Good Resilient Observes in literature and my resilent observers will be tested here.

If you use the codes, please cite

@INPROCEEDINGS{9482913,  
   author={Zheng, Yu and Anubi, Olugbenga Moses},  
   booktitle={2021 American Control Conference (ACC)},   
   title={Attack-Resilient Weighted $\ell_{1}$ Observer with Prior Pruning},  
   year={2021},  
   volume={},  
   number={},  
   pages={340-345},  
   doi={10.23919/ACC50511.2021.9482913}}

Or:

@incollection{zheng2022resilient,
  title={Resilient Observer Design for Cyber-Physical Systems with Data-Driven Measurement Pruning},
  author={Zheng, Yu and Anubi, Olugbenga Moses},
  booktitle={Security and Resilience in Cyber-Physical Systems: Detection, Estimation and Control},
  pages={85--117},
  year={2022},
  publisher={Springer}
}

Any questions, please contact Yu Zheng ([email protected]).

System_model_discrete_2021.slx

All parts (in blue blocks) are modulized, you will not have trouble to use them seperately.

Please refer to "run_model.m" for parameter settings, "System_model_discrete_2021.slx" for the exmaples of the usage of observers.

Fawzi, Hamza, Paulo Tabuada, and Suhas Diggavi. "Secure estimation and control for cyber-physical systems under adversarial attacks." IEEE Transactions on Automatic control 59.6 (2014): 1454-1467.

Parameter preparison: Resilent_Optimizer/opti_params.m
Solver: Resilent_Optimizer/solver_call_unc.m
Usage example: System_model_discrete_2021.slx/Unconstrained l1-based Observer

• Lu, An-Yang, and Guang-Hong Yang. "Secure state estimation for cyber-physical systems under sparse sensor attacks via a switched Luenberger observer." Information sciences 417 (2017): 454-464.
  
• Shoukry, Yasser, and Paulo Tabuada. "Event-triggered state observers for sparse sensor noise/attacks." IEEE Transactions on Automatic Control 61.8 (2015): 2079-2091.

Parameter preparison: Resilent_Optimizer/ETLO_params.m
Solver: Resilent_Optimizer/solver_event_luenburger.m
Usage example: System_model_discrete_2021.slx/Event-triggered Luenburger Observer

• Anubi, Olugbenga Moses, and Charalambos Konstantinou. "Enhanced resilient state estimation using data-driven auxiliary models." IEEE Transactions on Industrial Informatics 16.1 (2019): 639-647.
• Anubi, Olugbenga Moses, et al. "Multi-Model Resilient Observer under False Data Injection Attacks." 2020 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2020.

Parameter preparison: Resilent_Optimizer/opti_params.m
Solver: Resilent_Optimizer/solver_call.m
Usage example: System_model_discrete_2021.slx/Multi-model Observer

• Yu Zheng, et al. "Attack-Resilient Weighted L1 Observer with Prior Pruning". 2021 American Control Conference. (can be found in papers folder)
• Zheng, Yu, and Olugbenga Moses Anubi. "Resilient Observer Design for Cyber-Physical Systems with Data-Driven Measurement Pruning." Security and Resilience in Cyber-Physical Systems: Detection, Estimation and Control. Cham: Springer International Publishing, 2022. 85-117.

Parameter preparison: Resilent_Optimizer/opti_params.m
Solver: Resilent_Optimizer/Weighted_L1_solver.m
Pruning algorithm: Resilent_Optimizer/pruning_algorithm.m (reliable_num_attacks.m, pmf_PB.m)
Usage example: System_model_discrete_2021.slx/Weighted l1-based Observer with pruning

Estimation error (LO: luenburger observer, UL1O: unconstrained L1 decoder, MMO: multi-models observer, ETLO: event triggered Luengbuger observer, RPO: Resilient Pruning Observer)

Nakahira, Yorie, and Yilin Mo. "Attack-Resilient H_2, H_\infty, and L1 State Estimator." IEEE Transactions on Automatic Control 63.12 (2018): 4353-4360.

Parameter preparison: Resilent_Optimizer/opti_params.m
Solver: Resilent_Optimizer/local_estimate.m
Usage example: System_model_discrete_2021.slx/H_2 Observer

This one need more tests, current version fails under attack

Chong, Michelle S., Masashi Wakaiki, and Joao P. Hespanha. "Observability of linear systems under adversarial attacks." 2015 American Control Conference (ACC). IEEE, 2015.

Shoukry, Yasser, et al. "Secure state estimation for cyber-physical systems under sensor attacks: A satisfiability modulo theory approach." IEEE Transactions on Automatic Control 62.10 (2017): 4917-4932.

add real ML localization algorithm, below is the precision of the generated support prior

The updated comparison result:

The performance of designed FDIA: