Robot control design by quantitative feedback theory

A systematic robot control scheme based on off-line system identification and the quantitative feedback theory (QFT) is developed in this paper. The highly nonlinear and coupling properties of a manipulator make the control problem even more difficult. Avoiding the complex decoupling techniques used in multivariable system design, the system identification technique to extract system model with a bound is adopted instead. At different configurations, each axis is represented by linear second-order models. Due to the fact that positions and orientations of the manipulator may pose, parameter, i.e., pole as well as gain, variation of the transfer functions for each axis is determined by the identification technique. The QFT can then be readily applied to deal with the plant uncertainty. Since the identified transfer functions of the first three joints may assume unstable methods in some cases, the state-feedback stabilization is first accomplished before the design process of the adaptive control scheme.<>