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 899 articles )

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  1. Agarwal, Neha; Kar, Haranath: New results on saturation overflow stability of 2-D state-space digital filters (2016)
  2. Ahn, Choon Ki; Shi, Peng: Strict dissipativity and asymptotic stability of digital filters in direct form with saturation nonlinearity (2016)
  3. Ahn, Choon Ki; Wu, Ligang; Shi, Peng: Stochastic stability analysis for 2-D Roesser systems with multiplicative noise (2016)
  4. Amini, Amir; Azarbahram, Ali; Sojoodi, Mahdi: $H_\infty $ consensus of nonlinear multi-agent systems using dynamic output feedback controller: an LMI approach (2016)
  5. Boulaabi, Iskander; Sellami, Anis; Ben Hmida, Fayçal: Robust delay-derivative-dependent sliding mode observer for fault reconstruction: a diesel engine system application (2016)
  6. Farnam, Arash; Mahboobi Esfanjani, Reza: Improved linear matrix inequality approach to stability analysis of linear systems with interval time-varying delays (2016)
  7. 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)
  8. 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)
  9. Manfredi, Sabato: Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture (2016)
  10. Mukaidani, Hiroaki; Xu, Hua; Dragan, Vasile: Dynamic games for Markov jump stochastic delay systems (2016)
  11. Niamsup, P.; Phat, V.N.: Robust finite-time control for linear time-varying delay systems with bounded control (2016)
  12. Niamsup, P.; Phat, V.N.: A new result on finite-time control of singular linear time-delay systems (2016)
  13. Pourgholi, Mahdi; Boroujeni, Elham Amini: An iterative LMI-based reduced-order observer design for fractional-order chaos synchronization (2016)
  14. Ramasamy, S.; Nagamani, G.; Zhu, Quanxin: Robust dissipativity and passivity analysis for discrete-time stochastic T-S fuzzy Cohen-Grossberg Markovian jump neural networks with mixed time delays (2016)
  15. 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)
  16. Tan, Feng; Zhou, Bin; Duan, Guang-Ren: Finite-time stabilization of linear time-varying systems by piecewise constant feedback (2016)
  17. Tuan, Le A.; Phat, Vu N.: Finite-time stability and $H_\infty$ control of linear discrete-time delay systems with norm-bounded disturbances (2016)
  18. Veenman, Joost; Scherer, Carsten W.; Köroğlu, Hakan: Robust stability and performance analysis based on integral quadratic constraints (2016)
  19. Wang, Xiao-Lei; Yang, Guang-Hong; Li, Xiao-Jian: Fault detection filter design with varying gains for multi-delay uncertain systems (2016)
  20. Wang, Xin; She, Kun; Zhong, Shouming; Yang, Huilan: Further results on state estimation of neural networks with multiple time delays (2016)

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