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Institutionen för 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

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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)

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Targeted algorithms

Computationally intensive and distributed real-time algorithms:

Estimation Kalman filter Particle filter

Control Model-predictive control Multivariable control

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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

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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)

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Bearings-only tracking

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Speedup Particle filters

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Speedup Kalman filter

Grad Kalkyl

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Anomaly detection

Vid röda punkten 43 försvann Arctic Sea från AIS-systemet. Då var klockan 04.20 onsdagen den 24 juli 2009. En och en halv timme senare dök det upp igen vid den gröna punkten 44. Sedan drev fartyget långsamt norröver i nästan två timmar innan det fick upp farten och vände söderut igen.

Karta: Sjöfartsverket.