Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
158 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Barrier States Theory for Safety-Critical Multi-Objective Control (2310.07022v2)

Published 10 Oct 2023 in eess.SY and cs.SY

Abstract: Multi-objective safety-critical control entails a diligent design to avoid possibly conflicting scenarios and ensure safety. This paper addresses multi-objective safety-critical control through a novel approach utilizing barrier states (BaS) to integrate safety into control design. It introduces the concept of safety embedded systems, where the safety condition is integrated with barrier functions to characterize a dynamical subsystem that is incorporated into the original model for control design. This approach reformulates the control problem to focus on designing a control law for an unconstrained system, ensuring that the barrier state remains bounded while achieving other performance objectives. The paper demonstrates that designing a stabilizing controller for the safety embedded system guarantees the safe stabilization of the original safety-critical system, effectively mitigating conflicts between performance and safety constraints. This approach enables the use of various legacy control methods from the literature to develop safe control laws. Moreover, it explores how this method can be applied to enforce input constraints and extend traditional control techniques to incorporate safety considerations. Additionally, the paper introduces input-to-state safety (ISSf) through barrier states for analyzing robust safety under bounded input disturbances and develops the notion of input-to-state safe stability (IS$3$) for analyzing and designing robustly safe stabilizing feedback controls. The proposed techniques and concepts are used in various examples including the design of proportional-integral-derivative-barrier (PIDB) control for adaptive cruise control.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (56)
  1. Franco Blanchini “Set invariance in control” In Automatica 35.11 Elsevier, 1999, pp. 1747–1767
  2. Hassan K Khalil “Nonlinear systems” Prentice Hall, 2002
  3. Derong Liu and Anthony N Michel “Dynamical systems with saturation nonlinearities: analysis and design” Springer, 1994
  4. “Constrained model predictive control: Stability and optimality” In Automatica 36.6 Elsevier, 2000, pp. 789–814
  5. David Q Mayne “Model predictive control: Recent developments and future promise” In Automatica 50.12 Elsevier, 2014, pp. 2967–2986
  6. “Differential dynamic programming technique for constrained optimal control” In Computational Mechanics 9.1 Springer, 1991, pp. 27–40
  7. Dimitri Bertsekas “Dynamic programming and optimal control: Volume I” Athena scientific, 2012
  8. “Nonlinear tracking control in the presence of state and control constraints: a generalized reference governor” In Automatica 38.12 Elsevier, 2002, pp. 2063–2073
  9. Ilya Kolmanovsky, Emanuele Garone and Stefano Di Cairano “Reference and command governors: A tutorial on their theory and automotive applications” In 2014 American Control Conference, 2014, pp. 226–241 IEEE
  10. Hassan Almubarak, Nader Sadegh and Evangelos A. Theodorou “Safety Embedded Control of Nonlinear Systems via Barrier States” In IEEE Control Systems Letters 6, 2022, pp. 1328–1333
  11. “Safety Embedded Differential Dynamic Programming using Discrete Barrier States” In IEEE Robotics and Automation Letters 7.2, 2022, pp. 2755–2762
  12. Hassan Almubarak, Evangelos A Theodorou and Nader Sadegh “Barrier States Embedded Iterative Dynamic Game for Robust and Safe Trajectory Optimization” In Accepted to American Control Conference (ACC) 2022., 2021
  13. “Lectures on modern convex optimization”, 2020
