论文标题
放松的耗散性假设和用于多目标MPC的简化算法
Relaxed dissipativity assumptions and a simplified algorithm for multiobjective MPC
论文作者
论文摘要
我们考虑具有多个竞争成本功能的非线性模型预测控制（MPC）。在方案的每个步骤中，都解决了具有非线性系统和终端条件的多目标最佳控制问题。我们提出了一种算法，并为由此产生的MPC闭环系统提供性能保证。因此，我们通过假设严格的消散性和仅在其中一个竞争目标函数的兼容终端成本的存在来大大简化文献中的假设。我们提供的条件可确保闭环的渐近稳定性，而且，此外，还获得了所有成本标准的绩效估算。各种实例的数值模拟说明了我们的发现。所提出的算法需要在每次迭代中选择有效的解决方案，因此我们检查了几种选择规则及其对结果的影响。
We consider nonlinear model predictive control (MPC) with multiple competing cost functions. In each step of the scheme, a multiobjective optimal control problem with a nonlinear system and terminal conditions is solved. We propose an algorithm and give performance guarantees for the resulting MPC closed loop system. Thereby, we significantly simplify the assumptions made in the literature so far by assuming strict dissipativity and the existence of a compatible terminal cost for one of the competing objective functions only. We give conditions which ensure asymptotic stability of the closed loop and, what is more, obtain performance estimates for all cost criteria. Numerical simulations on various instances illustrate our findings. The proposed algorithm requires the selection of an efficient solution in each iteration, thus we examine several selection rules and their impact on the results.
