A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed env...A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.展开更多
Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained i...Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained interactive robot.Considering the elastic interaction force model,a mechanical trade-off always exists between the interaction force and position,which means that neither force nor path following can satisfy their desired demands completely.Based on this consideration,two irreconcilable control specifications,the force object function and the position track object function,are proposed,and a new multi-objective MPC scheme is then designed.展开更多
Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under dir...Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.展开更多
A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraint...A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraints.First,an NN is used to fit the motion data of robot manipulators for data-driven dynamic modeling,converting it into a linear prediction model through gradients.Then,by statistically analyzing the stochastic characteristics of the NN modeling errors,a distributionally robust model predictive controller is designed based on the chance constraints,and the optimization problem is transformed into a tractable quadratic programming(QP)problem under the distributionally robust optimization(DRO)framework.The recursive feasibility and convergence of the proposed algorithm are proven.Finally,the effectiveness of the proposed algorithm is verified through numerical simulation.展开更多
Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging comp...Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation.展开更多
Model predictive control(MPC)is a model-based optimal control strategy widely used in robot systems.In this work,the MPC controller tuning problem for the path tracking of the wheeled mobile robot is studied and a nov...Model predictive control(MPC)is a model-based optimal control strategy widely used in robot systems.In this work,the MPC controller tuning problem for the path tracking of the wheeled mobile robot is studied and a novel self-tuning approach is developed.First,two novel path tracking performance indices,i.e.,steadystate time ratio and steady-state distance ratio are proposed to more accurately reflect the control performance.Second,the mapping relationship between the proposed indices and the MPC parameters is established based on machine learning technique,and then a novel controller structure which can automatically tune the control parameters online is further designed.Finally,experimental verification with an actual wheeled mobile robot is conducted,which shows that the proposed method could outperform the existing method via achieving significant improvement in the rapidity,accuracy and adaptability of the robot path tracking.展开更多
Based on the Newton-Euler method, the dynamic behaviors of the left and right driving wheels and the robot body for the welding mobile robot were derived. In order to realize the combination control of body turning an...Based on the Newton-Euler method, the dynamic behaviors of the left and right driving wheels and the robot body for the welding mobile robot were derived. In order to realize the combination control of body turning and slider adjustment, the dynamic behaviors of sliders were also investigated. As a result, a systematic and complete dynamic model for the welding mobile robot was constructed. In order to verify the effectiveness of the above model, a sliding mode tracking control method was proposed and simulated, the lateral error stabilizes between -0.2 mm and ＋0.2 mm, and the total distance of travel for the slider is consistently within 4-2 ram. The simulation results verify the effectiveness of the established dynamic model and also show that the seam tracking controller based on the dynamic model has excellent performance in terms of stability and robustness. Furthermore, the model is found to be very suitable for practical applications of the welding mobile robot.展开更多
A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning...A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning between angular velocity and linear velocity.In the processing of pivot turning,the slippage parameters could be obtained by measuring the end point in a square path.In the process of coupled turning,the slippage parameters could be calculated by measuring the perimeter of a circular path and the linear distance between the start and end points.The identification results showed that slippage parameters were affected by velocity.Therefore,a fuzzy rule base was established with the basis on the identification data,and a fuzzy controller was applied to motion control and dead reckoning.This method effectively compensated for errors resulting in unequal tension between the left and right tracks,structural dimensions and slippage.The results demonstrated that the accuracy of robot positioning and control could be substantially improved on a rigid floor.展开更多
