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Output Feedback Controller Design for Discrete LTI Systems with Polytopic Uncertainty
- Citation Author(s):
- Submitted by:
- Maryam Dehghani
- Last updated:
- Fri, 11/06/2020 - 01:16
- DOI:
- 10.21227/mvj5-ht27
- License:
- Categories:
- Keywords:
Abstract
This paper concerns static output feedback stabilization of polytopic discrete LTI systems. The previous related studies were mainly based on LMI approaches which are naturally conservative. In this paper, a novel design algorithm is presented that iteratively partitions a primary design space to subspaces. Then, by assessing stabilizability status of each generated subspace, the algorithm determines the total stabilizable parts and removes the undesired parts of the design space. Mathematical theories are developed to predict the total De-stabilizability or stabilizability of a given subspace. These subspaces’ properties are detected through checking the existence of critical polynomials (which have roots on the unit circle of the complex plane) on their exposed edges. By omitting the undesired parts of the design space, the algorithm just searches the desired parts which are far smaller than the primary design space. This strategy improves the feasibility performance of the algorithm. Some illustrating examples are provided to show the steps and iterations of the design algorithm. Furthermore, one hundred random models are generated to evaluate the feasibility performance of the proposed algorithm as compared to some existing methods. The results reveal the superiority of the proposed algorithm.
Please check the attached file for information about the dataset.
Documentation
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Comments
The dataset shows the results of a new algorithm for output feedback design for polytopic discrete LTI systems. the approach is based on direct searching of the design space. The application of a similar method for continuous systems has been previously published in:
Abolpour, R., Dehghani, M. and Talebi, H.A., 2019. Output feedback controller for polytopic systems exploiting the direct searching of the design space. International Journal of Robust and Nonlinear Control, 29(15), pp.5164-5177.