事件驱动多关节机械臂轨迹跟踪自适应鲁棒控制

针对具有不确定干扰和建模误差的多关节机械臂轨迹跟踪控制问题，基于自适应鲁棒控制算法提出事件驱动跟踪控制器。通过自适应鲁棒控制保证多关节机械臂轨迹跟踪精度，处理不确定干扰和建模误差带来的不确定性影响。利用事件驱动控制框架，以当前跟踪误差和期望状态等变量作为输入定义事件驱动系统的变量。根据Lyapunov稳定性理论获得了驱动条件，且证明了无Zeno现象发生，使系统在满足驱动条件时更新控制指令，从而减少系统能耗与通信频率，提高系统的可靠性，保证多关节机械臂跟踪控制系统半全局最终一致有界。通过仿真验证了理论结果的有效性。

Event Triggered Adaptive Robust Trajectory Tracking Control for Multi-joint Manipulators

For the multi-joint manipulator trajectory tracking control with uncertain disturbances and modelling errors, an event triggered controller is proposed based on adaptive robust control algorithm. The adaptive robust control algorithm is presented to ensure the trajectory tracking precision of multi-joint manipulator, and the adaptive term is used to deal with the uncertainty caused by uncertain disturbances and modelling errors. In the event triggered control framework, the current tracking errors and expected states are taken as inputs to define the state variables of event triggered control system, and Lyapunov stability theory is used to obtain the triggering condition,and no Zeno behaviours occur in the system. The control command is updated only when the triggering condition is satisfied, which can reduce the frequency of communication and computation, and improve the reliability. The semi-global uniform ultimate boundedness of multi-joint manipulator tracking control system is ensured, and the theoretical results are verified through simulation.