Title
Improving the performance of active set based Model Predictive Controls by dataflow methods
Abstract
Dataflow representations of Digital Signal Processing (DSP) software have been developing since the 1980's. They have proven to be useful in identifying bottlenecks in DSP algorithms, improving the efficiency of the computations, and in designing appropriate hardware for implementing the algorithms. This paper demonstrates the use of dataflow to improve a Model Predictive Control (MPC) algorithm. MPC has been extensively used in the real world but its application has been limited to relatively slow processes because it is computationally intensive. It is shown that the time required for the MPC computations using a representative active set method for solving the optimization problem can be reduced by means of dataflow analysis and implementation improvements based on these analyses.
Year
DOI
Venue
2009
10.1109/CDC.2009.5400779
CDC
Keywords
Field
DocType
optimisation,signal processing,model predictive controls,dataflow analysis,dataflow representations,optimization,active set method,digital signal processing,predictive control,algorithm design and analysis,computational modeling,data mining,optimization problem,hardware,mathematical model,parallel processing,model predictive control
Signal processing,Digital signal processing,Algorithm design,Active set method,Computer science,Model predictive control,Parallel computing,Software,Dataflow,Optimization problem
Conference
ISSN
ISBN
Citations 
0191-2216 E-ISBN : 978-1-4244-3872-3
978-1-4244-3872-3
1
PageRank 
References 
Authors
0.41
2
3
Name
Order
Citations
PageRank
Ruirui Gu1566.71
Shuvra S. Bhattacharyya21416162.67
William S. Levine3135.15