2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004
This paper proves the bouudeduess of boundary and distributed damped strings and Euler-Bernoulli ... more This paper proves the bouudeduess of boundary and distributed damped strings and Euler-Bernoulli beams under combined distributed and boundary inputs. Distributed viscous or Kelvin-Voigt damping or a translational boundary damper stabilize strings and beams. Pointwise bounded re sponse is proven using the energy multiplier method. Without disturbances, the method proves strong exponential stability.
ABSTRACT Repetitive contact imaging uses a flexible whisker attached to a two-axis robot through ... more ABSTRACT Repetitive contact imaging uses a flexible whisker attached to a two-axis robot through a load cell. Assuming small deformations and rotations, the pitch axis decouples from the yaw. The yaw axis, under proportional—integral—derivative control, sweeps periodically back and forth across the object while the pitch axis, under repetitive learning (RL) control, maintains a uniform contact force. Once the RL controller converges, the three-dimensional contact points can be determined using an elastica algorithm. The RL controller is proven stable based on a distributed parameter beam model and is experimentally shown to provide a stable performance with improved moment regulation when compared with under proportional-derivative control.
2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004
This paper proves the bouudeduess of boundary and distributed damped strings and Euler-Bernoulli ... more This paper proves the bouudeduess of boundary and distributed damped strings and Euler-Bernoulli beams under combined distributed and boundary inputs. Distributed viscous or Kelvin-Voigt damping or a translational boundary damper stabilize strings and beams. Pointwise bounded re sponse is proven using the energy multiplier method. Without disturbances, the method proves strong exponential stability.
ABSTRACT Repetitive contact imaging uses a flexible whisker attached to a two-axis robot through ... more ABSTRACT Repetitive contact imaging uses a flexible whisker attached to a two-axis robot through a load cell. Assuming small deformations and rotations, the pitch axis decouples from the yaw. The yaw axis, under proportional—integral—derivative control, sweeps periodically back and forth across the object while the pitch axis, under repetitive learning (RL) control, maintains a uniform contact force. Once the RL controller converges, the three-dimensional contact points can be determined using an elastica algorithm. The RL controller is proven stable based on a distributed parameter beam model and is experimentally shown to provide a stable performance with improved moment regulation when compared with under proportional-derivative control.
Uploads
Papers by Haiyu Zhao