CODEV:自动模型预测控制设计和形式化验证

Nicole Chan, S. Mitra
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引用次数: 2

摘要

我们提出CODEV,一个基于matlab的工具,用于验证采用模型预测控制(MPC)的系统。MPC解是离线计算的,并与物理系统一起作为混合自动机建模,其连续动力学可能是非线性的,但控制解仍然是仿射的。虽然MPC是一种广泛应用于工业约束和最优控制的综合技术,但我们的工具提供了第一种自动化方法来分析这些系统,以严格保证安全性。这是通过对非线性混合模型实施基于仿真的验证算法来实现的,并根据MPC解决方案的结构进行了扩展。给定一个物理模型和所需系统行为(即性能和约束)的参数,CODEV生成一个控制律,并验证结果系统将健壮地保持约束。我们已经成功地将CODEV应用到一组基准示例中,这说明了它在处理MPC所使用的更复杂问题方面的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CODEV: Automated Model Predictive Control Design and Formal Verification
We present CODEV, a Matlab-based tool for verifying systems employing Model Predictive Control (MPC). The MPC solution is computed offline and modeled together with the physical system as a hybrid automaton, whose continuous dynamics may be nonlinear with a control solution that remains affine. While MPC is a widely used synthesis technique for constrained and optimal control in industry, our tool provides the first automated approach of analyzing these systems for rigorous guarantees of safety. This is achieved by implementing a simulation-based verification algorithm for nonlinear hybrid models, with extensions tailored to the structure of the MPC solution. Given a physical model and parameters for desired system behavior (i.e. performance and constraints), CODEV generates a control law and verifies the resulting system will robustly maintain constraints. We have applied CODEV successfully to a set of benchmark examples, which illuminates its potential to tackle more complex problems for which MPC is used.
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