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Improving the Resilience of Barrier Function-Based Safety-Critical Controllers Against Uncertainties With Application to Connected Autonomous Vehicles
Improving the Resilience of Barrier Function-Based Safety-Critical Controllers Against Uncertainties With Application to Connected Autonomous Vehicles
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211153018
- ISBN
- 9798384046059
- DDC
- 629.2
- 저자명
- Alan, Anil.
- 서명/저자
- Improving the Resilience of Barrier Function-Based Safety-Critical Controllers Against Uncertainties With Application to Connected Autonomous Vehicles
- 발행사항
- [Sl] : University of Michigan, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 165 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
- 주기사항
- Advisor: Orosz, Gabor.
- 학위논문주기
- Thesis (Ph.D.)--University of Michigan, 2024.
- 초록/해제
- 요약As safety is an ever more pressing requirement for modern control systems deployed into real-world environments, there has been an increase in demand to design controllers with mathematically rigorous safety guarantees. Control barrier functions (CBFs) provide one such framework, which takes our understanding of the system into consideration, and utilizes theoretical properties of sets to avoid unsafe states. Its intuitive nature leads to practical solutions for designing safe-by-design controllers, and their efficacy has been demonstrated experimentally in real-world conditions. A limitation inherent in the CBF framework is its dependence on the accuracy of the model capturing the underlying dynamics of the system, which consequently raises the question of resilience against model imperfections. The main contribution of this dissertation is a methodical investigation of a range of viable solutions to improve the resilience of CBF-based controllers. We study solutions in a categorical approach, and present our contributions on improving multiple aspects such as performance and conservativeness.The theoretical investigation is introduced in two main categories: input-to-state safety (ISSf) and robust control barrier functions (RCBFs). While methods in the former group looks to treat uncertainties to a more manageable level, methods in the latter group aims a complete cancellation approach. As a result, safety guarantees provided by these approaches land on a spectrum ranging from arbitrarily small (graceful) safety degradation to absolute robust safety. This dissertation delves into both approaches with a scope on controller design, where we focus on maintaining the beneficial properties of the CBF framework while improving the robustness. Another contribution of this dissertation is on the application front, where we utilize practical examples to support the theoretical results. In particular, a case study of designing safe and energy-efficient controllers for an autonomous truck is introduced as the main application. Hard-to-model nature of intricate relationships between complex subsystems makes the autonomous truck an ideal platform to evaluate the benefits of the CBF-based controllers. We deploy controllers (with and without the robustness feature) on a full-scale truck, and evaluate the theoretical guarantees experimentally in challenging conditions such as emergency brake.
- 일반주제명
- Automotive engineering
- 일반주제명
- Mechanical engineering
- 일반주제명
- Robotics
- 일반주제명
- Systems science
- 키워드
- Robust control
- 키워드
- Conservativeness
- 기타저자
- University of Michigan Mechanical Engineering
- 기본자료저록
- Dissertations Abstracts International. 86-03B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798384046059
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■035 ▼a(MiAaPQ)umichrackham005589
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a629.2
■1001 ▼aAlan, Anil.
■24510▼aImproving the Resilience of Barrier Function-Based Safety-Critical Controllers Against Uncertainties With Application to Connected Autonomous Vehicles
■260 ▼a[Sl]▼bUniversity of Michigan▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a165 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-03, Section: B.
■500 ▼aAdvisor: Orosz, Gabor.
■5021 ▼aThesis (Ph.D.)--University of Michigan, 2024.
■520 ▼aAs safety is an ever more pressing requirement for modern control systems deployed into real-world environments, there has been an increase in demand to design controllers with mathematically rigorous safety guarantees. Control barrier functions (CBFs) provide one such framework, which takes our understanding of the system into consideration, and utilizes theoretical properties of sets to avoid unsafe states. Its intuitive nature leads to practical solutions for designing safe-by-design controllers, and their efficacy has been demonstrated experimentally in real-world conditions. A limitation inherent in the CBF framework is its dependence on the accuracy of the model capturing the underlying dynamics of the system, which consequently raises the question of resilience against model imperfections. The main contribution of this dissertation is a methodical investigation of a range of viable solutions to improve the resilience of CBF-based controllers. We study solutions in a categorical approach, and present our contributions on improving multiple aspects such as performance and conservativeness.The theoretical investigation is introduced in two main categories: input-to-state safety (ISSf) and robust control barrier functions (RCBFs). While methods in the former group looks to treat uncertainties to a more manageable level, methods in the latter group aims a complete cancellation approach. As a result, safety guarantees provided by these approaches land on a spectrum ranging from arbitrarily small (graceful) safety degradation to absolute robust safety. This dissertation delves into both approaches with a scope on controller design, where we focus on maintaining the beneficial properties of the CBF framework while improving the robustness. Another contribution of this dissertation is on the application front, where we utilize practical examples to support the theoretical results. In particular, a case study of designing safe and energy-efficient controllers for an autonomous truck is introduced as the main application. Hard-to-model nature of intricate relationships between complex subsystems makes the autonomous truck an ideal platform to evaluate the benefits of the CBF-based controllers. We deploy controllers (with and without the robustness feature) on a full-scale truck, and evaluate the theoretical guarantees experimentally in challenging conditions such as emergency brake.
■590 ▼aSchool code: 0127.
■650 4▼aAutomotive engineering
■650 4▼aMechanical engineering
■650 4▼aRobotics
■650 4▼aSystems science
■653 ▼aSafety-critical control
■653 ▼aControl barrier functions
■653 ▼aRobust control
■653 ▼aAutonomous vehicles
■653 ▼aConservativeness
■690 ▼a0548
■690 ▼a0771
■690 ▼a0540
■690 ▼a0790
■71020▼aUniversity of Michigan▼bMechanical Engineering.
■7730 ▼tDissertations Abstracts International▼g86-03B.
■790 ▼a0127
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17164569▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
