论文信息 - Robust stability analysis of robot control systems

Robust stability analysis of robot control systems

Abstract Some robust stability measures for state-space models are discussed. These measures are used for assessing the robustness of a robotic system controlled by a form of the PID control algorithm. The highly nonlinear and strongly coupled robot model is replaced by a nominal linear model involving modelling uncertainty. The amount of uncertainty under which the robotic system can maintain its stability and tracking performance is determined using the above measures. The parametric sensitivity of the robotic system is also briefly considered.

Spyros G. Tzafestas | Irena Jaworska

[1] Lino Guzzella,et al. Time-optimal motions of robots in assembly tasks , 1985, 1985 24th IEEE Conference on Decision and Control.

[2] J. Martin. State-space measures for stability robustness , 1987 .

[3] S. Desa,et al. Stability and performance robustness of manipulators , 1985, 1985 24th IEEE Conference on Decision and Control.

[4] Hooshang Hemami,et al. An adaptive positional control scheme for robotic systems , 1985, 1985 24th IEEE Conference on Decision and Control.

[5] Lino Guzzella,et al. Time-optimal motions of robots in assembly tasks , 1986 .

[6] Spyros G. Tzafestas,et al. Robot model reference adaptive control through lower/upper part dynamic decoupling , 1988, J. Intell. Robotic Syst..

[7] Rama K. Yedavalli. Robust Control Design for Linear Systems with Structured Uncertainty , 1987 .

[8] A. Dickman,et al. On the robustness of multivariable linear feedback systems in state-space representation , 1987 .

[9] Spyros G. Tzafestas,et al. Improvement of systems reliability using robust control theory , 1991 .

[10] P. Dorato,et al. A historical review of robust control , 1987, IEEE Control Systems Magazine.

[11] Spyros G. Tzafestas,et al. Model Reference Adaptive Control of Industrial Robots with Actuator Dynamics , 1989 .

[12] S. Tzafestas,et al. Decentralized PID self-tuning control of industrial robots , 1986, 1986 25th IEEE Conference on Decision and Control.