The stochastic gradient (SG) algorithm has less of a computational burden than the least squares algorithms, but it can not track time varying parameters and has a poor convergence rate. In order to improve the track...The stochastic gradient (SG) algorithm has less of a computational burden than the least squares algorithms, but it can not track time varying parameters and has a poor convergence rate. In order to improve the tracking properties of the SG algorithm, the forgetting gradient (FG) algorithm is presented, and its convergence is analyzed by using the martingale hyperconvergence theorem. The results show that: (1) for time invariant deterministic systems, the parameter estimates given by the FG algorithm converge consistently to their true values; (2) for stochastic time varying systems, the parameter tracking error is bounded, that is, the parameter tracking error is small when both the parameter change rate and the observation noise are small.展开更多
We proposed and implemented a leg-vector water-jet actuated spherical robot and an underwater adaptive motion control system so that the proposed robot could perform exploration tasks in complex environments.Our aim w...We proposed and implemented a leg-vector water-jet actuated spherical robot and an underwater adaptive motion control system so that the proposed robot could perform exploration tasks in complex environments.Our aim was to improve the kinematic performance of spherical robots.We developed mechanical and dynamic models so that we could analyze the motions of the robot on land and in water.The robot was equipped with an Inertial Measurement Unit(IMU)that provided inclination and motion information.We designed three types of walking gait for the robot,with different stabilities and speeds.Furthermore,we proposed an online adjustment mechanism to adjust the gaits so that the robot could climb up slopes in a stable manner.As the system function changed continuously as the robot moved underwater,we implemented an online motion recognition system with a forgetting factor least squares algorithm.We proposed a generalized prediction control algorithm to achieve robust underwater motion control.To ensure real-time performance and reduce power consumption,the robot motion control system was implemented on a Zynq-7000 System-on-Chip(SoC).Our experimental results show that the robot’s motion remains stable at different speeds in a variety of amphibious environments,which meets the requirements for applications in a range of terrains.展开更多
基金the National Natural Science Foundationof China!( No.6993 4 0 10)
文摘The stochastic gradient (SG) algorithm has less of a computational burden than the least squares algorithms, but it can not track time varying parameters and has a poor convergence rate. In order to improve the tracking properties of the SG algorithm, the forgetting gradient (FG) algorithm is presented, and its convergence is analyzed by using the martingale hyperconvergence theorem. The results show that: (1) for time invariant deterministic systems, the parameter estimates given by the FG algorithm converge consistently to their true values; (2) for stochastic time varying systems, the parameter tracking error is bounded, that is, the parameter tracking error is small when both the parameter change rate and the observation noise are small.
基金National Natural Science Foundation of China(61773064,61503028).
文摘We proposed and implemented a leg-vector water-jet actuated spherical robot and an underwater adaptive motion control system so that the proposed robot could perform exploration tasks in complex environments.Our aim was to improve the kinematic performance of spherical robots.We developed mechanical and dynamic models so that we could analyze the motions of the robot on land and in water.The robot was equipped with an Inertial Measurement Unit(IMU)that provided inclination and motion information.We designed three types of walking gait for the robot,with different stabilities and speeds.Furthermore,we proposed an online adjustment mechanism to adjust the gaits so that the robot could climb up slopes in a stable manner.As the system function changed continuously as the robot moved underwater,we implemented an online motion recognition system with a forgetting factor least squares algorithm.We proposed a generalized prediction control algorithm to achieve robust underwater motion control.To ensure real-time performance and reduce power consumption,the robot motion control system was implemented on a Zynq-7000 System-on-Chip(SoC).Our experimental results show that the robot’s motion remains stable at different speeds in a variety of amphibious environments,which meets the requirements for applications in a range of terrains.
