.png){kind=icon}
返回
Integral-Square-Error Performance of Multiplexed Model Predictive Control
.png){kind=icon}
PRE
AI
DOI：10.1109/TII.2011.2106451.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
It is well-known that faster sampling increases computational load but gives better performance. Multiplexed Model Predictive Control (MMPC) has been proposed recently. Its motivation was to reduce real-time computational load. The reduction in computational load can be used gainfully to increase sampling rate and improve performance. Hence, in this paper, we derive a formula to compute the Integral-Square-Error (ISE) performance of a MMPC controlled system. Given the plant and disturbance models, the ISE formula derived allows one to investigate how the ISE changes with control design parameters, such as the sampling interval and control weighting. This enables one to select, for example, a suitable sampling interval for the MMPC design to achieve the desired ISE performance. In addition, we validated the ISE formula on a multizone semiconductor manufacturing thermal process.
Keyword:
Control systems analysis
multiplexing
predictive control
performance evaluation
semiconductor process modeling
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.9
论文数:
8.8K
被引数:
6.9W
机构
引用论文
Performing flexible control on low-cost microcontrollers using a minimal real-time kernel使用最小实时内核在低成本微控制器上执行灵活控制
OAAI
.png){kind=icon}
OAAI分享收藏Implementation of h-infinity control algorithms for sensor-constrained mechatronic systems. using low-cost microcontrollers传感器约束机电一体化系统h ∞ 控制算法的实现使用低成本微控制器
PREAI
分享收藏A low-temperature IC-compatible process for fabricating surface-micromachined metallic microchannels
PREAI
分享收藏
查看更多内容