Analysis And Research Of Walking Robotic Robust Controllers

The control problems of robotic manipulators have received great attention in theoretical research and engineering for many years. It is well known that the robotic manipulator is a very complicated MIMO nonlinear system with time-varying strong-coupling and nonlinear dynamic characteristics, so the control for such a system is quite difficult, we have to face a lot of uncertainties. So the research on uncertain robot manipulators has theoretical and practical importance.Robust control is just one of the most heated problems.As we known, robot is a very complicated system with uncertainties. And robust control strategies are utilized to solve uncertainties. So the research on Robust Control of uncertain robot has theoretical and practical importance.The dissertation firstly gives a brief description about 7-link walking robot, and then the models of robot and mathematics are introduced in detail.Then, The dissertation gives a list about recent robotic control strategies, and analyse several classes of control strategies.Secondly, the robotic system with uncertainties based on an advanced Robust Control strategy are given in this dissertation. The validity of the control scheme is shown by computer simulation of a two-link robotic manipulator.Besides, robust control strategy can guarantee system's stability, but it cannot obtain the good transition condition performance, and the uncertainty upper boundary learned difficulty. It discusses a control strategy based on the neural network robust controller. It unifies the robust control and the neural network constitutes the adaptive control system. And the robust adaptive control joined PD may avoid the acceleration survey, enhancement rate signal antijamming ability. Moreover carrying on the off-line computation through the design pure forward feed item to it, can reduces the operand of the real-time control greatly, and simplified the control structure.At last, it provides a trend predication about robotic control technique in the future.