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 625 articles , 1 standard article )

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Adamatzky, Andrew (ed.); Akl, Selim G. (ed.); Sirakoulis, Georgios Ch. (ed.): From parallel to emergent computing (2019)
  3. Altun, Yener; Tunç, Cemil: On the estimates for solutions of a nonlinear neutral differential system with periodic coefficients and time-varying lag (2019)
  4. Báez-López, José Miguel David; Báez Villegas, David Alfredo: MATLAB handbook with applications to mathematics, science, engineering, and finance (2019)
  5. Ebrahimpanah, Shahrouz; Chen, Qihong; Zhang, Liyan; Adam, Misbawu: Model predictive voltage control with optimal duty cycle for three-phase grid-connected inverter (2019)
  6. Keviczky, László; Bars, Ruth; Hetthéssy, Jenő; Bányász, Csilla: Control engineering: MATLAB exercises (2019)
  7. Keviczky, László; Bars, Ruth; Hetthéssy, Jenő; Bányász, Csilla: Control engineering (2019)
  8. Tunç, Cemil: On the properties of solutions for a system of nonlinear differential equations of second order (2019)
  9. 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)
  10. 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)
  11. Amat, Sergio; Legaz, M. José: On differential singular perturbation problems: a simple variational approach (2018)
  12. Azar, Ahmad Taher (ed.); Radwan, Ahmed (ed.); Vaidyanathan, Sundarapandian (ed.): Techniques of fractional order systems (2018)
  13. Bratishchev, Aleksandr Vasil’evich: Factorization of the characteristic polynomial of the equilibrium state for an autonomous system having an attracting invariant manifold (2018)
  14. Chen, Xue-wen; Zhou, Yue: Modelling and analysis of automobile vibration system based on fuzzy theory under different road excitation information (2018)
  15. Das, Raja; Reddy, Madhu Sudan: Application of recurrent neural network using MATLAB Simulink in medicine (2018)
  16. Douanla, Rostand Marc; Kenné, Godpromesse; Pelap, François Béceau; Fotso, Armel Simo: A modified RBF neuro-sliding mode control technique for a grid connected PMSG based variable speed wind energy conversion system (2018)
  17. Fernández-Cara, Enrique; Prouvée, Laurent: Optimal control of mathematical models for the radiotherapy of gliomas: the scalar case (2018)
  18. Jia, Zirui; Liu, Chongxin: Fractional-order modeling and simulation of magnetic coupled boost converter in continuous conduction mode (2018)
  19. Jordan Jalving, Yankai Cao, Victor M. Zavala: Graph-Based Modeling and Simulation of Complex Systems (2018) arXiv
  20. Klee, Harold; Allen, Randal: Simulation of dynamic systems with MATLAB and Simulink (2018)

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