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Håvard Fjær Grip

Researcher at California Institute of Technology

Publications -  84
Citations -  2627

Håvard Fjær Grip is an academic researcher from California Institute of Technology. The author has contributed to research in topics: Linear system & Mars Exploration Program. The author has an hindex of 25, co-authored 75 publications receiving 2247 citations. Previous affiliations of Håvard Fjær Grip include University of Twente & Washington State University.

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Output synchronization for heterogeneous networks of non-introspective agents

TL;DR: This paper considers the output synchronization problem for heterogeneous networks of linear agents, and designs decentralized controllers based on setting the control input of a single root agent to zero and letting the remaining agents synchronize to the root agent.
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Attitude Estimation Using Biased Gyro and Vector Measurements With Time-Varying Reference Vectors

TL;DR: An algorithm for estimation of bias in the body-fixed vector measurements, which is analyzed in combination with the attitude and gyro bias observer, and proves semiglobal stability without either of these assumptions when a parameter projection is added.
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Vehicle velocity estimation using nonlinear observers

TL;DR: Nonlinear observers for estimation of lateral and longitudinal velocity of automotive vehicles are proposed based on a sensor suite that is standard in many new cars, consisting of acceleration and yaw rate measurements in addition to wheel speed and steering angle measurements.
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Mars Helicopter Technology Demonstrator

TL;DR: Nomenclature ADC Analog-to-Digital Converter BIB Battery Interface Board COTS Commerical Off-the-shelf CPU Central Processor Unit dof degrees-of-freedom ECM Electronics Core Module EDM Engineering Design Model
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Vehicle sideslip estimation

TL;DR: In this article, the authors developed a vehicle sidelip observer that takes the nonlinearities of the system into account, both in the theoretical analysis and the design, to make the observer suitable for implementation in the embedded hardware, and a reduction in the number of tuning parameters compared to the EKF.