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


References in zbMATH (referenced in 989 articles )

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  1. Korobov, V.I.; Lutsenko, A.V.: On the robust stabilization of one class of nonlinear discrete systems (2017)
  2. La-inchua, T.; Niamsup, P.; Liu, Xinzhi: Finite-time stability of large-scale systems with interval time-varying delay in interconnection (2017)
  3. Mazko, A.G.; Kusii, S.N.: Stabilization by a measurable output and estimation of the level of attenuation for perturbations in control systems (2017)
  4. Zhang, Hao; Wang, Xing-Yuan; Lin, Xiao-Hui: Stability and control of fractional chaotic complex networks with mixed interval uncertainties (2017)
  5. Agarwal, Neha; Kar, Haranath: New results on saturation overflow stability of 2-D state-space digital filters (2016)
  6. Ahn, Choon Ki; Shi, Peng: Strict dissipativity and asymptotic stability of digital filters in direct form with saturation nonlinearity (2016)
  7. Ahn, Choon Ki; Wu, Ligang; Shi, Peng: Stochastic stability analysis for 2-D Roesser systems with multiplicative noise (2016)
  8. Amini, Amir; Azarbahram, Ali; Sojoodi, Mahdi: $H_\infty $ consensus of nonlinear multi-agent systems using dynamic output feedback controller: an LMI approach (2016)
  9. Boulaabi, Iskander; Sellami, Anis; Ben Hmida, Fayçal: Robust delay-derivative-dependent sliding mode observer for fault reconstruction: a diesel engine system application (2016)
  10. Farnam, Arash; Mahboobi Esfanjani, Reza: Improved linear matrix inequality approach to stability analysis of linear systems with interval time-varying delays (2016)
  11. Gai, Mingjiu; Cui, Shiwei; Liu, Xiaolei: Stability analysis of a class of fractional-order neural networks (2016)
  12. Ghous, Imran; Huang, Shipei; Xiang, Zhengrong: State feedback $L_1$-gain control of positive 2-D continuous switched delayed systems via state-dependent switching (2016)
  13. Haidar, Ihab; Pasillas-Lépine, William; Chaillet, Antoine; Panteley, Elena; Palfi, Stéphane; Senova, Suhan: Closed-loop firing rate regulation of two interacting excitatory and inhibitory neural populations of the basal ganglia (2016)
  14. Lu, Chunge; Wang, Linshan: Robust exponential stability of impulsive reaction-diffusion neural networks with leakage time-varying delay (2016)
  15. Manfredi, Sabato: Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture (2016)
  16. Mukaidani, Hiroaki; Xu, Hua; Dragan, Vasile: Dynamic games for Markov jump stochastic delay systems (2016)
  17. Muoi, N.H.; Rajchakit, G.; Phat, V.N.: LMI approach to finite-time stability and stabilization of singular linear discrete delay systems (2016)
  18. Niamsup, P.; Phat, V.N.: Robust finite-time control for linear time-varying delay systems with bounded control (2016)
  19. Niamsup, P.; Phat, V.N.: A new result on finite-time control of singular linear time-delay systems (2016)
  20. Pourgholi, Mahdi; Boroujeni, Elham Amini: An iterative LMI-based reduced-order observer design for fractional-order chaos synchronization (2016)

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