.png){kind=icon}
.png){kind=icon}
Return
A Discrete Time Domain-Based MILP Framework for Control Parameter Tuning
.png){kind=icon}
PRE
AI
DOI：10.1109/JSYST.2020.2993778.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The problem of tuning a fixed optimal set of parameters in time domain for dynamic systems is inherently nonlinear due to the product of tunable variables (controller gains and time constants) and time-dependent variables (bounded to the process), involved in equality constraints. This article presents a framework to transform such nonlinear problem into a mixed-integer linear problem through a binary-disjunctive representation of the problematic product between tunable and process-bounded variables, whereas addressing alternative linear representations to other nonlinearities such as saturation. A set of linear formulations in time domain are also developed to describe typical dynamic performance requirements, such as overshoot and settling time. The proposed framework was used to determine the optimal control parameters for disturbance rejection of the active power control loop in a photovoltaic generator with battery energy storage.
Keywords:
Tuning
Time-domain analysis
Stability analysis
Process control
Optimization
Linear programming
Numerical stability
Automatic control
dynamics
energy storage
integer linear programming
optimization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
2.4
Papers:
4.5K
Citations:
387