Enhancing the motion performance of wheeled biped robots amidst uncertain disturbances remains a challenge due to their under-actuated and inherently unstable nature.Aiming to address this issue,this paper proposes a ...Enhancing the motion performance of wheeled biped robots amidst uncertain disturbances remains a challenge due to their under-actuated and inherently unstable nature.Aiming to address this issue,this paper proposes a disturbance adaptive control framework for such robots.The framework introduces a disturbance variable to describe the comprehensive effect of disturbances due to environmental interactions on the robotic system.A Kalman filter is also employed to estimate the robot’s center of mass(CoM)state and the uncertain disturbances by leveraging the dynamic coupling intrinsic to the robots.Estimated results are then integrated into a nominal model predictive control framework to generate an optimal CoM trajectory over a finite time horizon.This approach enables the robot to adapt to various types of external disturbances in the sagittal plane while maintaining accurate velocity tracking.The efficacy of the proposed approach is validated by conducting experimental evaluations on a hydraulically driven wheeled biped robot.展开更多
This paper discusses the path planning and path following control problems of robotic fish.In order to avoid obstacles when robotic fish swim in a complex environment,a path plan-ning method based on beetle swarm opti...This paper discusses the path planning and path following control problems of robotic fish.In order to avoid obstacles when robotic fish swim in a complex environment,a path plan-ning method based on beetle swarm optimization(BSO)algorithm is developed.This method considers the influence of the robotic fish’s volume and motion constraints on the path planning task,which can eliminate the collision risk and meet the constraint of the minimum turning radius when the robotic fish obtains the planned path.In construct-ing the path following controller,a multilayer perception based model predictive control(MPC)is adopted to design the optimal control method,and the objective function of the optimal control is dynamically adjusted according to the path curvature.The simulation results show that this proposed method can effectively overcome the complexity of robotic fish kinematics modelling and adapt well to the reference paths of different curvatures given by the path planner.展开更多
This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical m...This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach.The nonlinear components of the model are compensated through nonlinear feedback linearization.Subsequently,a fuzzy-based regulator is employed to enhance the receding horizon opti-mization process for achieving optimal results.A Deep Neural Network(DNN)is trained to address disturbances.Conse-quently,a novel hybrid controller incorporating Nonlinear Model Predictive Control(NMPC),the Fuzzy Regulator(FR),and Deep Neural Network Feedforward(DNNF),named NMPC-FRDNNF is developed.Finally,the efficacy of the control system is validated through simulations and experiments.The results indicate that the Root Mean Square Error(RMSE)of the controller with FR and DNNF decreases by 33.2 and 48.9%,respectively,compared to the controller without these enhancements.This research provides a theoretical foundation and practical insights for ensuring the future highly stable,safe,and efficient maintenance of blankets.展开更多
This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time d...This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time domain for the case of ideal network condition is first derived, and then the networked predictive controller as well as two algorithms for dealing with communication delay and consecutive data packet dropouts are proposed. Simulation and experimental results verify the realizability and effectiveness of the proposed algorithms.展开更多
This research formulates a path-following control problem subjected to wheel slippage and skid and solves it using a logic-based control scheme for a wheeled mobile robot （WMR）. The novelty of the proposed scheme li...This research formulates a path-following control problem subjected to wheel slippage and skid and solves it using a logic-based control scheme for a wheeled mobile robot （WMR）. The novelty of the proposed scheme lies in its methodology that considers both longitudinal and lateral slip components. Based on the derived slip model, the controller for longitudinal motion slip has been synthesized. Various control parameters have been studied to investigate their effects on the performance of the controller resulting in selection of their optimum values. The designed controller for lateral slip or skid is based on the proposed side friction model and skid check condition. Considering a car-like WMR, simulation results demonstrate the effectiveness of the proposed control scheme. The robot successfully followed the desired circular trajectory in the presence of wheel slippage and skid. This research finds its potential in various applications involving WMR navigation and control.展开更多
The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper pre...The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved stability.展开更多
