时变输出约束机械臂系统渐近跟踪控制

Asymptotic Tracking Control for Robot Manipulators Systems with Time-Varying Output Constraints

针对非对称时变输出约束的机械臂系统,提出了一种基于事件触发的自适应渐近跟踪控制策略。首先,采用自适应命令滤波反步方法,解决了“计算爆炸”问题;同时,利用时变非对称李雅普诺夫函数,可以保证闭环系统的渐近稳定性且系统状态满足非对称时变约束条件;此外,自适应渐近跟踪控制可以保证在存在不匹配扰动的情况下,跟踪误差渐近收敛于零。该控制器设计采用了事件触发控制策略,在必要时产生控制输入,减少通信负担,提高了控制性能;最后,通过对非对称时变约束下的双连杆机械臂系统进行仿真,验证了该方法的有效性。

In this paper,an event-based adaptive asymptotic tracking control strategy is proposed for robot manipulator systems with asymmetric time-varying output constraints.Firstly,the“computational explosion”problem is solved by employing the adaptive command filtered backstepping method.At the same time,the asymptotic stability of the closed-loop system can be guaranteed by using the asymmetric time-varying Lyapunov function,and the system state satisfies the asymmetric time-varying constraints.In addition,the adaptive asymptotic tracking control can ensure that the tracking errors converge to zero asymptotically in the case of mismatched disturbance.Besides,the control design utilizes the event-triggered control mechanism that generates control inputs only when necessary,reducing the computational burden and improving the control performance.Finally,a two-link manipulator system with asymmetric time-varying constraints is simulated to verify the effectiveness of the proposed method.