended state observer(LESO) is devised to estimate the system state and the lumped disturbance, and a linear feedback controller with disturbance compensation is designed to perform individual-axis tracking control. After that, a cross-coupled control approach is used to further improve synchronization performance. The bounded-input-bounded-output(BIBO) stability of the closedloop control system is analyzed. Finally, both simulation and experiment are carried out to demonstrate the effectiveness of the proposed method.展开更多
The existing research of the motion optimization of multi-axis machine tools is mainly based on geometric and kinematic constraints, which aim at obtaining minimum-time trajectories and finding obstacle-free paths. In...The existing research of the motion optimization of multi-axis machine tools is mainly based on geometric and kinematic constraints, which aim at obtaining minimum-time trajectories and finding obstacle-free paths. In motion optimization, the stiffness characteristics of the whole machining system, including machine tool and cutter, are not considered. The paper presents a new method to establish a general stiffness model of multi-axis machining system. An analytical stiffness model is established by Jacobi and point transformation matrix method. Based on the stiffness model, feed-direction stiffness index is calculated by the intersection of force ellipsoid and the cutting feed direction at the cutter tip. The stiffness index can help analyze the stiffness performance of the whole machining system in the available workspace. Based on the analysis of the stiffness performance, multi-axis motion optimization along tool paths is accomplished by mixed programming using Matlab and Visual C＋＋. The effectiveness of the motion optimization method is verified by the experimental research about the machining performance of a 7-axis 5-linkage machine tool. The proposed research showed that machining stability and production efficiency can be improved by multi-axis motion optimization based on the anisotropic force ellipsoid of the whole machining system.展开更多
The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the...The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the linear pendulum model is formulated over a predictive horizon by dimensional analysis.Through gait pattern conversion,the lateral-sequence walk and trot gaits of the quadruped can be regarded as unified biped gaits,allowing the dynamics of the linear inverted pendulum model to serve quadruped motion generation.In addition,a simple linearization of the center of pressure constraints for these quadruped gaits is developed for linear model predictive control problem.Furthermore,the motion generation problem can be solved online by quadratic programming with foothold adaptation.It is demonstrated that the proposed unified scheme can generate stable locomotion online for quadruped lateral-sequence walk and trot gaits,both in simulation and on hardware.The results show significant performance improvements compared to previous work.Moreover,the results also suggest the linearly simplified scheme has the ability to robustness against unexpected disturbances.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
Sloshing experiment is crucial to determine the reaction performance of regeneration columns on an offshore floating platform.A novel type of column motion simulating device and a Marine Predator Algorithm-based Slidi...Sloshing experiment is crucial to determine the reaction performance of regeneration columns on an offshore floating platform.A novel type of column motion simulating device and a Marine Predator Algorithm-based Sliding Mode Controller(MPA-SMC)are proposed for such sloshing experiments.The simulator consists of a Stewart platform and a steel framework.The Stewart platform is located at the column's center of gravity(CoG)and supported by the steel framework.The platform's hydraulic servo system is controlled by a sliding mode controller with parameters optimized by MPA to improve robustness and precision.A numerical sloshing experiment is conducted using the proposed device and controller.The results show that the novel motion simulator has lower torque during the column sloshes,and the proposed controller performs better than a well-tuned PID controller in terms of target tracking precision and anti-interference capability.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
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
Microrobots powered by an external magnetic field could be used for sophisticated medical applications such as cell treatment,micromanipulation,and noninvasive surgery inside the body.Untethered microrobot application...Microrobots powered by an external magnetic field could be used for sophisticated medical applications such as cell treatment,micromanipulation,and noninvasive surgery inside the body.Untethered microrobot applications can benefit from haptic technology and telecommunication,enabling telemedical micro-manipulation.Users can manipulate the microrobots with haptic feedback by interacting with the robot operating system remotely in such applications.Artificially created haptic forces based on wirelessly transmitted data and model-based guidance can aid human operators with haptic sensations while manipulating