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2006•Unpublished venueRequires access

PID state observer for robotic systems

Youngjin Choi

Open publisher page 3 citations

Abstract

The PID (proportional-integral-derivative) state observer to make an output feedback PID controller is suggested for robotic systems. When an inverse optimal PID controller (full state feedback one) is utilized with this PID state observer, an output feedback PID control system recovers the extended disturbance input-to-state stability (ISS) of a full state feedback PID control system, if only one condition for an observer gain parameter is satisfied. The condition is derived from the stability proof and it depends on only the proportional gain value among the gains in the PID controller

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What this paper is about

The PID (proportional-integral-derivative) state observer to make an output feedback PID controller is suggested for robotic systems. When an inverse optimal PID controller (full state feedback one) is utilized with this PID state observer, an output feedback PID control system recovers the extended disturbance input-to-state stability (ISS) of a full state feedback PID control system, if only one condition for an observer gain parameter is satisfied. The condition is derived from the stability proof and it depends on only the proportional gain value among the gains in the PID controller

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Available abstract

The PID (proportional-integral-derivative) state observer to make an output feedback PID controller is suggested for robotic systems. When an inverse optimal PID controller (full state feedback one) is utilized with this PID state observer, an output feedback PID control system recovers the extended disturbance input-to-state stability (ISS) of a full state feedback PID control system, if only one condition for an observer gain parameter is satisfied. The condition is derived from the stability proof and it depends on only the proportional gain value among the gains in the PID controller

Key concepts: PID controller, Control theory (sociology), Observer (physics), Stability (learning theory), Proportional control, Control engineering, Computer science, State observer

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