SReachTools is a MATLAB toolbox to tackle various problems in stochastic reachability. Currently, the toolbox can perform verification and (open-loop or affine disturbance-feedback) controller synthesis for linear (time-varying/time-invariant) systems with additive (Gaussian/non-Gaussian) disturbance. By verification, we are referring to the problem of stochastic reachability of a target tube. Our project website is at https://sreachtools.github.io.

This is an area of active research, and this toolbox will attempt to cater certain classes of problems.

We aim to support the following problems:

• Stochastic reachability of a target tube (guaranteeing safety for stochastic systems to lying in a collection of time-varying safe sets while satisfying input bounds):
  • This problem subsumes existing work on terminal hitting stochastic reach-avoid problems as well as stochastic viability problems. We implement a dynamic programming solution, limited to 3-dimensional LTI systems using SReachDynProg.
  • Open-loop controller synthesis using SReachPoint (admissible controller satisfying hard control bounds with maximum safety probability):
    • chance-open: Chance constraint formulation solved via linear programming
    • genzps-open: Fourier transforms-based compuation (Genz's algorithm + patternsearch)
    • particle-open: Particle control approach (mixed-integer linear program approach)
    • voronoi-open: Voronoi partition-based undersampled particle control approach (mixed-integer linear program approach)
  • Affine controller synthesis using SReachPoint (admissible controller with chance constrained input bounds with maximum safety probability):
    • chance-affine: Chance constraint formulation solved via difference-of-convex programming (risk allocation and controller synthesis performed simultaneously)
    • chance-affine-uni: Chance constraint formulation solved via bisection for uniform risk allocation and second order cone programs for controller synthesis (risk allocation and controller synthesis performed separately)
  • Stochastic reach set computation using SReachSet (set of initial states from which an admissible controller exists such that the probability of safety is above a given threshold):
    • chance-open: Chance constraint-based under-approximation
    • genzps-open: Fourier transforms-based under-approximation
    • lag-over/lag-under: Lagrangian methods-based over- and under-approximation
• Forward stochastic reachability using SReachFwd (characterizing the stochasticity of the state at a future time of interest):
  • state-stoch/concat-stoch: Stochasticity of the state or the concatenated state vector
  • state-prob/concat-prob: Probability of the state or the concatenated state vector lying in a target set or a tube respectively

Do check our project blog for updates!

For easy start, we have cataloged in our project webpage a number of relevant, easy-to-follow examples. These are also part of the repository (see examples/*.m).

Further, you can see SReachTools in action at Code Ocean. Check out https://codeocean.com/explore/capsules/?query=SReachTools.

We will denote MATLAB's command prompt by >>, while the system command prompt by $ .

External dependencies of SReachTools are:

1. MATLAB's Statistics and Machine Learning Toolbox
2. MPT3 (https://www.mpt3.org/)
3. CVX (http://cvxr.com/cvx/)
4. MATLAB's Global Optimization Toolbox (optional)
5. MATLAB's Optimization Toolbox (optional)
6. GeoCalcLib (https://github.com/sreachtools/GeoCalcLib) (optional)
7. GUROBI (optional)
8. MOSEK (optional)

These dependencies are platform-independent, and have been tested in Windows, MacOS, and Linux.

1. MATLAB (>2017a) with MATLAB's Statistics and Machine Learning Toolbox
2. MPT3 (https://www.mpt3.org/) --- for polytopic computational geometry
   1. Copy the MATLAB script install_mpt3.m provided by MPT3 from the browser to your local computer.
   2. Download and install MPT3 by running the following command in MATLAB's command prompt (after changing directory to the folder containing install_mpt3.m)

      >> install_mpt3
      

   3. Add cd <PATH-TO-TBXMANAGER>;tbxmanager restorepath to your MATLAB startup script for the MPT3 installation to persist across MATLAB runs.
3. CVX (http://cvxr.com/cvx/) --- for parsing convex and mixed-integer programs. Use the Standard bundles, including Gurobi and/or MOSEK, even if you do not plan to use Gurobi or MOSEK. CVX does not require any additional licenses to work with GUROBI or MOSEK in an academic setting.
   1. Download the zip file from http://cvxr.com/cvx/download/, and extract it to the cvx folder.
   2. Install CVX by running the following command in MATLAB's command prompt (after changing the current working directory to the cvx folder)