To address the limitations of traditional manual highway guardrail inspections,this paper proposes an obstacle-crossing and collaborative tracking control method for a rail-mounted robot.Static and dynamic analyses ve...To address the limitations of traditional manual highway guardrail inspections,this paper proposes an obstacle-crossing and collaborative tracking control method for a rail-mounted robot.Static and dynamic analyses verify the robot's structural reliability and driving feasibility.Based on the leader-follower model,a triangular collaborative tracking model is developed,and a linear time-varying model predictive controll(LTV-MPC)is designed to achieve smooth and precise collaborative control.For obstacle crossing,an acceleration reference model and a gradient-based adaptive law are proposed,leading to a model reference adaptive controll(MRAC)that effectively suppresses vibrations and ensures synchronous control.Simulation results show that the MPC achieves a 0.415%overshoot and a 0.344 m steady-state accuracy,while also reducing the intensity of speed fluctuations by 35%.The MRAC ensures smooth obstacle-crossing speeds and adaptive strategy switching,validating the reliability and practicality of the rail-mounted robot under complex working conditions.展开更多
Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion i...Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion in swimming,and provides additional support during terrestrial crawling.However,when the tail lifts off the ground during land crawling,its flexible underactuated structure tends to oscillate randomly due to minimal damping.These oscillations impart disruptive reaction torques to the body,critically impairing locomotion stability.To tackle this issue,we employed the standard Denavit-Hartenberg(DH)method and Newton-Euler equations to formulate a rigid-flexible coupled dynamic model for the tail,in which distributed elastic forces are embedded as internal forces in the force balance equations.Based on this model,we propose an oscillation suppression strategy based on an energy-optimized Nonlinear Model Predictive Controller(NMPC)with a single joint torque as the control input.This controller solves a constrained multi-objective optimization problem to effectively suppress the underactuated oscillations of the tail.Finally,experimental comparisons validate the accuracy of the dynamic model,and simulations based on this model substantiate the effectiveness of the oscillation suppression strategy.展开更多
Considering the wheeled mobile robot(WMR)tracking problem with velocity saturation,we developed a data‐driven iterative learning double loop control method with constraints.First,the authors designed an outer loop co...Considering the wheeled mobile robot(WMR)tracking problem with velocity saturation,we developed a data‐driven iterative learning double loop control method with constraints.First,the authors designed an outer loop controller to provide virtual velocity for the inner loop according to the position and pose tracking error of the WMR kinematic model.Second,the authors employed dynamic linearisation to transform the dynamic model into an online data‐driven model along the iterative domain.Based on the measured input and output data of the dynamic model,the authors identified the parameters of the inner loop controller.The authors considered the velocity saturation constraints;we adjusted the output velocity of the WMR online,providing effective solutions to the problem of velocity saltation and the saturation constraint in the tracking process.Notably,the inner loop controller only uses the output data and input of the dynamic model,which not only enables the reliable control of WMR trajectory tracking,but also avoids the influence of inaccurate model identification processes on the tracking performance.The authors analysed the algorithm's convergence in theory,and the results show that the tracking errors of position,angle and velocity can converge to zero in the iterative domain.Finally,the authors used a simulation to demonstrate the effectiveness of the algorithm.展开更多
The complete dynamics model of a four-Mecanum-wheeled robot considering mass eccentricity and friction uncertainty is derived using the Lagrange’s equation. Then based on the dynamics model, a nonlinear stable adapti...The complete dynamics model of a four-Mecanum-wheeled robot considering mass eccentricity and friction uncertainty is derived using the Lagrange’s equation. Then based on the dynamics model, a nonlinear stable adaptive control law is derived using the backstepping method via Lyapunov stability theory. In order to compensate for the model uncertainty, a nonlinear damping term is included in the control law, and the parameter update law with σ-modification is considered for the uncertainty estimation. Computer simulations are conducted to illustrate the suggested control approach.展开更多
基金National Natural Science Foundation of China(Nos.62173303 and 62273307)Natural Science Foundation of Zhejiang Province(No.LQ24F030023)。
文摘A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.
基金supported by the National Natural Science Foundation of China(62303095)the Natural Science Foundation of Sichuan Province(2023NSFSC0872).
文摘Dear Editor,This letter proposes a novel Nash bargaining solution-based multiobjective model predictive control(MPC)scheme to deal with the interaction force control and the path-following problem of the constrained interactive robot.Considering the elastic interaction force model,a mechanical trade-off always exists between the interaction force and position,which means that neither force nor path following can satisfy their desired demands completely.Based on this consideration,two irreconcilable control specifications,the force object function and the position track object function,are proposed,and a new multi-objective MPC scheme is then designed.
