Most of the existing control methods for servo systems driven by hydraulic actuators have been developed by using a backstepping scheme and assuming that all system states (including internal hydraulic signals) are measurable. In this paper, we propose a new control design method for high-order servo systems with hydraulic actuator dynamics, where the backstepping scheme is avoided and only the system output (e.g., motion displacement) is required for the control implementation. For this purpose, the system model is first transformed into a canonical form, where the unknown dynamics in the system are lumped as one term. Then, we introduce a simple robust unknown dynamics estimator (UDE) that has only one tuning parameter but achieves exponential error convergence to accommodate the lumped uncertainties. Therefore, the function approximators (e.g., neural network and fuzzy systems) can be avoided, leading to reduced computational costs, simpler parameter tuning, and improved convergence as compared to backstepping methods. Extensive simulations and experiments based on a realistic test rig are conducted to show the efficacy of the proposed control.

中文翻译：

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不确定液压伺服系统的输出反馈控制

现有的由液压执行器驱动的伺服系统的大多数控制方法都是通过使用反步方案并假设所有系统状态（包括内部液压信号）都是可测量的。在本文中，我们为具有液压致动器动力学的高阶伺服系统提出了一种新的控制设计方法，其中避免了反步方案，并且只需要系统输出（例如，运动位移）来实现控制。为此，首先将系统模型转换为规范形式，其中系统中的未知动力学被集中为一项。然后，我们引入了一个简单的鲁棒未知动态估计器 (UDE)，它只有一个调整参数，但实现了指数误差收敛以适应集中的不确定性。因此，函数逼近器（例如，神经网络和模糊系统）可以避免，与反推方法相比，可以减少计算成本，更简单的参数调整和改进的收敛性。进行了基于现实测试台的大量模拟和实验，以显示所提出的控制的有效性。