  14. JA Snyman, C Frangos and Y Yavin “Penalty function solutions to optimal control problems with general constraints via a dynamic optimisation method” In Computers & Mathematics with Applications 23.11 Elsevier, 1992, pp. 47–55
  15. Brian C Fabien “An extended penalty function approach to the numerical solution of constrained optimal control problems” In Optimal Control Applications and Methods 17.5 Wiley Online Library, 1996, pp. 341–355
  16. “Exact penalty function approach to constrained optimal control problems” In Optimal Control Applications and Methods 10.2 Wiley Online Library, 1989, pp. 173–180
  17. Murad Abu-Khalaf and Frank L Lewis “Nearly optimal state feedback control of constrained nonlinear systems using a neural networks HJB approach” In Annual Reviews in Control 28.2 Elsevier, 2004, pp. 239–251
  18. “A barrier function method for the optimization of trajectory functionals with constraints” In Proceedings of the 45th IEEE Conference on Decision and Control, 2006, pp. 864–869 IEEE
  19. Paul Malisani, François Chaplais and Nicolas Petit “An interior penalty method for optimal control problems with state and input constraints of nonlinear systems” In Optimal Control Applications and Methods 37.1 Wiley Online Library, 2016, pp. 3–33
  20. Stephen Prajna “Barrier certificates for nonlinear model validation” In 42nd IEEE International Conference on Decision and Control (IEEE Cat. No. 03CH37475) 3, 2003, pp. 2884–2889 IEEE
  21. Mitio Nagumo “Über die lage der integralkurven gewöhnlicher differentialgleichungen” In Proceedings of the Physico-Mathematical Society of Japan. 3rd Series 24 THE PHYSICAL SOCIETY OF JAPAN, The Mathematical Society of Japan, 1942, pp. 551–559
  22. “Safety verification of hybrid systems using barrier certificates” In International Workshop on Hybrid Systems: Computation and Control, 2004, pp. 477–492 Springer
  23. Stephen Prajna, Ali Jadbabaie and George J Pappas “Stochastic safety verification using barrier certificates” In 2004 43rd IEEE conference on decision and control (CDC)(IEEE Cat. No. 04CH37601) 1, 2004, pp. 929–934 IEEE
  24. “Exponential-condition-based barrier certificate generation for safety verification of hybrid systems” In Computer Aided Verification: 25th International Conference, CAV 2013, Saint Petersburg, Russia, July 13-19, 2013. Proceedings 25, 2013, pp. 242–257 Springer
  25. “Barrier certificates revisited” In Journal of Symbolic Computation 80 Elsevier, 2017, pp. 62–86
  26. K.B. Ngo, R. Mahony and Zhong-Ping Jiang “Integrator backstepping design for motion systems with velocity constraint” In 2004 5th Asian Control Conference (IEEE Cat. No.04EX904) 1, 2004, pp. 141–146 Vol.1
  27. Keng Peng Tee, Shuzhi Sam Ge and Eng Hock Tay “Barrier Lyapunov functions for the control of output-constrained nonlinear systems” In Automatica 45.4 Elsevier, 2009, pp. 918–927
  28. Harshad S Sane “Adaptive stabilization and disturbance rejection for linear systems and Hammerstein systems”, 2001
  29. “Constructive safety using control barrier functions” In IFAC Proceedings Volumes 40.12 Elsevier, 2007, pp. 462–467
  30. Aaron D Ames, Jessy W Grizzle and Paulo Tabuada “Control barrier function based quadratic programs with application to adaptive cruise control” In 53rd IEEE Conference on Decision and Control, 2014, pp. 6271–6278 IEEE
  31. Muhammad Zakiyullah Romdlony and Bayu Jayawardhana “Uniting control Lyapunov and control barrier functions” In 53rd IEEE Conference on Decision and Control, 2014, pp. 2293–2298 IEEE
  32. Muhammad Zakiyullah Romdlony and Bayu Jayawardhana “Stabilization with guaranteed safety using control Lyapunov–barrier function” In Automatica 66 Elsevier, 2016, pp. 39–47
  33. “Control barrier function based quadratic programs for safety critical systems” In IEEE Transactions on Automatic Control 62.8 IEEE, 2016, pp. 3861–3876
