发表机构
Delft Center for Systems and Control, TU Delft（代尔夫特系统与控制中心，代尔夫特理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对输入约束非线性系统，建立了异步确定性等价模型预测控制在模型失配下的稳定性与性能保证，量化了预测时域、执行间隔和不确定性对性能的影响，为异步MPC设计提供指导。
AI 中文摘要
确定性等价模型预测控制（CE-MPC）因其简单高效而被广泛使用，但在异步反馈下的理论保证仍然有限。本文针对输入约束非线性系统，建立了异步CE-MPC的稳定性与性能保证。我们首先推导了一个名义稳定性条件和竞争比界，该界明确考虑了执行间隔，而无需指定反馈机制。随后，针对二次阶段代价的价值函数扰动分析，在无约束限定条件下，处理了加性且可能非光滑的模型失配。结合这些结果，我们得到了在一般异步反馈（包括事件/自触发和多步MPC）下CE-MPC的稳定性准则和竞争比界。这些保证明确关联了预测时域、执行间隔和不确定性幅度，量化了相对于理想无限时域控制器的性能退化。这些结果阐明了反馈频率、模型精度和时域长度之间的权衡，为使用近似或学习模型的异步MPC设计提供了指导。
英文摘要
Certainty-equivalence model predictive control (CE-MPC) is widely used for its simplicity and efficiency, but theoretical guarantees under asynchronous feedback remain limited. This paper establishes stability and performance guarantees for asynchronous CE-MPC of input-constrained nonlinear systems. We first derive a nominal stability condition and competitive-ratio bound that explicitly account for inter-execution intervals without prescribing a feedback mechanism. A value-function perturbation analysis for quadratic stage costs then accommodates additive, potentially non-smooth model mismatch without constraint qualification conditions. Combining these results yields stability criteria and competitive-ratio bounds for CE-MPC under general asynchronous feedback, including event/self-triggered and multi-step MPC. The guarantees explicitly relate prediction horizon, inter-execution time, and uncertainty magnitude, quantifying performance degradation relative to an ideal infinite-horizon controller. These results clarify tradeoffs between feedback frequency, model accuracy, and horizon length, guiding asynchronous MPC design using approximate or learned models.
CommentsThis is the first work to characterize the joint effects of model mismatch, general asynchronous feedback, and prediction horizon on stability and suboptimality. Explicit closed-form stability conditions and competitive-ratio performance bounds are derived and rigorously proved
