Zhang Feilong, Wang Tian, Zhang Liang, Shi Enming, Wang Chengchao, Li Ning, Lu Yu, Zhang Bi
State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China.
University of Chinese Academy of Sciences, Beijing, China.
Front Robot AI. 2025 Mar 4;12:1534040. doi: 10.3389/frobt.2025.1534040. eCollection 2025.
A sliding-mode control based on a prescribed performance function is proposed for discrete-time single-input single-output systems. The controller design aims to maintain the tracking error in a predefined convergence zone described by a performance function. However, due to the fixed structure of the controller, the applicability and universality of this method are limited. To address this issue, we separate the controller into two parts and analyze the principle of the prescribed performance control (PPC) method. Then we can replace the linear part of the controller with model-based control methods to adapt to the specific characteristics of the controlled system. Compared with current works, when the established system model is inaccurate, we can enhance the smoothness or response speed of the system by introducing a penalty constant to alter the system's transient characteristics while the tracking error is within the prescribed domain. Finally, numerical comparison simulations and a lower limb exoskeleton experiment illustrate the established results and the effectiveness of the proposed method.
针对离散时间单输入单输出系统，提出了一种基于规定性能函数的滑模控制方法。控制器设计旨在将跟踪误差保持在由性能函数描述的预定义收敛区域内。然而，由于控制器结构固定，该方法的适用性和通用性受到限制。为了解决这个问题，我们将控制器分为两部分，并分析规定性能控制（PPC）方法的原理。然后，我们可以用基于模型的控制方法替换控制器的线性部分，以适应被控系统的具体特性。与现有工作相比，当建立的系统模型不准确时，我们可以通过引入惩罚常数来改变系统的瞬态特性，从而在跟踪误差处于规定范围内时提高系统的平滑度或响应速度。最后，数值比较仿真和下肢外骨骼实验验证了所建立的结果以及所提方法的有效性。
