Bayesian Inference for Time Delay Systems with Application to Connected Automated Vehicles

Ji, Xunbi A.; Molnár, Tamás G.; Gorodetsky, Alex; Orosz, Gábor

doi:10.1109/itsc48978.2021.9564457

Cited by 7 publications

(14 citation statements)

References 17 publications

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“…The steps of the proof follow those of Theorem 2 in [30]. We prove the Proposition by showing that (20) implies (11) and by applying Theorem 2. We relate (20) to (11) by introducing the difference between their corresponding terms.…”

Section: B Robust Safety In Uncertain Environmentmentioning

confidence: 94%

“…We prove the Proposition by showing that (20) implies (11) and by applying Theorem 2. We relate (20) to (11) by introducing the difference between their corresponding terms. Applying (10) to express both Ḣ(x, e, ė, u) and Ḣ(x, ê, ê, u), we get…”

Section: B Robust Safety In Uncertain Environmentmentioning

confidence: 98%

“…Response times include sensory, feedback and actuation delays arising in practice [18]. The magnitude of the delay depends on the application: it is milliseconds in robotic systems [19], a few tenths of a second in connected automated vehicles [20] and days in epidemiological models [21]. Delays have significant impact on safety in the context of dynamic environments: it may occur that by the time the control system responds, the environment changes and safety is compromised.…”

mentioning

confidence: 99%

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Safety-Critical Control With Input Delay in Dynamic Environment

Molnár

Ames

Orosz

2023

IEEE Trans. Contr. Syst. Technol.

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Endowing nonlinear systems with safe behavior is increasingly important in modern control. This task is particularly challenging for real-life control systems that must operate safely in dynamically changing environments. This paper develops a framework for safety-critical control in dynamic environments, by establishing the notion of environmental control barrier functions (ECBFs). The framework is able to guarantee safety even in the presence of input delay, by accounting for the evolution of the environment during the delayed response of the system. The underlying control synthesis relies on predicting the future state of the system and the environment over the delay interval, with robust safety guarantees against prediction errors. The efficacy of the proposed method is demonstrated by a simple adaptive cruise control problem and a more complex robotics application on a Segway platform.

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Section: B Robust Safety In Uncertain Environmentmentioning

confidence: 94%

Section: B Robust Safety In Uncertain Environmentmentioning

confidence: 98%

mentioning

confidence: 99%

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Safety-Critical Control With Input Delay in Dynamic Environment

Molnár

Ames

Orosz

2023

IEEE Trans. Contr. Syst. Technol.

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“…When ℎ( ) = 0, the derivative of ℎ with respect to time is not affected by the control input according to (13), hence the corresponding uncontrolled system must be safe on its own. One may sufficiently satisfy (17) by requiring that ℎ( ) is never zero.…”

Section: Safety-critical Controlmentioning

confidence: 99%

“…While most works in safety-critical control are applied to delay-free systems, time delays often arise in many applications. For example, human-machine interactions involve the reflex delay of the human operators, models of vehicular traffic contain the reaction time of the drivers 13 , wheel-shimmy motion can occur on vehicles due to the elastic contact between the tire and the road that can be modeled as distributed delay 14 , manufacturing processes including metal cutting may suffer from vibrations due to a delayed regenerative effect of the chip formation 15 , hydraulic systems showcase time delay caused by wave propagation in pipes 16 , and epidemiological models contain delays due to the incubation period of infectious diseases 17,18 . Time delay also plays important role in population dynamics 19 , neural networks 20 , brain dynamics 21 , the human sensory system 22,23 and robotic systems 24 .…”

Section: Introductionmentioning

confidence: 99%

Control Barrier Functionals: Safety-critical Control for Time Delay Systems

Molnár¹,

Ames²,

Orosz³

2022

Preprint

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This work presents a theoretical framework for the safety-critical control of time delay systems. The theory of control barrier functions, that provides formal safety guarantees for delay-free systems, is extended to systems with state delay. The notion of control barrier functionals is introduced to attain formal safety guarantees, by enforcing the forward invariance of safe sets defined in the infinite dimensional state space. The proposed framework is able to handle multiple delays and distributed delays both in the dynamics and in the safety condition, and provides an affine constraint on the control input that yields provable safety. This constraint can be incorporated into optimization problems to synthesize pointwise optimal and provable safe controllers. The applicability of the proposed method is demonstrated by numerical simulation examples.

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Control barrier functionals: Safety‐critical control for time delay systems

Molnár

Ames

Orosz

2023

Intl J Robust & Nonlinear

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This work presents a theoretical framework for the safety-critical control of time delay systems. The theory of control barrier functions, that provides formal safety guarantees for delay-free systems, is extended to systems with state delay. The notion of control barrier functionals is introduced, to attain formal safety guarantees by enforcing the forward invariance of safe sets defined in the infinite dimensional state space. The proposed framework is able to handle multiple delays and distributed delays both in the dynamics and in the safety condition, and provides an affine constraint on the control input that yields provable safety. This constraint can be incorporated into optimization problems to synthesize pointwise optimal and provable safe controllers. The applicability of the proposed method is demonstrated by numerical simulation examples.

show abstract

Bayesian Inference for Time Delay Systems with Application to Connected Automated Vehicles

Cited by 7 publications

References 17 publications

Safety-Critical Control With Input Delay in Dynamic Environment

Safety-Critical Control With Input Delay in Dynamic Environment

Control Barrier Functionals: Safety-critical Control for Time Delay Systems

Control barrier functionals: Safety‐critical control for time delay systems

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