基金supported by the National Natural Science Foundation of China(62073113,62003122,62303148)the Fundamental Research Funds for the Central Universities(MCCSE2023A01,JZ2023HGTA0201,JZ2023HGQA0109)the Anhui Provincial Natural Science Foundation(2308085QF204)
文摘Dear Editor,This letter considers the formation control of multiple mobile robot systems(MMRS)that only relies on the local observation information.A new distributed finite-time observer is proposed for MMRS under directed graph to estimate the relative information between each follower robot and the leader robot.Then the formation control problem is transformed into the tracking problem and a finite-time tracking controller is proposed based on the robot model feature.
基金Project supported by the National Natural Science Foundation of China(Nos.62273245 and 62173033)the Sichuan Science and Technology Program of China(No.2024NSFSC1486)the Opening Project of Robotic Satellite Key Laboratory of Sichuan Province of China。
文摘A distributionally robust model predictive control(DRMPC)scheme is proposed based on neural network(NN)modeling to achieve the trajectory tracking control of robot manipulators with state and control torque constraints.First,an NN is used to fit the motion data of robot manipulators for data-driven dynamic modeling,converting it into a linear prediction model through gradients.Then,by statistically analyzing the stochastic characteristics of the NN modeling errors,a distributionally robust model predictive controller is designed based on the chance constraints,and the optimization problem is transformed into a tractable quadratic programming(QP)problem under the distributionally robust optimization(DRO)framework.The recursive feasibility and convergence of the proposed algorithm are proven.Finally,the effectiveness of the proposed algorithm is verified through numerical simulation.
文摘Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation.
基金the National Natural Science Foundation of China(No.61903291)the Key Research and Development Program of Shaanxi Province(No.2022NY-094)。
文摘Model predictive control(MPC)is a model-based optimal control strategy widely used in robot systems.In this work,the MPC controller tuning problem for the path tracking of the wheeled mobile robot is studied and a novel self-tuning approach is developed.First,two novel path tracking performance indices,i.e.,steadystate time ratio and steady-state distance ratio are proposed to more accurately reflect the control performance.Second,the mapping relationship between the proposed indices and the MPC parameters is established based on machine learning technique,and then a novel controller structure which can automatically tune the control parameters online is further designed.Finally,experimental verification with an actual wheeled mobile robot is conducted,which shows that the proposed method could outperform the existing method via achieving significant improvement in the rapidity,accuracy and adaptability of the robot path tracking.
基金Project(50605044) supported by the National Natural Science Foundation of China Project(2004DFA02400) supported by the Key International Science and Technology Cooperation Program
文摘Based on the Newton-Euler method, the dynamic behaviors of the left and right driving wheels and the robot body for the welding mobile robot were derived. In order to realize the combination control of body turning and slider adjustment, the dynamic behaviors of sliders were also investigated. As a result, a systematic and complete dynamic model for the welding mobile robot was constructed. In order to verify the effectiveness of the above model, a sliding mode tracking control method was proposed and simulated, the lateral error stabilizes between -0.2 mm and ＋0.2 mm, and the total distance of travel for the slider is consistently within 4-2 ram. The simulation results verify the effectiveness of the established dynamic model and also show that the seam tracking controller based on the dynamic model has excellent performance in terms of stability and robustness. Furthermore, the model is found to be very suitable for practical applications of the welding mobile robot.
文摘A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning between angular velocity and linear velocity.In the processing of pivot turning,the slippage parameters could be obtained by measuring the end point in a square path.In the process of coupled turning,the slippage parameters could be calculated by measuring the perimeter of a circular path and the linear distance between the start and end points.The identification results showed that slippage parameters were affected by velocity.Therefore,a fuzzy rule base was established with the basis on the identification data,and a fuzzy controller was applied to motion control and dead reckoning.This method effectively compensated for errors resulting in unequal tension between the left and right tracks,structural dimensions and slippage.The results demonstrated that the accuracy of robot positioning and control could be substantially improved on a rigid floor.
基金supported by the National Natural Science Foundation of China(Grant No.52405059)Heilongjiang Province Young Science and Technology Talent Lifting Project(Grant No.2023QNTJ008)+1 种基金the Natural Science Foundation of Heilongjiang Province of China(Grant No.YQ2024E017)Self-Planned Task of State Key Laboratory of Robotics and System(Harbin Institute of Technology,China)(Grant No.SKLRS202401C).