microrobots.The system presented here includes a haptic device and a magnetic tweezer system linked together using a network-based teleoperation method with motion models in fluids.The magnetic microrobots can be controlled remotely,and the haptic interactions with the remote environment can be felt in real time.A time-domain passivity controller is applied to overcome network delay and ensure stability of communication.This study develops and tests a motion model for microrobots and evaluates two image-based 3D tracking algorithms to improve tracking accuracy in various Newtonian fluids.Additionally,it demonstrates that microrobots can group together to transport multiple larger objects,move through microfluidic channels for detailed tasks,and use a novel method for disassembly,greatly expanding their range of use in microscale operations.Remote medical treatment in multiple locations,remote delivery of medication without the need for physical penetration of the skin,and remotely controlled cell manipulations are some of the possible uses of the proposed technology.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
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Supported by National Natural Science Foundation of China(Grant Nos.52025121,52394263)National Key R&D Plan of China(Grant No.2023YFD2000301)+2 种基金Foundation of State Key Laboratory of Automobile Safety and Energy Saving of China(Grant No.KFZ2201)the Jiangsu Provincial Scientific Research Center of Applied Mathematics under(Grant No.BK20233002)Special Fund of Jiangsu Province for the Transformation of Scientific and Technological Achievements under(Grant No.BA2021023)。
文摘This paper tackles uncertainties between planning and actual models.It extends the concept of RCI(robust control invariant)tubes,originally a parameterized representation of closed-loop control robustness in traditional feedback control,to the domain of motion planning for autonomous vehicles.Thus,closed-loop system uncertainty can be preemptively addressed during vehicle motion planning.This involves selecting collision-free trajectories to minimize the volume of robust invariant tubes.Furthermore,constraints on state and control variables are translated into constraints on the RCI tubes of the closed-loop system,ensuring that motion planning produces a safe and optimal trajectory while maintaining flexibility,rather than solely optimizing for the open-loop nominal model.Additionally,to expedite the solving process,we were inspired by L2gain to parameterize the RCI tubes and developed a parameterized explicit iterative expression for propagating ellipsoidal uncertainty sets within closedloop systems.Furthermore,we applied the pseudospectral orthogonal collocation method to parameterize the optimization problem of transcribing trajectories using high-order Lagrangian polynomials.Finally,under various operating conditions,we incorporate both the kinematic and dynamic models of the vehicle and also conduct simulations and analyses of uncertainties such as heading angle measurement,chassis response,and steering hysteresis.Our proposed robust motion planning framework has been validated to effectively address nearly all bounded uncertainties while anticipating potential tracking errors in control during the planning phase.This ensures fast,closed-loop safety and robustness in vehicle motion planning.
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 by the National Natural Science Foundation of China(Grant No.52105466).
文摘The prediction and compensation control of marine ship motion is crucial for ensuring the safety of offshore wind turbine loading and unloading operations.However,the accuracy of prediction and control is significantly affected by the hysteresis phenomenon in the wave compensation system.To address this issue,a ship heave motion prediction is proposed in this paper on the basis of the Gauss-DeepAR(AR stands for autoregressive recurrent)model and the Hilbert−Huang time-delay compensation control strategy.Initially,the zero upward traveling wave period of the level 4−6 sea state ship heave motion is analyzed,which serves as the input sliding window for the Gauss-DeepAR prediction model,and probability predictions at different wave direction angles are conducted.Next,considering the hysteresis characteristics of the ship heave motion compensation platform,the Hilbert−Huang transform is employed to analyze and calculate the hysteresis delay of the compensation platform.After the optimal control action value is subsequently calculated,simulations and hardware platform tests are conducted.The simulation results demonstrated that the Gauss-DeepAR model outperforms autoregressive integrated moving average model(ARIMA),support vector machine(SVM),and longshort-term memory(LSTM)in predicting non-independent identically distributed datasets at a 90°wave direction angle in the level 4−6 sea states.Furthermore,the model has good predictive performance and generalizability for non-independent and non-uniformly distributed datasets at a 180°wave direction angle.The hardware platform compensation test results revealed that the Hilbert–Huang method has an outstanding effect on determining the hysteretic delay and selecting the optimal control action value,and the compensation efficiency was higher than 90%in the level 4−6 sea states.
