The robust control problem for a class of underactuated mechanical systems called acrobots is addressed. The goal is to drive the acrobots away from the straight-down position and balance them at the straight-up unsta...The robust control problem for a class of underactuated mechanical systems called acrobots is addressed. The goal is to drive the acrobots away from the straight-down position and balance them at the straight-up unstable equilibrium position in the presence of parametric uncertainties and external disturbance. First, in the swing-up area, it is shown that the time derivative of energy is independent of the parameter uncertainties, but exogenous disturbance may destroy the characteristic of increase in mechanical energy. So, a swing-up controller with compensator is designed to suppress the influence of the disturbance. Then, in the attractive area, the control problem is formulated into a H~ control framework by introducing a proper error signal, and a sufficient condition of the existence of Hoo state feedback control law based on linear matrix inequality （LMI） is proposed to guarantee the quadratic stability of the control system. Finally, the simulation results show that the proposed control approach can simultaneously handle a maximum ±10% parameter perturbation and a big disturbance simultaneously.展开更多
Quadrotor unmanned aerial vehicles have become the most commonly used flying robots with wide applications in recent years.This paper presents a bioinspired control strategy by integrating the backstepping sliding mod...Quadrotor unmanned aerial vehicles have become the most commonly used flying robots with wide applications in recent years.This paper presents a bioinspired control strategy by integrating the backstepping sliding mode control technique and a bioinspired neural dynamics model.The effects of both disturbances and system and measurement noises on the quadrotor unmanned aerial vehicle control performance have been addressed in this paper.The proposed control strategy is robust against disturbances with guaranteed stability proven by the Lyapunov stability theory.In addition,the proposed control strategy is capable of providing smooth control inputs under noises.Considering the modeling uncertainties,the adaptive sliding innovation filter is integrated with the proposed control to provide accurate state estimates to improve tracking effectiveness.Finally,the simulation results demonstrate that the proposed control strategy provides satisfactory tracking performance for a quadrotor unmanned vehicle operating under disturbances and noises.展开更多
There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles(AUVs) is proposed for a three-dimensi...There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles(AUVs) is proposed for a three-dimensional underwater workspace in the ocean current. Each AUV in the model will be competed, and the shortest path under an ocean current and different azimuths will be selected for task assignment and path planning while guaranteeing the least total consumption. First, the initial position and orientation of each AUV are determined. The velocity and azimuths of the constant ocean current are determined. Then the AUV task assignment problem in the constant ocean current environment is considered. The AUV that has the shortest path is selected for task assignment and path planning. Finally, to prove the effectiveness of the proposed method, simulation results are given.展开更多
Tracking control has been a vital research topic in robotics.This paper presents a novel hybrid control strategy for an unmanned underwater vehicle(UUV)based on a bio-inspired neural dynamics model.An enhanced backste...Tracking control has been a vital research topic in robotics.This paper presents a novel hybrid control strategy for an unmanned underwater vehicle(UUV)based on a bio-inspired neural dynamics model.An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods.Then,a novel sliding mode control is proposed,which is capable of providing smooth and continuous torque commands free from chattering.In comparative studies,the proposed combined hybrid control strategy has ensured control signal smoothness,which is critical in real‐world applications,especially for a UUV that needs to operate in complex underwater environments.展开更多
基金Projects(61074112,60674044) supported by the National Natural Science Foundation of China
文摘The robust control problem for a class of underactuated mechanical systems called acrobots is addressed. The goal is to drive the acrobots away from the straight-down position and balance them at the straight-up unstable equilibrium position in the presence of parametric uncertainties and external disturbance. First, in the swing-up area, it is shown that the time derivative of energy is independent of the parameter uncertainties, but exogenous disturbance may destroy the characteristic of increase in mechanical energy. So, a swing-up controller with compensator is designed to suppress the influence of the disturbance. Then, in the attractive area, the control problem is formulated into a H~ control framework by introducing a proper error signal, and a sufficient condition of the existence of Hoo state feedback control law based on linear matrix inequality （LMI） is proposed to guarantee the quadratic stability of the control system. Finally, the simulation results show that the proposed control approach can simultaneously handle a maximum ±10% parameter perturbation and a big disturbance simultaneously.
文摘Quadrotor unmanned aerial vehicles have become the most commonly used flying robots with wide applications in recent years.This paper presents a bioinspired control strategy by integrating the backstepping sliding mode control technique and a bioinspired neural dynamics model.The effects of both disturbances and system and measurement noises on the quadrotor unmanned aerial vehicle control performance have been addressed in this paper.The proposed control strategy is robust against disturbances with guaranteed stability proven by the Lyapunov stability theory.In addition,the proposed control strategy is capable of providing smooth control inputs under noises.Considering the modeling uncertainties,the adaptive sliding innovation filter is integrated with the proposed control to provide accurate state estimates to improve tracking effectiveness.Finally,the simulation results demonstrate that the proposed control strategy provides satisfactory tracking performance for a quadrotor unmanned vehicle operating under disturbances and noises.
基金Project supported by the National Natural Science Foundation of China(Nos.U1706224,91748117,and 51575336)the Creative Activity Plan for Science and Technology Commission of Shanghai,China(Nos.18JC1413000,18DZ1206305,and 16550720200)
文摘There is an ocean current in the actual underwater working environment. An improved self-organizing neural network task allocation model of multiple autonomous underwater vehicles(AUVs) is proposed for a three-dimensional underwater workspace in the ocean current. Each AUV in the model will be competed, and the shortest path under an ocean current and different azimuths will be selected for task assignment and path planning while guaranteeing the least total consumption. First, the initial position and orientation of each AUV are determined. The velocity and azimuths of the constant ocean current are determined. Then the AUV task assignment problem in the constant ocean current environment is considered. The AUV that has the shortest path is selected for task assignment and path planning. Finally, to prove the effectiveness of the proposed method, simulation results are given.
基金This work is supported by the Advanced Robotic Intelligent Systems Laboratory at the University of Guelph under Natural Sciences and Engineering Research Council of Canada(NSERC).
文摘Tracking control has been a vital research topic in robotics.This paper presents a novel hybrid control strategy for an unmanned underwater vehicle(UUV)based on a bio-inspired neural dynamics model.An enhanced backstepping kinematic control strategy is first developed to avoid sharp velocity jumps and provides smooth velocity commands relative to conventional methods.Then,a novel sliding mode control is proposed,which is capable of providing smooth and continuous torque commands free from chattering.In comparative studies,the proposed combined hybrid control strategy has ensured control signal smoothness,which is critical in real‐world applications,especially for a UUV that needs to operate in complex underwater environments.
