LMI toolbox
Linear Matrix Inequalities (LMIs) and LMI techniques have emerged as powerful design tools in areas ranging from control engineering to system identification and structural design. The LMI Control Toolbox implements state-of-the-art interior-point LMI solvers. While these solvers are significantly faster than classical convex optimization algorithms, it should be kept in mind that the complexity of LMI computations remains higher than that of solving, say, a Riccati equation. For instance, problems with a thousand design variables typically take over an hour on today’s workstations. However, research on LMI optimization is still very active and substantial speed-ups can be expected in the future. Thanks to its efficient “structured” representation of LMIs, the LMI Control Toolbox is geared to making the most out of such improvements
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References in zbMATH (referenced in 864 articles )
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Sorted by year (- Ahn, Choon Ki; Shi, Peng: Strict dissipativity and asymptotic stability of digital filters in direct form with saturation nonlinearity (2016)
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- Sharma, V.; Agrawal, V.; Sharma, B.B.; Nath, R.: Unknown input nonlinear observer design for continuous and discrete time systems with input recovery scheme (2016)
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- Tuan, Le A.; Phat, Vu N.: Finite-time stability and $H_\infty$ control of linear discrete-time delay systems with norm-bounded disturbances (2016)
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- Buzachero, L.F.S.; Assunção, E.; Teixeira, M.C.M.; da Silva, E.R.P.: Less conservative optimal robust control of a 3-DOF helicopter (2015)
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- Chen, Shyh-Feng: Stability analysis and stabilization of 2-D singular Roesser models (2015)
- Dong, Xin-Zhuang; Xiao, Mingqing: D-admissible hybrid control of a class of singular systems (2015)