Integrated System Health Management (ISHM) and Autonomy

Figueroa, Fernando; Walker, Mark

doi:10.2514/6.2018-1152

Cited by 9 publications

(3 citation statements)

References 6 publications

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“…An 'autonomous system' is defined as one that takes actions on its own to achieve goals provided independently by whomever defines them or will benefit from their achievement. Also, the decision-making process is local and offline (13)(14)(15)(16) .…”

Section: Autonomous Versus Automatedmentioning

confidence: 99%

The state of the art and operational scenarios for urban air mobility with unmanned aircraft

Maia

Saúde

2021

Aeronaut. j.

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A state-of-the-art review of all the developments, standards and regulations associated with the use of major unmanned aircraft systems under development is presented. Requirements and constraints are identified by evaluating technologies specific to urban air mobility, considering equivalent levels of safety required by current and future civil aviation standards. Strategies, technologies and lessons learnt from remotely piloted aviation and novel unmanned traffic management systems are taken as the starting point to assess operational scenarios for autonomous urban air mobility.

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Section: Autonomous Versus Automatedmentioning

confidence: 99%

The state of the art and operational scenarios for urban air mobility with unmanned aircraft

Maia

Saúde

2021

Aeronaut. j.

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“…When the concept of integrated system health management (ISHM) became formalized, most interpretations of integrated encompassed some interactions between SHM and DM, although practical implementations of such interactions have been limited (Figueroa & Walker, 2018). A notable early example of ISHM is the Deep Space 1 Remote Agent Experiment, or RAX (Bernard et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Unifying System Health Management and Automated Decision Making

Balaban¹,

Johnson²,

Kochenderfer³

2019

jair

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Health management of complex dynamic systems has evolved from simple automated alarms into a subfield of artificial intelligence with techniques for analyzing off-nominal conditions and generating responses. This evolution took place largely apart from the development of automated system control, planning, and scheduling (generally referred to in this work as decision making). While there have been efforts to establish an information exchange between system health management and decision making, successful practical implementations of integrated architectures remain limited. This article proposes that rather than being treated as connected yet distinct entities, system health management and decision making should be unified in their formulations. Enabled by advances in modeling and algorithms, we believe that a unified approach will increase systems' resilience to faults and improve their effectiveness. We overview the prevalent system health management methodology, illustrate its limitations through numerical examples, and describe a proposed unified approach. We then show how typical system health management concepts are accommodated in the proposed approach without loss of functionality or generality. A computational complexity analysis of the unified approach is also provided.

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“…Still, the two sides largely remained separated. When the concept of Integrated System Health Management became formalized, most interpretations of integrated encompassed some interactions between DM and SHM, although practical implementations of such interactions have been limited (Figueroa and Walker 2018).…”

Section: Introductionmentioning

confidence: 99%

Rethinking System Health Management

Balaban,

Johnson,

Kochenderfer

2019

Preprint

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Health management of complex dynamic systems has traditionally evolved separately from automated control, planning, and scheduling (generally referred to in the paper as decision making). A goal of Integrated System Health Management has been to enable coordination between system health management and decision making, although successful practical implementations have remained limited. This paper proposes that, rather than being treated as connected, yet distinct entities, system health management and decision making should be unified in their formulations. Enabled by advances in modeling and computing, we argue that the unified approach will increase a system's operational effectiveness and may also lead to a lower overall system complexity. We overview the prevalent system health management methodology and illustrate its limitations through numerical examples. We then describe the proposed unification approach and show how it accommodates the typical system health management concepts.

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Integrated System Health Management (ISHM) and Autonomy

Cited by 9 publications

References 6 publications

The state of the art and operational scenarios for urban air mobility with unmanned aircraft

The state of the art and operational scenarios for urban air mobility with unmanned aircraft

Unifying System Health Management and Automated Decision Making

Rethinking System Health Management

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