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Publikováno v:
Journal of the Franklin Institute. 344:349-361
Manipulating flexible objects stirs a great deal of interest due to the potential applications in industry. Most previous research work with multiple manipulators, however, focused on developing control strategies for the manipulation of rigid bodies
Publikováno v:
IEEE Transactions on Neural Networks. 18:1042-1048
In this paper, experimental studies of a decentralized neural network control scheme of the reference compensation technique applied to control a 2-degrees-of-freedom (2-DOF) inverted pendulum on an x - y plane are presented. Each axis is controlled
Publikováno v:
IEEE Transactions on Control Systems Technology. 12:474-483
In this paper, a new simple stable force tracking impedance control scheme that has the capability to track a specified desired force and to compensate for uncertainties in environment location and stiffness as well as in robot dynamic model is propo
Publikováno v:
The International Journal of Robotics Research. 20:765-774
In impedance control for force tracking, it is well known that the reference trajectory of the robot is calculated from known environmental stiffness. The authors present a simple technique for determining the reference trajectory under the condition
Publikováno v:
Robotica. 18:305-314
In this paper neural network (NN) control techniques for non-model based PD controlled robot manipulators are proposed. The main difference between the proposed technique and the existing feedback error learning (FEL) technique is that compensation o
Publikováno v:
IEEE Transactions on Industrial Electronics. 47:403-412
The original impedance function is known to lack robustness due to unknown robot dynamic model and the environment. In order to improve that result, a new impedance function is derived which specifies a desired force directly. This results in a new r
Publikováno v:
IEEE Transactions on Industrial Electronics. 45:451-461
The performance of an impedance controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and environment stiffness. The purpose of this paper is to improve the controller robustness by applying the neural n
Publikováno v:
Robotica. 15:305-312
It is well known that computed torque robot control is subjected to performance degradation due to uncertainties in robot model, and application of neural network (NN) compensation techniques are promising. In this paper we examine the effectiveness
Autor:
R.G. Bonitz, T.C. Hsia
Publikováno v:
IEEE Robotics & Automation Magazine. 4:18-22
A simple, but effective, method of calibrating a multimanipulator robotic system is introduced. The algorithm uses precisely machined calibration plates which are inexpensive to manufacture and require no measuring instrumentation. The method is test