Informationsteknologi Institutionen f¶r informationsteknologi | Model-based estimation and control on multicore platforms Motivation: Streamlined

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Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Model-based estimation and control on multicore platforms Motivation: Streamlined real-time control and estimation software written for single core runs slower on multicore Battery-driven embedded control systems need multicore processors for longer battery life and reduced heat production Control and estimation algorithms: Application design must map to the multicore architecture Parallel Cache-aware Slide 2 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Work plan Goals: Re-design of control and estimation algorithms for linear speedup on multicore platforms Model processor and memory system demand of algorithms for guaranteed real-time performance Proof of concept in laboratory real-time setups (control) and data from industrial applications (estimation) Slide 3 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Targeted algorithms Computationally intensive and distributed real-time algorithms: Estimation Kalman filter Particle filter Control Model-predictive control Multivariable control Slide 4 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Results so far Effective implementation of the Kalman filter on multicore The KF is modified to give linear speedup Application to echo cancellation Memory bandwidth model Effective implementation of the Particle Filters on multicore A number of PFs is evaluated with respect to scaling, performance, computational burden Algorithms with good scaling properties on multicore are found. Application to bearings-only tracking (SAAB Systems) Feedforward state estimation algorithms are revisited to clarify design issues Laboratory setup for real-time estimation and control on multicore LEGO-based mobile robotic wireless sensor network Multicore central node Both control (of mobile robots) and estimation Slide 5 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Future and ongoing research Estimation MIMO Kalman filtering (sensor fusion) Anomaly detection (SAAB Systems) Change detection by Kalman filter Change detection by Particle filter New applications Road grade estimation (Scania) Control Parallelization of model-predictive control (parallel optimization) Slide 6 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Bearings-only tracking Slide 7 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Speedup Particle filters Slide 8 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Speedup Kalman filter GradKalkyl Slide 9 Informationsteknologi Institutionen fr informationsteknologi | www.it.uu.se Anomaly detection Vid rda punkten 43 frsvann Arctic Sea frn AIS-systemet. D var klockan 04.20 onsdagen den 24 juli 2009. En och en halv timme senare dk det upp igen vid den grna punkten 44. Sedan drev fartyget lngsamt norrver i nstan tv timmar innan det fick upp farten och vnde sderut igen. Karta: Sjfartsverket.