论文标题
大型多代理网络的基于LQR的分布式观察者设计
Distributed LQR-based observer design for large-scale multi-agent networks
论文作者
论文摘要
在本文中，考虑了具有相同动力学的代理网络。假定代理商是由自我和邻近的输出测量所馈送的，而状态则无法进行测量。通过利用两种互补的分布式LQR方法，提出了将分布式LQR问题视为分布式LQR问题双重的分布式估计。第一种是一种自下而上的方法，其中定义了自动稳定剂之间的最佳相互作用，以最大程度地减少全局LQR标准的上限。在第二个（自上而下）的方法中，集中式最佳LQR控制器由分布式控制方案近似，该方案通过LQR控制的稳定性保证了稳定性。在本文中，通过使用自下而上的方法解决双重LQR问题，提出了将确定性性能标准的上限最小化的分布式观察者。成本函数是通过考虑最低能量估计理论来定义的，在该理论中，加权矩阵具有确定性的解释。提出的结果可用于设计最佳或近乎最佳的分布式控制/估计方案。
In this paper, network of agents with identical dynamics is considered. The agents are assumed to be fed by self and neighboring output measurements, while the states are not available for measuring. Viewing distributed estimation as dual to the distributed LQR problem, a distributed observer is proposed by exploiting two complementary distributed LQR methods. The first consists of a bottom-up approach in which optimal interactions between self-stabilizing agents are defined so as to minimize an upper bound of the global LQR criterion. In the second (top-down) approach, the centralized optimal LQR controller is approximated by a distributed control scheme whose stability is guaranteed by the stability margins of LQR control. In this paper, distributed observer which minimizes an upper bound of a deterministic performance criterion, is proposed by solving a dual LQR problem using bottom-up approach. The cost function is defined by considering minimum-energy estimation theory where the weighting matrices have deterministic interpretation. The presented results are useful for designing optimal or near-optimal distributed control/estimation schemes.
