具有未知负载扰动的水井钻机电液伺服系统无模型自适应控制

Model-free adaptive control for water well drilling rig electro-hydraulic servo with unknown load disturbance

中文关键词  水井钻机  电液伺服系统  无模型自适应控制  径向基神经网络  扰动

英文关键词  water well drilling rig  electric hydraulic servo system  model-free adaptive control  radial basis function neural network  disturbances

中文摘要

      针对电液伺服系统在水井钻机推进工况下存在的参数不确定以及未知负载扰动突变等非线性因素, 提出 了基于径向基(RBF)神经网络扰动观测器的无模型自适应控制方法. 首先, 通过改进的无模型自适应控制动态线性 化方法, 将被控系统线性化为与输入输出相关的增量形式, 并将未知负载扰动合并到一个非线性项中; 然后, 设计了 径向基神经网络扰动观测器对含有未知负载扰动的非线性项进行估计, 作为对未知扰动的补偿; 最后, 设计了时变 参数估计律, 通过在线调整伪偏导数, 给出了电液伺服系统的控制更新律. 仿真结果表明, 所设计的控制器能够对未 知负载扰动突变进行补偿, 并能确保跟踪误差有界收敛.

英文摘要

      A model-free adaptive control method based on radial basis function neural network disturbance observer is designed to solve the non-linear problems such as unmodelled dynamics and load disturbances mutations in the electrohydraulic servo system under the propulsion working condition of water well drilling rig. Firstly, the model-free adaptive dynamic linearization method is utilized to linearize the controlled system into an incremental form relative to the input and output of control system, where the uncertain disturbances are incorporated into a nonlinear term. Secondly, a radial basis function neural network disturbance observer is designed to estimate the unknown load disturbance as the compensation of mutations for the disturbances. Finally, the time-varying parameter estimation law is proposed, thence an electro-hydraulic servo system control updating law is acquired by the online adjusting the pseudo partial derivatives. The simulation results show that the compensation of with unknown load disturbances is realized and the sound convergence of tracking error is ensured by the proposed control scheme.