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Pressure observer based adaptive robust trajectory tracking control of a parallel manipulator driven by pneumatic muscles

机译:基于压力观测器基于气动肌肉驱动的并联机械手的自适应鲁棒轨迹跟踪控制

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This paper presents a pressure observer based adaptive robust controller (POARC) for posture trajectory tracking of a parallel manipulator driven by three pneumatic muscles without pressure sensors. Due to model errors of the static forces and friction forces of pneumatic muscles, simplified average flow rate characteristics of valves, unknown disturbances of entire system, and unmeasured pressures, there exist rather severe parametric uncertainties, nonlinear uncertainties and dynamic uncertainties in modeling of the parallel manipulator. A nonlinear pressure observer is constructed to estimate unknown pressures on the basis of a single-input-single-output (SISO) decoupling model that is simplified from the actual multiple-input-multiple-output (MIMO) coupling model of the parallel manipulator. Then, an adaptive robust controller integrated with the pressure observer is developed to accomplish high precision posture trajectory tracking of the parallel manipulator. The experimental results indicate that the system with the proposed POARC not only achieves good control accuracy and smooth movement but also maintains robustness to disturbances.
机译:本文介绍了一种基于压力观测器的自适应鲁棒控制器(POARC),用于平行机械手的姿势轨迹跟踪,其由三个气动肌肉驱动而没有压力传感器。由于静力和气动肌的摩擦力的模型误差,简化平均流量特性的阀门,整个系统的未知干扰,以及未测量的压力,存在相当严重的参数不确定性,非线性不确定性和平行建模中的动态不确定性操纵器。构造非线性压力观测器以基于单输入单输出(SISO)解耦模型来估计未知压力,该模型是由并行机械手的实际多输入 - 多输出(MIMO)耦合模型简化的单一输入单输出模型。然后,开发了一种与压力观测器集成的自适应稳健控制器,以实现平行操纵器的高精度姿势轨迹跟踪。实验结果表明,该系统具有拟议的POARC不仅可以实现良好的控制精度和平稳的运动,而且还保持稳健性。

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