文摘Enhancing the motion performance of wheeled biped robots amidst uncertain disturbances remains a challenge due to their under-actuated and inherently unstable nature.Aiming to address this issue,this paper proposes a disturbance adaptive control framework for such robots.The framework introduces a disturbance variable to describe the comprehensive effect of disturbances due to environmental interactions on the robotic system.A Kalman filter is also employed to estimate the robot’s center of mass(CoM)state and the uncertain disturbances by leveraging the dynamic coupling intrinsic to the robots.Estimated results are then integrated into a nominal model predictive control framework to generate an optimal CoM trajectory over a finite time horizon.This approach enables the robot to adapt to various types of external disturbances in the sagittal plane while maintaining accurate velocity tracking.The efficacy of the proposed approach is validated by conducting experimental evaluations on a hydraulically driven wheeled biped robot.
基金This work was supported in part by the National Natural Science Foundation of China under Grant 61903007in part by the National Key Research and Development Program of China under Grant 2019YFD0901000.
文摘This paper discusses the path planning and path following control problems of robotic fish.In order to avoid obstacles when robotic fish swim in a complex environment,a path plan-ning method based on beetle swarm optimization(BSO)algorithm is developed.This method considers the influence of the robotic fish’s volume and motion constraints on the path planning task,which can eliminate the collision risk and meet the constraint of the minimum turning radius when the robotic fish obtains the planned path.In construct-ing the path following controller,a multilayer perception based model predictive control(MPC)is adopted to design the optimal control method,and the objective function of the optimal control is dynamically adjusted according to the path curvature.The simulation results show that this proposed method can effectively overcome the complexity of robotic fish kinematics modelling and adapt well to the reference paths of different curvatures given by the path planner.
基金supported by Comprehensive Research Facility for Fusion Technology Program of China under Contract No.2018-000052-73-01-001228the China Scholarship Council with No.202206340050National Natural Science Foundation of China with Grant No.11905147.
文摘This paper investigates the motion control of the heavy-duty Bionic Caterpillar-like Robot(BCR)for the maintenance of the China Fusion Engineering Test Reactor(CFETR).Initially,a comprehensive nonlinear mathematical model for the BCR system is formulated using a physics-based approach.The nonlinear components of the model are compensated through nonlinear feedback linearization.Subsequently,a fuzzy-based regulator is employed to enhance the receding horizon opti-mization process for achieving optimal results.A Deep Neural Network(DNN)is trained to address disturbances.Conse-quently,a novel hybrid controller incorporating Nonlinear Model Predictive Control(NMPC),the Fuzzy Regulator(FR),and Deep Neural Network Feedforward(DNNF),named NMPC-FRDNNF is developed.Finally,the efficacy of the control system is validated through simulations and experiments.The results indicate that the Root Mean Square Error(RMSE)of the controller with FR and DNNF decreases by 33.2 and 48.9%,respectively,compared to the controller without these enhancements.This research provides a theoretical foundation and practical insights for ensuring the future highly stable,safe,and efficient maintenance of blankets.
基金supported in part by the National Natural Science Foundation of China under Grant Nos.61333033,61690210 and 61690212
文摘This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time domain for the case of ideal network condition is first derived, and then the networked predictive controller as well as two algorithms for dealing with communication delay and consecutive data packet dropouts are proposed. Simulation and experimental results verify the realizability and effectiveness of the proposed algorithms.
基金Project supported by the European Commission under the Erasmus Mundus Master Program
文摘This research formulates a path-following control problem subjected to wheel slippage and skid and solves it using a logic-based control scheme for a wheeled mobile robot （WMR）. The novelty of the proposed scheme lies in its methodology that considers both longitudinal and lateral slip components. Based on the derived slip model, the controller for longitudinal motion slip has been synthesized. Various control parameters have been studied to investigate their effects on the performance of the controller resulting in selection of their optimum values. The designed controller for lateral slip or skid is based on the proposed side friction model and skid check condition. Considering a car-like WMR, simulation results demonstrate the effectiveness of the proposed control scheme. The robot successfully followed the desired circular trajectory in the presence of wheel slippage and skid. This research finds its potential in various applications involving WMR navigation and control.