基金supported by Southern Marine Science and Guangdong Laboratory(Zhuhai)(Grant No.SML2023SP229)。
文摘The maneuverability and stealth of aerial-aquatic vehicles(AAVs)is of significant importance for future integrated air-sea combat missions.To improve the maneuverability and stealth of AAVs near the water surface,this paper proposed a high-maneuverability skipping motion strategy for the tandem twin-rotor AAV,inspired by the motion behavior of the flying fish to avoid aquatic and aerial predators near the water surface.The novel tandem twin-rotor AAV was employed as the research subject and a strategybased ADRC control method for validation,comparing it with a strategy-based PID control method.The results indicate that both control methods enable the designed AAV to achieve high stealth and maneuverability near the water surface with robust control stability.The strategy-based ADRC control method exhibits a certain advantage in controlling height,pitch angle,and reducing impact force.This motion strategy will offer an inspiring approach for the practical application of AAVs to some extent.
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supported by Natural Science Foundation of China(Nos.61773159 and 61473117)Hunan Provincial Natural Science Foundation of China(No.13JJ8020and 14JJ5024)Hunan Province Education Department(No.12A040)
文摘Electronic line-shafting （ELS） is the most popular control strategy for printing machines with shaftless drives. A sliding-mode controller for tracking control is designed in this study as the first step towards an improved ELS control scheme. This controller can eliminate the negative effects on synchronization precision resulting from the friction at low speed present in the pre-registration step of a shaftless driven printing machine. Moreover, it can eliminate the synchronization error of the printing process resulting from nonlinearities and load disturbances. Based on observer techniques, the unknown components of load torque and system parameter variations are estimated. On this basis, a novel ELS control method using equivalent load-torque observers is proposed. Experimental results demonstrate the effectiveness of the proposed control system for four-axis position control.
基金supported by the National Natural Science Foundation of China(NSFC)(61822311)the NSFC-Zhejiang Joint Fund for the Intergration of Industrialization and Informatization(U1709213)。
文摘The position synchronization control(PSC) problem is studied for networked multi-axis servo systems(NMASSs) with time-varying delay that is smaller than one sampling period. To improve the control performance of the system, time-varying delays, modeling uncertainties, and external disturbances are first modeled as a lumped disturbance. Then, a linear extended state observer(LESO) is devised to estimate the system state and the lumped disturbance, and a linear feedback controller with disturbance compensation is designed to perform individual-axis tracking control. After that, a cross-coupled control approach is used to further improve synchronization performance. The bounded-input-bounded-output(BIBO) stability of the closedloop control system is analyzed. Finally, both simulation and experiment are carried out to demonstrate the effectiveness of the proposed method.
基金supported by National Natural Science Foundation of China (Grant No. 51075168)National Basic Research Program of China (973 Program, Grant No. 2011CB706803)National Hi-tech Research and Development Program of China (863 Program, Grant No. 2009AA04Z149)
文摘The existing research of the motion optimization of multi-axis machine tools is mainly based on geometric and kinematic constraints, which aim at obtaining minimum-time trajectories and finding obstacle-free paths. In motion optimization, the stiffness characteristics of the whole machining system, including machine tool and cutter, are not considered. The paper presents a new method to establish a general stiffness model of multi-axis machining system. An analytical stiffness model is established by Jacobi and point transformation matrix method. Based on the stiffness model, feed-direction stiffness index is calculated by the intersection of force ellipsoid and the cutting feed direction at the cutter tip. The stiffness index can help analyze the stiffness performance of the whole machining system in the available workspace. Based on the analysis of the stiffness performance, multi-axis motion optimization along tool paths is accomplished by mixed programming using Matlab and Visual C＋＋. The effectiveness of the motion optimization method is verified by the experimental research about the machining performance of a 7-axis 5-linkage machine tool. The proposed research showed that machining stability and production efficiency can be improved by multi-axis motion optimization based on the anisotropic force ellipsoid of the whole machining system.