      >> cvx_setup
      

   3. Add cd <PATH-TO-CVX>;cvx_setup to your MATLAB startup script for the CVX installation to persist across MATLAB runs.
   4. Other notes:
      • Detailed installation instructions are given in http://cvxr.com/cvx/download/.
      • SDPT3 (the default backend solver of CVX) performs reasonably well with CVX, when compared to MOSEK, and significantly poorly when compared to GUROBI in the tested examples and CVX v2.1 version. See Step 5 for instructions in installing external solvers for SReachTools.

These dependencies will allow non-essential features of SReachTools or enable superior performance.

1. MATLAB's Global Optimization Toolbox and Optimization Toolbox
   • Affects genzps-open options in SReachPoint and SReachSet computation.
2. GeoCalcLib --- a MATLAB interface to Avis's LRS vertex-facet enumeration library. In empirical tests, we found LRS to be a superior alternative to MPT's preferred approach for vertex-facet enumeration, CDD.
   • Affects lag-over and lag-under options in SReachSet computation.
   • See https://github.com/sreachtools/GeoCalcLib for detailed installation instructions.
   • ⚠️ GeoCalcLib currently works only in Unix and MAC OS.
3. External solvers --- GUROBI and/or MOSEK.
   1. Why do we need to install external solvers?
      • Mixed-integer programming enabled by GUROBI or MOSEK is required for particle-based approaches in SReachPoint.
        • Affects voronoi-open and particle-open options in SReachPoint computation.
      • External solvers are typically more numerically robust and computationally faster than free solvers like SDPT3 that come with CVX.
        • Affects overall computation speed and solution quality.
   2. GUROBI (http://www.gurobi.com/): A backend solver for CVX that also enables mixed-integer programming associated with particle-based approaches, apart from convex programming. MPT3 + GUROBI also provides robust polyhedral computation. (:warning: Currently facing issues).
      1. GUROBI offers free academic license, which can be requested at http://www.gurobi.com/registration/download-reg.
      2. MPT3 + GUROBI: Requires the external installation.
         1. Obtain a copy of GUROBI Optimizer from http://www.gurobi.com/ (Requires signing up)
         2. Unzip the installation to desired folder.
         3. Generate the license file by running the following command in the Unix command prompt (after changing the current working directory to the <PATH-TO-GUROBI-HOME>/gurobi902/<OS>/bin/)

            $ grbgetkey OUTPUT_OF_GUROBI_LICENSE_REQUEST
            

         4. Setup GUROBI by running the following command in MATLAB's command prompt (after changing the current working directory to <PATH-TO-GUROBI-HOME>/gurobi902/<OS>/matlab/)

            >> gurobi_setup
            

         5. Add GRB_LICENSE_FILE environment variable that has the location of the gurobi.lic file for MPT3 to detect GUROBI. Alternatively, add the following command in startup.m

            >> setenv('GRB_LICENSE_FILE','/home/ubuntu/gurobi.lic')
            

         6. Update MPT3 with GUROBI by running the following command in MATLAB's command prompt

            >> mpt_init
            

      3. CVX + GUROBI: The current build of CVX v2.2 does not play well with GUROBI v9.0.2. (:warning: Currently facing issues)
         • Previously, CVX v2.1 worked with GUROBI v7.5.2 successfully. We will update these instructions once CVX + GUROBI becomes a viable option again.
         • See the following CVX forum posts for more details:
           1. http://ask.cvxr.com/t/cvx-with-gurobi-error-warning/7072
           2. http://ask.cvxr.com/t/mismangement-of-matlab-path-in-cvxv2-2-and-external-gurobi-v9-0-2/7346/3
         • We found CVX + GUROBI to be faster than SDPT3 and MOSEK
   3. MOSEK (https://www.mosek.com/): A backend solver for CVX that also enables mixed-integer programming associated with particle-based approaches, apart from convex programming.
      1. MOSEK offers free academic license, which can be requested at https://www.mosek.com/license/request/.
      2. CVX + MOSEK:
         1. Save the license file obtained via email in your home folder in a folder named mosek. See https://docs.mosek.com/9.2/licensing/quickstart.html for more details.
         2. To enable MOSEK bundled with CVX, run the following command in MATLAB command prompt

