论文部分内容阅读
本文考察带动力学不确定性的刚性机械臂的跟踪控制问题。文中给出了新型标称跟踪控制器,它由两部分组成:一是非线性补偿器,二是新型PID型跟踪控制器。同时给出了如何采用人工神经元网络方法,使通过“学习”、逐步“认识”不确定性,据此设计额外补偿费。对于存在和不存在不确定性的情况,都对跟踪控制系统的性能做了分析。
This paper investigates the tracking control problem of rigid manipulators with kinematic uncertainties. The paper presents a new nominal tracking controller, which consists of two parts: one is the nonlinear compensator and the other is the new PID tracking controller. At the same time, it shows how to adopt artificial neural network method to make “learning” gradually “recognize” the uncertainty and design additional compensation fees accordingly. For the presence and absence of uncertainty, the performance of the tracking control system was analyzed.