基金supported by the National Natural Science Foundation of China(Nos.52305072 and 52122503)Natural Science Foundation of Hebei Province of China(No.E2022203095)+2 种基金University-Industry Collaborative Education Program(No.220603936245709)Cultivation Project for Basic Research and Innovation of Yanshan University(No.2021LGQN004)henzhen Special Fund for Future Industrial Development(No.KJZD20230923114222045).
文摘The goal of this paper is to develop a unified online motion generation scheme for quadruped lateral-sequence walk and trot gaits based on a linear model predictive control formulation.Specifically,the dynamics of the linear pendulum model is formulated over a predictive horizon by dimensional analysis.Through gait pattern conversion,the lateral-sequence walk and trot gaits of the quadruped can be regarded as unified biped gaits,allowing the dynamics of the linear inverted pendulum model to serve quadruped motion generation.In addition,a simple linearization of the center of pressure constraints for these quadruped gaits is developed for linear model predictive control problem.Furthermore,the motion generation problem can be solved online by quadratic programming with foothold adaptation.It is demonstrated that the proposed unified scheme can generate stable locomotion online for quadruped lateral-sequence walk and trot gaits,both in simulation and on hardware.The results show significant performance improvements compared to previous work.Moreover,the results also suggest the linearly simplified scheme has the ability to robustness against unexpected disturbances.
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.
文摘Sloshing experiment is crucial to determine the reaction performance of regeneration columns on an offshore floating platform.A novel type of column motion simulating device and a Marine Predator Algorithm-based Sliding Mode Controller(MPA-SMC)are proposed for such sloshing experiments.The simulator consists of a Stewart platform and a steel framework.The Stewart platform is located at the column's center of gravity(CoG)and supported by the steel framework.The platform's hydraulic servo system is controlled by a sliding mode controller with parameters optimized by MPA to improve robustness and precision.A numerical sloshing experiment is conducted using the proposed device and controller.The results show that the novel motion simulator has lower torque during the column sloshes,and the proposed controller performs better than a well-tuned PID controller in terms of target tracking precision and anti-interference capability.
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 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 by National Science Foundation Grant No.2123824.
文摘Microrobots powered by an external magnetic field could be used for sophisticated medical applications such as cell treatment,micromanipulation,and noninvasive surgery inside the body.Untethered microrobot applications can benefit from haptic technology and telecommunication,enabling telemedical micro-manipulation.Users can manipulate the microrobots with haptic feedback by interacting with the robot operating system remotely in such applications.Artificially created haptic forces based on wirelessly transmitted data and model-based guidance can aid human operators with haptic sensations while manipulating microrobots.The system presented here includes a haptic device and a magnetic tweezer system linked together using a network-based teleoperation method with motion models in fluids.The magnetic microrobots can be controlled remotely,and the haptic interactions with the remote environment can be felt in real time.A time-domain passivity controller is applied to overcome network delay and ensure stability of communication.This study develops and tests a motion model for microrobots and evaluates two image-based 3D tracking algorithms to improve tracking accuracy in various Newtonian fluids.Additionally,it demonstrates that microrobots can group together to transport multiple larger objects,move through microfluidic channels for detailed tasks,and use a novel method for disassembly,greatly expanding their range of use in microscale operations.Remote medical treatment in multiple locations,remote delivery of medication without the need for physical penetration of the skin,and remotely controlled cell manipulations are some of the possible uses of the proposed technology.
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.