            >> cvx_setup
            

         3. See http://web.cvxr.com/cvx/doc/mosek.html for more details.
      3. MPT3 + MOSEK: Unfortunately, MPT3 does not support MOSEK. See https://www.mpt3.org/Main/FAQ.
      4. In empirical tests, SDPT3 and MOSEK have demonstrated similar performance in computation time and solution quality. We found MOSEK to be slower than GUROBI.

1. Install the necessary dependencies listed above
2. Clone the SReachTools repository (or download the latest zip file from Releases)

   $ git clone https://github.com/sreachtools/SReachTools
   

   ⚠️ Please do not add the folder to the MATLAB path manually.

3. Install SReachTools by running the following command in MATLAB command prompt (after changing the current working directory in MATLAB to SReachTools folder)

   >> srtinit
   

   • (Optional) Additional steps:
     • Run srtinit -t to run all the unit tests.
     • Run srtinit -v to visualize the steps the changes to the path and check for recommended dependencies.
     • Run srtinit -x to remove functions of SReachTools from MATLAB's path after use.
4. You can add cd <PATH-TO-SREACHTOOLS>;srtinit to your MATLAB's startup.m to automatically have this done in future.

SReachTools is an open-source MATLAB toolboxes. We welcome feedback, issues, bug-fixes, and other enhancements. Please see our contribution guidelines of this project to know more on how you can help us.

The Stochastic Reachability Toolbox (SReachTools) is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this toolbox (see LICENSE). If not, see https://www.gnu.org/licenses/.

It is the user's responsibility in assessing the correctness of the theory and software implementation before putting it to use in their own research or exploiting the results commercially. We are, however, very happy to answer any questions and investigate any bug reports.

This toolbox was developed by Abraham P. Vinod and Joseph D. Gleason, under the supervision of Prof. Meeko Oishi.

If this toolbox comes handy in your research, please consider citing our work. A copy of this paper is available in the repository.

IEEE citation style:

A. P. Vinod, J. D. Gleason, and M. M. K. Oishi. "SReachTools: A MATLAB Stochastic Reachability Toolbox," In Proceedings of the International Conference on Hybrid Systems: Computation and Control, Montreal, Canada, April 16--18, 2019. https://sreachtools.github.io.

BibTeX entry for use in LaTeX with \usepackage{url}:

@misc{SReachTools,
    author    = {Vinod, Abraham P. and Gleason, Joseph D. and Oishi, Meeko M. K.},
    title     = {{S}{R}each{T}ools: A {MATLAB} {S}tochastic {R}eachability {T}oolbox},
    booktitle = {Proceedings of the International Conference on Hybrid Systems: Computation and Control},
    year      = {2019},
    address   = {Montreal, Canada},
    month     = {April 16--18},
    note      = {\url{https://sreachtools.github.io}}
}

As seen from the installation instructions, this toolbox leverages several existing toolboxes and third-party codes:

1. MPT3 developed by M. Herceg, M. Kvasnica, C.N. Jones, and M. Morari, along with their dependencies.
2. CVX developed by Michael Grant and Stephen Boyd
3. GeoCalcLib developed by Rainer Schaich.
4. An algorithm for numerical computation of multivariate normal distribution values developed by Alan Genz (Distributed with SReachTools under its appropriate license).
5. allcomb.m developed by Jos van der Geest (Distributed with SReachTools under its appropriate license).

When available, we also use commercial toolboxes from MATLAB and Gurobi.