  34. “Control barrier certificates for safe swarm behavior” In IFAC-PapersOnLine 48.27 Elsevier, 2015, pp. 68–73
  35. Li Wang, Aaron Ames and Magnus Egerstedt “Safety barrier certificates for heterogeneous multi-robot systems” In 2016 American control conference (ACC), 2016, pp. 5213–5218 IEEE
  36. Li Wang, Evangelos A Theodorou and Magnus Egerstedt “Safe learning of quadrotor dynamics using barrier certificates” In 2018 IEEE International Conference on Robotics and Automation (ICRA), 2018, pp. 2460–2465 IEEE
  37. “Discrete Control Barrier Functions for Safety-Critical Control of Discrete Systems with Application to Bipedal Robot Navigation.” In Robotics: Science and Systems, 2017
  38. “Reinforcement learning for safety-critical control under model uncertainty, using control lyapunov functions and control barrier functions” In Robotics: Science and Systems, 2020
  39. “Exponential Control Barrier Functions for enforcing high relative-degree safety-critical constraints” In 2016 American Control Conference (ACC), 2016, pp. 322–328
  40. “Control Barrier Functions for Systems with High Relative Degree” In 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, pp. 474–479
  41. “Safe optimal control using stochastic barrier functions and deep forward-backward sdes” In arXiv preprint arXiv:2009.01196, 2020
  42. “Learning Barrier Functions with Memory for Robust Safe Navigation” In IEEE Robotics and Automation Letters 6.3 IEEE, 2021, pp. 4931–4938
  43. Wei Xiao, Calin A Belta and Christos G Cassandras “Feasibility-guided learning for constrained optimal control problems” In 2020 59th IEEE Conference on Decision and Control (CDC), 2020, pp. 1896–1901 IEEE
  44. Eduardo D Sontag “Smooth stabilization implies coprime factorization” In IEEE transactions on automatic control 34.4, 1989, pp. 435–443
  45. Muhammad Zakiyullah Romdlony and Bayu Jayawardhana “On the new notion of input-to-state safety” In 2016 IEEE 55th conference on decision and control (CDC), 2016, pp. 6403–6409 IEEE
  46. Shishir Kolathaya and Aaron D Ames “Input-to-state safety with control barrier functions” In IEEE control systems letters 3.1 IEEE, 2018, pp. 108–113
  47. Miroslav Krstic “Inverse optimal safety filters” In IEEE Transactions on Automatic Control IEEE, 2023
  48. “Nonovershooting Control of Strict-Feedback Nonlinear Systems” In IEEE Transactions on Automatic Control 51.12, 2006, pp. 1938–1943
  49. Muhammad Zakiyullah Romdlony and Bayu Jayawardhana “Robustness analysis of systems’ safety through a new notion of input-to-state safety” In International Journal of Robust and Nonlinear Control 29.7 Wiley Online Library, 2019, pp. 2125–2136
  50. Andrii Mironchenko “Input-to-State Stability: Theory and Applications” Springer Nature, 2023
  51. Andrii Mironchenko “Local input-to-state stability: Characterizations and counterexamples” In Systems & Control Letters 87 Elsevier, 2016, pp. 23–28
  52. Eduardo D Sontag “Input to state stability: Basic concepts and results” In Nonlinear and optimal control theory: lectures given at the CIME summer school held in Cetraro, Italy June 19–29, 2004 Springer, 2008, pp. 163–220
  53. Eduardo D Sontag and Yuan Wang “New characterizations of input-to-state stability” In IEEE transactions on automatic control 41.9 IEEE, 1996, pp. 1283–1294
  54. Jaroslav Kautsky, Nancy K Nichols and Paul Van Dooren “Robust pole assignment in linear state feedback” In International Journal of control 41.5 Taylor & Francis, 1985, pp. 1129–1155
  55. Katja Vogel “A comparison of headway and time to collision as safety indicators” In Accident analysis & prevention 35.3 Elsevier, 2003, pp. 427–433
  56. A Shaout and Mohammad Ameen Jarrah “Cruise control technology review” In Computers & electrical engineering 23.4 Elsevier, 1997, pp. 259–271
Citations (1)

Summary

We haven't generated a summary for this paper yet.