机译:FAST L_1L1

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摘要

This study proposes a new method based on sensitivity analysis to solve a series of sequential parametric linear programmings (LPs) such as that those arise in l(1) model predictive controll(1) (MPC). The main idea is to find a relationship between each of the two successive parametric LPs by using sensitivity analysis strategy. Tolerance analysis-based MPC (TA-l(1) MPC) and sensitivity analysis-based MPC (SA-l(1) MPC) are introduced for reducing computational complexity and runtime. TA-l(1) MPC takes O(Nn(2)) operations per step time, where N and n are the prediction horizon and the number of states, respectively. This approach is very faster than generic optimisation methods but it can be applied only for initial conditions that are near to steady-state values. SAl1 MPC has not any limitation in usage and it reduces the runtime significantly compared with common solvers. Finally, numerical results indicate the potential of the proposed algorithms.
机译:本研究提出了一种基于灵敏度分析的新方法,以解决一系列顺序参数线性节目(LPS),例如L(1)模型预测控制(1)(MPC)中出现的那些。主要思想是通过使用灵敏度分析策略在两个连续参数LPS之间找到关系。引入了基于公差分析的MPC(TA-L(1)MPC)和基于敏感性分析的MPC(SA-1(1)MPC),以降低计算复杂性和运行时。 TA-L(1)MPC每步时间采用O(nn(2))操作,其中n和n分别是预测地平线和状态的数量。这种方法比通用优化方法更快,但它只能用于靠近稳态值的初始条件。 SAL1 MPC在使用中没有任何限制,与普通溶剂相比,它会显着降低运行时。最后,数值结果表明所提出的算法的潜力。

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