Adaptive Trajectory Tracking Control of Global Prescribed Performance-based Space Robots
Targeting the trajectory tracking control issue of a base-floating rigid space robot,a novel global adaptive control strategy was proposed based on an adaptive neural network,a performance function,and a barrier function.First,for any initial state of the space robot system,the designed controller made the trajectory tracking error converging in a predefined time and was always con-strained to be within the boundaries of the given performance function,so as to guarantee the desired transient and steady state performances.Then,the adaptive neural network was designed based on a single-parameter updating technique to approximate the uncertainty of the space robot dynamics mod-el,thus reducing the computational burden.Finally,the consistent boundedness of all states of the system was proved by Lyapunov stability analysis criterion.Numerical simulation results showed that the proposed method not only made the trajectory tracking accuracy of the space robot reaching the desired performance constraints requirements,but also ensured the global stability of the controlled system.
space robotadaptive controlglobal stabilityprescribed performance
万方数据
维普
