Cooperative distributed model predictive control of multiple coupled linear systems
Cooperative distributed model predictive control of multiple coupled linear systems
复制标题
DOI：
10.1049/iet-cta.2015.0096
复制
发表时间：
2015-11
影响因子：
2.6
通讯作者：
Yulong Gao;Yuanqing Xia;Li Dai
中科院分区：
文献类型：
--
作者：
Yulong Gao;Yuanqing Xia;Li Dai
针对一组具有耦合成本和耦合约束的线性子系统，提出了一种协同分布式模型预测控制(CDMPC)算法。在每个采样时间，允许所有子系统同步优化。构造了一个改进的兼容性约束，以确保每个子系统的实际状态轨迹不会偏离假设状态轨迹太多，这对确保稳定性起到了重要作用。此外，还以分布式方式设计了正不变终端集和与之相关的终端代价(局部控制Lyapunov函数)。通过应用所提出的算法，保证了局部约束和耦合约束的递推可行性以及整个系统的闭环稳定性。最后，给出了CDMPC算法与集中式模型预测控制算法的数值比较结果，验证了该算法的有效性。
This study presents a cooperative distributed model predictive control (CDMPC) algorithm for a team of linear subsystems with the coupled cost and coupled constraints. At each sampling time, all the subsystems are permitted to synchronously optimise. An improved compatibility constraint, which plays an important to ensure the stability, is constructed to ensure that the actual state trajectory of each subsystem does not deviate too much from its assumed one. Moreover, a positive invariant terminal set and an associated terminal cost (a local control-Lyapunov function) are designed in the distributed manner. By applying the proposed algorithm, the recursive feasibility with respect to both local and coupled constraints and the closed-loop stability of the whole system are ensured. In final, the numerical results of the comparisons between the CDMPC algorithm and the centralised model predictive control are given to show the effectiveness of the proposed algorithm.