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Real-time implementation of model predictive control

Authors: Leonidas G. Bleris; Mayuresh V. Kothare;

Real-time implementation of model predictive control

Abstract

A real-time implementation of model predictive control (MPC) is presented in this paper. MPC, also known as receding horizon control and moving horizon control, is widely accepted as the controller of choice for multivariable systems that have inequality constraints on system states, inputs and outputs. For processes with slow dynamics and low sampling rates, MPC is typically implemented on a dedicated computer. For systems with fast dynamics such as those in MEMS, a hardware embedded MPC would be an appropriate controller implementation since the size and the application precludes the use of a dedicated computer. Recent manufacturing advances have opened the path for the fabrication of micromechanical devices and electronic subsystems under the same manufacturing and packaging process, thereby opening the path for the use of advanced control algorithms towards systems-on-chip applications.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Average
Top 10%
Top 10%
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