LMIs in Control/pages/LMI for the Observability Grammian
LMI for the Observability Grammian
Observability is a system property which says that the state of the system can be reconstructed using the input and output on an interval . This is necessary when knowledge of the full state is not available. If observable, estimators or observers can be created to reconstruct the full state. Observability and controllability are dual concepts. Thus in order to investigate the observability of a system we can study the controllability of the dual system. Although system observability can be determined with multiple methods, one is to compute the rank of the observability grammian.
where , , at any .
The matrices necessary for this LMI are and .
The LMI:LMI to Determine the Observability Grammian
is observable if and only if is the unique solution to
where is the observability grammian.
The above LMI attempts to find the observability grammian of the system . If the problem is feasible and a unique is found, then the system is also observable. The observability grammian can also be computed as: . Due to the dual nature of observability and controllability this LMI can be determined by determining the controllability of the dual nature, which results in the above LMI. The Observability and Controllability matricies are written as and respectively. They are related as follows:
Hence is observable if and only if is controllable. Please refer to the section on controllability grammians.
This implementation requires Yalmip and Sedumi.
A list of references documenting and validating the LMI.
- LMI Methods in Optimal and Robust Control - A course on LMIs in Control by Matthew Peet.
- LMI Properties and Applications in Systems, Stability, and Control Theory - A List of LMIs by Ryan Caverly and James Forbes.
- LMIs in Systems and Control Theory - A downloadable book on LMIs by Stephen Boyd.
- LMIs in Control Systems: Analysis, Design and Applications - by Guang-Ren Duan and Hai-Hua Yu, CRC Press, Taylor & amp; Francis Group, 2013, Section 6.1.1 and Table 6.1 pp. 166–170, 192.
- A Course in Robust Control Theory: a Convex Approach, - by Geir E. Dullerud and Fernando G. Paganini, Springer, 2011, Section 2.2.3, pp. 71-73.