Approximation-free Control for Signal Temporal Logic Specifications using Spatiotemporal Tubes
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This paper presents a spatiotemporal tube (STT)-based control framework for satisfying Signal Temporal Logic (STL) specifications in unknown control-affine systems. We formulate STL constraints as a robust optimization problem (ROP) and recast it as a scenario optimization program (SOP) to construct STTs with formal correctness guarantees. We also propose a closed-form control law that operates independently of the system dynamics, and ensures the system trajectory evolves within the STTs, thereby satisfying the STL specifications. The proposed approach is validated through case studies and comparisons with state-of-the-art methods, demonstrating superior computational efficiency, trajectory quality, and applicability to complex STL tasks.
Ratnangshu Das, Subhodeep Choudhury, Pushpak Jagtap• 2025
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| STL Task Control | stlfrag 1 | Total Computation Time (s)0.414 | 6 | |
| STL Task Control | stlfrag 2 | Total Computation Time (s)0.156 | 6 | |
| STL Task Control | stlcg 1 | Total Computation Time (s)28.504 | 5 | |
| STL Task Control | stlcg 2 | Total Computation Time (s)7.589 | 5 | |
| STL-constrained control | stlcg-1 without disturbance nominal scenario | Max Control Input1.2658 | 4 | |
| STL-constrained control | stlfrag-1 without disturbance (nominal scenario) | Max Control Input1.2937 | 4 | |
| STL-constrained control | stlcg-1 with disturbance perturbed scenario | Max Control Input7.1901 | 2 | |
| STL-constrained control | stlfrag with disturbance perturbed scenario 1 | Max Control Input10.6582 | 2 |
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