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Linear-Convex Optimal Steady-State Control
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DOI：10.1109/TAC.2020.3044275.png)
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摘要
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We consider the problem of designing a feedback controller for a multivariable linear time-invariant system, which regulates a system output to the solution of an equality-constrained convex optimization problem despite unknown constant exogenous disturbances; we term this the linear-convex optimal steady-state (OSS) control problem. We introduce the notion of an optimality model, and show that the existence of an optimality model is sufficient to reduce the OSS control problem to a stabilization problem. This yields a design framework for OSS control that unifies and extends existing design methods in the literature. We illustrate the approach via an application to optimal frequency control of power networks, where our methodology recovers centralized and distributed controllers reported in the recent literature.
Keyword:
Optimization
Steady-state
Regulation
Computational modeling
Closed loop systems
Predictive models
Convex functions
Convex optimization
online optimization
output regulation
reference tracking and disturbance rejection
期刊
IF:
7
论文数:
1.3W
被引数:
6.7W
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