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 721 articles , 1 standard article )

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  1. Shafai, Bahram: System identification and adaptive control (to appear) (2024)
  2. Alshabeeb, Israa Ali; Ali, Nidaa Ghalib: Optimization of fuzzy inference system based on particle swarm optimization to enhance the efficiency of system (2021)
  3. Rolf Bork, Jonathan Hanks, David Barker, Joseph Betzwieser, Jameson Rollins, Keith Thorne, Erik von Reis: advligorts: The Advanced LIGO real-time digital control and data acquisition system (2021) not zbMATH
  4. Abhyankar, Shrirang; Betrie, Getnet; Maldonado, Daniel Adrian; Mcinnes, Lois C.; Smith, Barry; Zhang, Hong: PETSc DMNetwork: a library for scalable network PDE-based multiphysics simulations (2020)
  5. Altun, Yener: Improved results on the stability analysis of linear neutral systems with delay decay approach (2020)
  6. Altun, Yener; Tunç, Cemil: On the asymptotic stability of a nonlinear fractional-order system with multiple variable delays (2020)
  7. Angermann, Anne; Beuschel, Michael; Rau, Martin; Wohlfarth, Ulrich: MATLAB -- Simulink -- Stateflow. Foundations, toolboxes, examples (2020)
  8. Bhaumik, Shovan; Date, Paresh: Nonlinear estimation. Methods and applications with deterministic sample points (2020)
  9. Bruni, Stefano; Meijaard, J. P.; Rill, Georg; Schwab, A. L.: State-of-the-art and challenges of railway and road vehicle dynamics with multibody dynamics approaches (2020)
  10. Chaudhry, Afraz Mehmood; Arshad Uppal, Ali; Alsmadi, Yazan M.; Bhatti, Aamer Iqbal; Utkin, Vadim I.: Robust multi-objective control design for underground coal gasification energy conversion process (2020)
  11. Cheng, Shuo; Li, Chen-feng; Chen, Xiang; Li, Liang; Wu, Xiu-heng; Fan, Zhi-xian: A hierarchical estimation scheme of tire-force based on random-walk SCKF for vehicle dynamics control (2020)
  12. Dang, Chaoliang; Tong, Xiangqian; Song, Weizhang: Sliding-mode control in dq-frame for a three-phase grid-connected inverter with LCL-filter (2020)
  13. Fraser, Douglas; Giaquinta, Ruben; Hoffmann, Ruth; Ireland, Murray; Miller, Alice; Norman, Gethin: Collaborative models for autonomous systems controller synthesis (2020)
  14. Hoffmann, Josef; Quint, Franz: Multi-rate signal processing, filter banks and wavelets. Explained comprehensibly with MATLAB / Simulink (2020)
  15. Kumar, Niteen; Majumdar, Rudrodip; Singh, Suneet: Predictor-corrector nodal integral method for simulation of high Reynolds number fluid flow using larger time steps in Burgers’ equation (2020)
  16. Laoprom, Ittipon; Tunyasrirut, Satean: Design of PI controller for voltage controller of four-phase interleaved boost converter using particle swarm optimization (2020)
  17. Lhachimi, Hicham; Sayouti, Yassine; El Kouari, Youssef: Control of a flexible microgrid during both modes of operations with presence of nonlinear loads (2020)
  18. Lin, Xinyou; Li, Xuefan; Shen, Ying; Li, Hailin: Charge depleting range dynamic strategy with power feedback considering fuel-cell degradation (2020)
  19. Li, Ruobing; Zhu, Quanmin; Kiely, Janice; Zhang, Weicun: Algorithms for U-model-based dynamic inversion (UM-dynamic inversion) for continuous time control systems (2020)
  20. Malik, Avinash; Roop, Partha: A dynamic quantized state system execution framework for hybrid automata (2020)

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