控制理论(社会学)
估计员
相位裕度
模型预测控制
理论(学习稳定性)
常量(计算机编程)
控制系统
稳态(化学)
数学
计算机科学
工程类
带宽(计算)
控制(管理)
放大器
计算机网络
统计
运算放大器
人工智能
机器学习
电气工程
程序设计语言
化学
物理化学
作者
Scott A. Bortoff,Paul Schwerdtner,Claus Danielson,Stefano Di Cairano,Daniel J. Burns
标识
DOI:10.1109/tcst.2022.3141937
摘要
We formulate a model predictive control (MPC) for linear time-invariant systems based on H-infinity loop-shaping. The design results in a closed-loop system that includes a state estimator and attains an optimized stability margin. Input and output weights are designed in the frequency domain to satisfy steady-state and transient performance requirements, in lieu of standard MPC plant model augmentations. The H-infinity loop-shaping synthesis results in an observer-based state feedback structure. An inverse optimal control problem is solved to construct the MPC cost function, so that the control input computed by MPC is equal to the H-infinity control input when the constraints are inactive. The MPC inherits the closed-loop performance and stability margin of the loop-shaped design when constraints are inactive. We apply the methodology to a multizone heat pump, and validate the results in simulations and laboratory experiments. The design rejects constant unmeasured disturbances, tracks constant references with zero steady-state error, meets transient performance requirements, provides an excellent stability margin, and enforces input and output constraints.
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