AMD - Toolbox for computing separating input in set-membership identification of affine systems

This is the code of active model discrimination (AMD) that computes the separating input for set-membership identification of affine systems. Please refer to the reference:

Ding, Y., Harirchi F., Yong, S. Z., Jacobsen, E., and Ozay, N. (2018). Optimal input design for affine model discrimination with applications in intention-aware vehicles, in Proceedings of the 9th ACM/IEEE International Conference on Cyber-Physical Systems, PP. 297-307, arXiv:1702.01112.

List of capabilities:

• Driver intention estimation for two driving scenarios: lane changing and intersection crossing
• Concatenate the affine dynamics over a finite horizon and a finite number of model/member pairs
• Convert semi-infinite constraint to linear constraint by leveraging robust optimization
• Implement double negation to find equivalence of the (non-convex) separability condition
• Solve a mixed integer linear program (MILP) to get the separating input for set-membership identification
  • Polyhedral constraints on input, controlled state, noise
• Compare with previous work
  • Harirchi F., Yong, S. Z., Jacobsen E., and Ozay, N. (2017). Active mode discrimination with applications to fraud
    detection in smart buildings. IFAC-PapersOnLine, 50(1):9527-9534.

Requirements

• Matlab 2018b
• Optimizaiton modeling toolbox, Yalmip (https://yalmip.github.io/download/)
• Solver: Gurobi 7.5.2 for solving LP and supporting SOS-1 constraint (https://www.gurobi.com/)

Notes

• Gurobi 8.1.1 may result in infeasible sultion for intersection crossing scenario.