2015Journal of Engineering and TechnologyRequires access

Observer Design with Gershgorin Disc and Application to System with Unknown Input

Si Chen, Sanghyuk Lee

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Abstract

Observer design for system with unknown input was carried out. Kalman filter was considered to estimate system state with white noise.With the results of Kalman filter design, state observer, controller properties, including controllability and observability, and the Kalman filter structure and algorithm were also studied. Kalman filter algorithm was applied to Position and velocity measurement based on Kalman filter with white noise, and it was constructed and achieved by programming based on Matlab programming. Finally, observer for system with unknown input was constructed with the help of Gershgorin's disc theorem. With the designed observer, system states was constructed and applied to system with unknown input. By simulation results, estimation performance was verified.

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What this paper is about

Observer design for system with unknown input was carried out. Kalman filter was considered to estimate system state with white noise.With the results of Kalman filter design, state observer, controller properties, including controllability and observability, and the Kalman filter structure and algorithm were also studied. Kalman filter algorithm was applied to Position and velocity measurement based on Kalman filter with white noise, and it was constructed and achieved by programming based on Matlab programming. Finally, observer for system with unknown input was constructed with the help of Gershgorin's disc theorem. With the designed observer, system states was constructed and applied to system with unknown input. By simulation results, estimation performance was verified.

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Available abstract

Observer design for system with unknown input was carried out. Kalman filter was considered to estimate system state with white noise.With the results of Kalman filter design, state observer, controller properties, including controllability and observability, and the Kalman filter structure and algorithm were also studied. Kalman filter algorithm was applied to Position and velocity measurement based on Kalman filter with white noise, and it was constructed and achieved by programming based on Matlab programming. Finally, observer for system with unknown input was constructed with the help of Gershgorin's disc theorem. With the designed observer, system states was constructed and applied to system with unknown input. By simulation results, estimation performance was verified.

Key concepts: Alpha beta filter, Observability, Control theory (sociology), Kalman filter, Observer (physics), Invariant extended Kalman filter, Controllability, Extended Kalman filter

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