# Luenberger observer for linear system control

This article explains the design of Luenberger observer for linear system control. If you are interested in the design of nonlinear system observer, read the next article. Observer in control systems is very important because we cannot directly “observe” the system state. One very popular observer is Kalman Filter and another is this Luenberger observer. Kalman Filter is built based on Bayesian rule (probabilistic) so that it is robust for measurement error, but slow. In contrast, Luenberger observer is based on deterministic sense so that fast. Of course, robustness is very important but robust measurement algorithm makes the algorithm slow, and actually Luenberger observer can observe most of systems successfully. The below is the proof and the selection of gain values for Luenberger observer, If you are interested in nonlinear version of Luenberger observer, read here.

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I am Youngmok Yun, and writing about robotics theories and my research.

My main site is http://youngmok.com, and Korean ver. is  http://yunyoungmok.tistory.com.

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# Feedback linearization control (FBL) for nonlinear system control proof, practical implementation, and easy example part 2

This article explains about Feedback linearization control (FBL) method for control of a nonlinear system. By demonstrating a control strategy of the inverted pendulum problem, I am going to explain how to implement its algorithm into a real system. The basic idea is that we can cancel control input by manipulating control input. The below is its practical implementation method and example.

If you want to know the proof of feedback linearization control method. refer this.

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I am Youngmok Yun, and writing about robotics theories and my research.

My main site is http://youngmok.com, and Korean ver. is  http://yunyoungmok.tistory.com.

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# Feedback linearization control (FBL) for nonlinear system control proof, practical implementation, and easy example part1

This article explains about Feedback linearization control (FBL) method for control of a nonlinear system. This is one of the easiest strategy to control nonlinear systems, but pretty powerful. The basic idea is that we can cancel control input by manipulating control input. The below is its proof.

This is the most basic concept to explain easily. If the nonlinear system is not fully controllable, we should use another strategy which finds reduced order manifold (ROM). About the more advanced technique and examples will be explained in the next articles.

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I am Youngmok Yun, and writing about robotics theories and my research.

My main site is http://youngmok.com, and Korean ver. is  http://yunyoungmok.tistory.com.

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