综合的机器人鲁棒自适应控制

研究了不确定性机器人轨迹跟踪的鲁棒自适应控制方法．利用机器人动力学参数变量分离方法，将系统的集中不确定性反映到一个集中的标量参数上，进而提出一种基于简单的计算力矩结构的综合鲁棒自适应控制策略，同时还设计了一个通用的非线性反馈增益和一个简单的自适应律，通过在线刷新一个集中的系统不确定性参数，最后保证系统达到全局指数意义的渐近稳定或全局一致最后有界．通过简化控制结构得出一种简单的鲁棒控制器．按照对控制参数的不同选择，可保证系统达到严格的全局一致最后有界、全局渐近稳定、全局指数稳定三种稳定性结果．理论分析和计算机仿真验证了控制律的有效性．

Synthetical Robust Adaptive Control of Robot Manipulators

By virtue of a novel parameter separation method that the lumped uncertainties of robot dynamics can be transferred to a scalar constant, a synthetical computed torque structure based robust adaptive control algorithm for trajectory tracking of robot manipulators with uncertainties was proposed. A general nonlinear feedback gain and a simple adaptive controllaw which is used to update the uncertain scalar constant were presented to warrant that the closed loop system can attain global asymptotical stability in a sense of exponential convergence or global uniform ultimate boudedness. In addition, a simple robust controller was also developed by simplifying the control structure and it is shown by theories and simulations that the effects of large system uncertainties can be compensated and the three kinds of stability results (i.e. global uniform ultimate boundendness, global asymptotical stability, global exponential stability) can be guaranteed based on the designer's choice.