SCOTS: a tool for the synthesis of symbolic controllers. We introduce SCOTS a software tool for the automatic controller synthesis for nonlinear control systems based on symbolic models, also known as discrete abstractions. The tool accepts a differential equation as the description of a nonlinear control system. It uses a Lipschitz type estimate on the right-hand-side of the differential equation together with a number of discretization parameters to compute a symbolic model that is related with the original control system via a feedback refinement relation. The tool supports the computation of minimal and maximal fixed points and thus natively provides algorithms to synthesize controllers with respect to invariance and reachability specifications. The atomic propositions, which are used to formulate the specifications, are allowed to be defined in terms of finite unions and intersections of polytopes as well as ellipsoids. While the main computations are done in C++, the tool contains a Matlab interface to simulate the closed loop system and to visualize the abstract state space together with the atomic propositions. We illustrate the performance of the tool with two examples from the literature. The tool and all conducted experiments are available at

References in zbMATH (referenced in 15 articles )

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  1. Nejati, Ameneh; Soudjani, Sadegh; Zamani, Majid: Compositional abstraction-based synthesis for continuous-time stochastic hybrid systems (2021)
  2. Apaza-Perez, W. Alejandro; Combastel, Christophe; Zolghadri, Ali: On distributed symbolic control of interconnected systems under persistency specifications (2020)
  3. Neider, Daniel; Weinert, Alexander; Zimmermann, Martin: Synthesizing optimally resilient controllers (2020)
  4. Sinisi, Stefano; Alimguzhin, Vadim; Mancini, Toni; Tronci, Enrico; Mari, Federico; Leeners, Brigitte: Optimal personalised treatment computation through in silico clinical trials on patient digital twins (2020)
  5. Hsu, Kyle; Majumdar, Rupak; Mallik, Kaushik; Schmuck, Anne-Kathrin: Lazy abstraction-based controller synthesis (2019)
  6. Khaled, Mahmoud; Zamani, Majid: \textsfpFaces: an acceleration ecosystem for symbolic control (2019)
  7. Lavaei, Abolfazl; Soudjani, Sadegh; Zamani, Majid: Compositional construction of infinite abstractions for networks of stochastic control systems (2019)
  8. Meyer, Pierre-Jean; Devonport, Alex; Arcak, Murat: TIRA: toolbox for interval reachability analysis (2019)
  9. Swikir, Abdalla; Zamani, Majid: Compositional synthesis of finite abstractions for networks of systems: a small-gain approach (2019)
  10. Le Co├źnt, Adrien; Alexandre dit Sandretto, Julien; Chapoutot, Alexandre; Fribourg, Laurent: An improved algorithm for the control synthesis of nonlinear sampled switched systems (2018)
  11. Li, Yinan; Liu, Jun: ROCS: a robustly complete control synthesis tool for nonlinear dynamical systems (2018)
  12. Kim, Eric S.; Arcak, Murat; Seshia, Sanjit A.: Symbolic control design for monotone systems with directed specifications (2017)
  13. Liu, Jun: Robust abstractions for control synthesis: completeness via robustness for linear-time properties (2017)
  14. Zamani, Majid; Tkachev, Ilya; Abate, Alessandro: Towards scalable synthesis of stochastic control systems (2017)
  15. Rungger, Matthias; Zamani, Majid: SCOTS: a tool for the synthesis of symbolic controllers (2016)