In this paper, we propose an adaptive fuzzy dynamic surface control(DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal w...In this paper, we propose an adaptive fuzzy dynamic surface control(DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal with the difficulties associated with input saturation. An adaptive DSC design with an auxiliary first-order filter is used to solve the "explosion of complexity"problem. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The main advantage of the proposed method is that only one adaptation parameter needs to be updated,which reduces the computational burden significantly. Simulation results demonstrate the feasibility of the proposed scheme and the comparison results show that the improved DSC method can reduce the computational burden by almost two thirds in comparison with the standard DSC method.展开更多
On-orbit spacecraft face many threats,such as collisions with debris or other spacecraft.Therefore,perception of the surrounding space environment is vitally important for on-orbit spacecraft.Spacecraft require a dyna...On-orbit spacecraft face many threats,such as collisions with debris or other spacecraft.Therefore,perception of the surrounding space environment is vitally important for on-orbit spacecraft.Spacecraft require a dynamic attitude tracking ability with high precision for such missions.This paper aims to address the above problem using an improved backstepping controller.The tracking mission is divided into two phases:coarse alignment and fine alignment.In the first phase,a traditional saturation controller is utilized to limit the maximum attitude angular velocity according to the actuator’s ability.For the second phase,the proposed backstepping controller with different virtual control inputs is applied to track the moving target.To fulfill the high precision attitude tracking requirements,a hybrid attitude control actuator consisting of a Control Moment Gyro(CMG)and Reaction Wheel(RW)is constructed,which can simultaneously avoid the CMG singularity and RW saturation through the use of an angular momentum optimal management strategy,such as null motion.Finally,five simulation scenarios were carried out to demonstrate the effectiveness of the proposed control strategy and hybrid actuator.展开更多
In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from mo...In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network（NN）-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function（RBF） NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.展开更多
Automotive collision avoidance technology can effectively avoid the accidents caused by dangerous traffic conditions or driver's manipulation errors.Moreover,it can promote the development of autonomous driving fo...Automotive collision avoidance technology can effectively avoid the accidents caused by dangerous traffic conditions or driver's manipulation errors.Moreover,it can promote the development of autonomous driving for intelligent vehicle in intelligent transportation.We present a collision avoidance system,which is composed of an evasive trajectory planner and a path following controller.Considering the stability of the vehicle in the conflict-free process,the evasive trajectory planner is designed by polynomial parametric method and optimized by genetic algorithm.The path following controller is proposed to make the car drive along the designed path by controlling the vehicle's lateral movement.Simulation results show that the vehicle with the proposed controller has good stability in the collision process,and it can ensure the vehicle driving in accordance with the planned trajectory at different speeds.The research results can provide a certain basis for the research and development of automotive collision avoidance technology.展开更多
基金supported in part by the National Natural Science Foundation of China (61773051,61773072,61761166011)the Fundamental Research Fund for the Central Universities (2016RC021,2017JBZ003)
文摘In this paper, we propose an adaptive fuzzy dynamic surface control(DSC) scheme for single-link flexible-joint robotic systems with input saturation. A smooth function is utilized with the mean-value theorem to deal with the difficulties associated with input saturation. An adaptive DSC design with an auxiliary first-order filter is used to solve the "explosion of complexity"problem. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded, and the tracking error eventually converges to a small neighborhood around zero. The main advantage of the proposed method is that only one adaptation parameter needs to be updated,which reduces the computational burden significantly. Simulation results demonstrate the feasibility of the proposed scheme and the comparison results show that the improved DSC method can reduce the computational burden by almost two thirds in comparison with the standard DSC method.
基金the support provided by the National Natural Science Foundation of China(No.61973153)the National Key Research and Development Plan of China(No.2016YFB0500901)the Open Fund of the National Defense Key Discipline Laboratory of Micro-Spacecraft Technology of China(No.HIT.KLOF.MST.201705)
文摘On-orbit spacecraft face many threats,such as collisions with debris or other spacecraft.Therefore,perception of the surrounding space environment is vitally important for on-orbit spacecraft.Spacecraft require a dynamic attitude tracking ability with high precision for such missions.This paper aims to address the above problem using an improved backstepping controller.The tracking mission is divided into two phases:coarse alignment and fine alignment.In the first phase,a traditional saturation controller is utilized to limit the maximum attitude angular velocity according to the actuator’s ability.For the second phase,the proposed backstepping controller with different virtual control inputs is applied to track the moving target.To fulfill the high precision attitude tracking requirements,a hybrid attitude control actuator consisting of a Control Moment Gyro(CMG)and Reaction Wheel(RW)is constructed,which can simultaneously avoid the CMG singularity and RW saturation through the use of an angular momentum optimal management strategy,such as null motion.Finally,five simulation scenarios were carried out to demonstrate the effectiveness of the proposed control strategy and hybrid actuator.
基金supported by National Basic Research and Development Program of China (973 Program, Grant No. 2006CB705402)
文摘In order to solve the problem of trajectory tracking for a class of novel serial-parallel hybrid humanoid arm（HHA）, which has parameters uncertainty, frictions, disturbance, abrasion and pulse forces derived from motors, a multistep dynamics modeling strategy is proposed and a robust controller based on neural network（NN）-adaptive algorithm is designed. At the first step of dynamics modeling, the dynamics model of the reduced HHA is established by Lagrange method. At the second step of dynamics modeling, the parameter uncertain part resulting mainly from the idealization of the HHA is learned by adaptive algorithm. In the trajectory tracking controller, the radial basis function（RBF） NN, whose optimal weights are learned online by adaptive algorithm, is used to learn the upper limit function of the total uncertainties including frictions, disturbances, abrasion and pulse forces. To a great extent, the conservatism of this robust trajectory tracking controller is reduced, and by this controller the HHA can impersonate mostly human actions. The proof and simulation results testify the validity of the adaptive strategy for parameter learning and the neural network-adaptive strategy for the trajectory tracking control.
基金supported by the National Key Research and Development Plan of China (No.2016YFB0101102 )the Suzhou Tsinghua Innovation Initiative(No. 2016SZ0207)+2 种基金the National Natural Science Foundation of China(No.51375007)the Research Project of Key Laboratory of Advanced Manufacture Technology for Automobile Parts(Chongqing University of Technology),Ministry of Education (No.2015KLMT04)the Fundamental Research Funds for the Central Universities (No. NE2016002)
文摘Automotive collision avoidance technology can effectively avoid the accidents caused by dangerous traffic conditions or driver's manipulation errors.Moreover,it can promote the development of autonomous driving for intelligent vehicle in intelligent transportation.We present a collision avoidance system,which is composed of an evasive trajectory planner and a path following controller.Considering the stability of the vehicle in the conflict-free process,the evasive trajectory planner is designed by polynomial parametric method and optimized by genetic algorithm.The path following controller is proposed to make the car drive along the designed path by controlling the vehicle's lateral movement.Simulation results show that the vehicle with the proposed controller has good stability in the collision process,and it can ensure the vehicle driving in accordance with the planned trajectory at different speeds.The research results can provide a certain basis for the research and development of automotive collision avoidance technology.
