Simulink® is an environment for multidomain simulation and Model-Based Design for dynamic and embedded systems. It provides an interactive graphical environment and a customizable set of block libraries that let you design, simulate, implement, and test a variety of time-varying systems, including communications, controls, signal processing, video processing, and image processing. Simulink is integrated with MATLAB®, providing immediate access to an extensive range of tools that let you develop algorithms, analyze and visualize simulations, create batch processing scripts, customize the modeling environment, and define signal, parameter, and test data.

References in zbMATH (referenced in 640 articles , 1 standard article )

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Bhaumik, Shovan; Date, Paresh: Nonlinear estimation. Methods and applications with deterministic sample points (2020)
  3. Adamatzky, Andrew (ed.); Akl, Selim G. (ed.); Sirakoulis, Georgios Ch. (ed.): From parallel to emergent computing (2019)
  4. Altun, Yener; Tunç, Cemil: On the estimates for solutions of a nonlinear neutral differential system with periodic coefficients and time-varying lag (2019)
  5. Báez-López, José Miguel David; Báez Villegas, David Alfredo: MATLAB handbook with applications to mathematics, science, engineering, and finance (2019)
  6. Biçer, Emel; Tunç, Cemil: On the asymptotic stability behaviours of solutions of nonlinear differential equations with multiple variable advanced arguments (2019)
  7. Chen, Gang; Li, Zhiyong; Wei, Mengli: Distributed fixed-time secondary coordination control of islanded microgrids (2019)
  8. Ebrahimpanah, Shahrouz; Chen, Qihong; Zhang, Liyan; Adam, Misbawu: Model predictive voltage control with optimal duty cycle for three-phase grid-connected inverter (2019)
  9. Guezmil, Amal; Berriri, Hanen; Pusca, Remus; Sakly, Anis; Romary, Raphael; Mimouni, Mohamed Faouzi: High order sliding mode observer-based backstepping fault-tolerant control for induction motor (2019)
  10. Karsenty, Avi; Mandelbaum, Yaakov: Computer algebra challenges in nanotechnology: accurate modeling of nanoscale electro-optic devices using finite elements method (2019)
  11. Keviczky, László; Bars, Ruth; Hetthéssy, Jenő; Bányász, Csilla: Control engineering (2019)
  12. Keviczky, László; Bars, Ruth; Hetthéssy, Jenő; Bányász, Csilla: Control engineering: MATLAB exercises (2019)
  13. Kim, Kwangmin; Kim, Minji; Kim, Dongmok; Lee, Dongjun: Modeling and velocity-field control of autonomous excavator with main control valve (2019)
  14. Li, Xiaojing; Wu, Aiguo; Zhang, Zhaolong: Immersion and invariance modular nonlinear tracking control for an underactuated quadrotor (2019)
  15. Lungu, Mihai; Lungu, Romulus: Adaptive neural network-based satellite attitude control by using the dynamic inversion technique and a VSCMG pyramidal cluster (2019)
  16. Tunç, Cemil: On the properties of solutions for a system of nonlinear differential equations of second order (2019)
  17. Uddin, Mohammad Monir: Computational methods for approximation of large-scale descriptor systems (2019)
  18. Xu, Dezhi; Dai, Yuchen; Yang, Chengshun; Yan, Xinggang: Adaptive fuzzy sliding mode command-filtered backstepping control for islanded PV microgrid with energy storage system (2019)
  19. Yang, Chunyu; Xu, Yiming; Dai, Wei; Zhou, Linna: Two-time-scale composite control of flexible manipulators (2019)
  20. Yin, Yanli; Ran, Yan; Zhang, Liufeng; Pan, Xiaoliang; Luo, Yong: An energy management strategy for a super-mild hybrid electric vehicle based on a known model of reinforcement learning (2019)

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