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 534 articles , 1 standard article )

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Bavafa-Toosi, Yazdan: Introduction to linear control systems (2017)
  3. Benveniste, Albert; Bourke, Timothy; Caillaud, Benoit; Pagano, Bruno; Pouzet, Marc: A type-based analysis of causality loops in hybrid systems modelers (2017)
  4. Berger, Julien; Mendes, Nathan; Guernouti, Sihem; Woloszyn, Monika; Chinesta, Francisco: Review of reduced order models for heat and moisture transfer in building physics with emphasis in PGD approaches (2017)
  5. Brandstetter, Pavel; Kuchar, Martin: Sensorless control of variable speed induction motor drive using RBF neural network (2017)
  6. Carpiuc, Sabin-Constantin; Lazar, Corneliu: Modeling of synchronous electric machines for real-time simulation and automotive applications (2017)
  7. Chen, Mingshuai; Ravn, Anders P.; Wang, Shuling; Yang, Mengfei; Zhan, Naijun: A two-way path between formal and informal design of embedded systems (2017)
  8. Costello, Sean; François, Grégory; Bonvin, Dominique: Crosswind kite control -- a benchmark problem for advanced control and dynamic optimization (2017)
  9. Izadbakhsh, Alireza: A note on the “nonlinear control of electrical flexible-joint robots” (2017)
  10. Jino Joy; Ushakumari, S.: Performance comparison of a canonical switching cell with SPWM and SVPWM fed sensorless PMBLDC motor drive under conventional and fuzzy logic controllers (2017)
  11. Kharola, Ashwani; Patil, Pravin: A PID based ANFIS control of inverted pendulum climbing on inclined plane (2017)
  12. Klee, Harold; Allen, Randal: Simulation of dynamic systems with MATLAB and Simulink (2017)
  13. Landau, Ioan Doré; Airimiţoaie, Tudor-Bogdan; Castellanos-Silva, Abraham; Constantinescu, Aurelian: Adaptive and robust active vibration control. Methodology and tests (2017)
  14. Rahme, Sandy; Meskin, Nader; Mohammadpour, Javad: Adaptive sliding mode-based diagnosis of actuator faults for LPV systems (2017)
  15. Schweizer, Wolfgang: Simulating physical systems. Computational physics with MATLAB (2017)
  16. Tunç, Cemil; Mohammed, Sizar Abid: A remark on the stability and boundedness criteria in retarded Volterra integro-differential equations (2017)
  17. Yazgan, Ramazan; Tunç, Cemil; Atan, Özkan: On the global asymptotic stability of solutions to neutral equations of first order (2017)
  18. Zhao, Yecheng; Zeng, Haibo: An efficient schedulability analysis for optimizing systems with adaptive mixed-criticality scheduling (2017)
  19. Alaimo, A.; Artale, V.; Barbaraci, G.; Milazzo, C.L.R.; Orlando, C.; Ricciardello, A.: LQR-PID control applied to hexacopter flight (2016)
  20. Bayrak, Alper; Tatlicioglu, Enver: A novel online adaptive time delay identification technique (2016)

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