Real-Time Algorithms and Its Applications for Receding Horizon Control of Large-Scale Complex Nonlinear Systems

通过分别利用仿真结果的奇异值分解、压缩映射、线性互补问题和交换代数，提高了非线性滚动域控制(NRHC)的计算量和精度。因此，即使对于热学和流体现象等非线性分布参数系统，NRHC的实时实现也变得触手可及，而NRHC被认为是不可能的。还证明了一类可解析求解的NRHC问题的存在性。

Improvements in computational burden and accuracy of nonlinear receding horizon control(NRHC) have been achieved by exploiting singular-value decomposition of simulation results, contraction mappings, linear complementarity problems, and commutative algebra, respectively. As a result, real-time implementation of NRHC has been made within reach even for nonlinear distributed-parameter systems such as thermal and fluid phenomena, for which NRHC had been regarded impossible. The existence of a class of NRHC problems that can be solved analytically has also been shown.