基金supported in part by the National Natural Science Foundation of China under Grant 52575004the Beijing Natural Science Foundation under Grant L243004the National Natural Science Foundation of China under Grant 62403060.
文摘The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved stability.
基金Supported by the Shaanxi Provincial Key Research and Development Program(2024GX-YBXM-288)the Science and Technology Project of Shaanxi Provincial Transportation Department(21-20K)the National Natural Science Foundation of China(52172324)。
文摘To address the limitations of traditional manual highway guardrail inspections,this paper proposes an obstacle-crossing and collaborative tracking control method for a rail-mounted robot.Static and dynamic analyses verify the robot's structural reliability and driving feasibility.Based on the leader-follower model,a triangular collaborative tracking model is developed,and a linear time-varying model predictive controll(LTV-MPC)is designed to achieve smooth and precise collaborative control.For obstacle crossing,an acceleration reference model and a gradient-based adaptive law are proposed,leading to a model reference adaptive controll(MRAC)that effectively suppresses vibrations and ensures synchronous control.Simulation results show that the MPC achieves a 0.415%overshoot and a 0.344 m steady-state accuracy,while also reducing the intensity of speed fluctuations by 35%.The MRAC ensures smooth obstacle-crossing speeds and adaptive strategy switching,validating the reliability and practicality of the rail-mounted robot under complex working conditions.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFB3213600).
文摘Inspired by the crucial role of the tail in crocodile locomotion,we propose a novel rigid-flexible coupled tail structure design.The tail design reduces the number of required actuators,enables undulatory propulsion in swimming,and provides additional support during terrestrial crawling.However,when the tail lifts off the ground during land crawling,its flexible underactuated structure tends to oscillate randomly due to minimal damping.These oscillations impart disruptive reaction torques to the body,critically impairing locomotion stability.To tackle this issue,we employed the standard Denavit-Hartenberg(DH)method and Newton-Euler equations to formulate a rigid-flexible coupled dynamic model for the tail,in which distributed elastic forces are embedded as internal forces in the force balance equations.Based on this model,we propose an oscillation suppression strategy based on an energy-optimized Nonlinear Model Predictive Controller(NMPC)with a single joint torque as the control input.This controller solves a constrained multi-objective optimization problem to effectively suppress the underactuated oscillations of the tail.Finally,experimental comparisons validate the accuracy of the dynamic model,and simulations based on this model substantiate the effectiveness of the oscillation suppression strategy.
基金supported by the Innovation Project of Guangxi Graduate Education(Grant No.YCSW2022436).
文摘Considering the wheeled mobile robot(WMR)tracking problem with velocity saturation,we developed a data‐driven iterative learning double loop control method with constraints.First,the authors designed an outer loop controller to provide virtual velocity for the inner loop according to the position and pose tracking error of the WMR kinematic model.Second,the authors employed dynamic linearisation to transform the dynamic model into an online data‐driven model along the iterative domain.Based on the measured input and output data of the dynamic model,the authors identified the parameters of the inner loop controller.The authors considered the velocity saturation constraints;we adjusted the output velocity of the WMR online,providing effective solutions to the problem of velocity saltation and the saturation constraint in the tracking process.Notably,the inner loop controller only uses the output data and input of the dynamic model,which not only enables the reliable control of WMR trajectory tracking,but also avoids the influence of inaccurate model identification processes on the tracking performance.The authors analysed the algorithm's convergence in theory,and the results show that the tracking errors of position,angle and velocity can converge to zero in the iterative domain.Finally,the authors used a simulation to demonstrate the effectiveness of the algorithm.
文摘The complete dynamics model of a four-Mecanum-wheeled robot considering mass eccentricity and friction uncertainty is derived using the Lagrange’s equation. Then based on the dynamics model, a nonlinear stable adaptive control law is derived using the backstepping method via Lyapunov stability theory. In order to compensate for the model uncertainty, a nonlinear damping term is included in the control law, and the parameter update law with σ-modification is considered for the uncertainty estimation. Computer simulations are conducted to illustrate the suggested control approach.
