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针对拓扑结构为无向连通的多机械臂系统,提出了一种自适应与迭代学习相结合的分布式控制协议来实现整个系统对给定期望参考轨迹的一致性跟踪.通过引入一个适当的自适应迭代学习参数,所提自适应迭代学习控制协议能够克服机械臂系统中的干扰和模型不确定性,并且每个机械臂的自适应迭代学习控制(AILC)律仅需要利用其与邻居机械臂的相对交互信息.进一步,在只有一部分机械臂具有期望参考轨迹信息的前提下,该控制协议可以实现整个系统对期望参考轨迹的跟踪,同时能够保证轨迹跟踪误差与控制输入的有界性.此外,利用李亚普诺夫分析方法证实了所得结论的正确性,并且通过一个实例验证了所提自适应迭代学习控制协议的有效性.
Aiming at the multi-arm system with undirected topology, a distributed control protocol based on adaptive and iterative learning is proposed to achieve the consistent tracking of a given expected reference trajectory of the whole system. By introducing an appropriate Adapting to iterative learning parameters, the proposed adaptive iterative learning control protocol can overcome disturbances and model uncertainties in the manipulator system, and the adaptive iterative learning control (AILC) law of each manipulator only needs to utilize its interaction with the neighbor manipulator The control protocol can track the desired reference trajectory of the whole system and at the same time can guarantee the bound of trajectory tracking error and control input. , The correctness of the conclusion is verified by using Lyapunov analysis method, and the validity of the proposed adaptive iterative learning control protocol is verified by an example.