Integral Control Barrier Functions for Dynamically Defined Control Laws

Ames, Aaron D.; Notomista, Gennaro; Wardi, Yoraı̈; Egerstedt, Magnus

doi:10.1109/lcsys.2020.3006764

Cited by 35 publications

(18 citation statements)

References 19 publications

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“…As will be shown in the next section, affine input constraints are desirable in order to synthesize robot controllers under real-time constraints at high frequencies commonly used in the control loops of modern robotic platforms. To circumvent this issue, control dependent control barrier functions [23] or the more general formulation of integral control barrier functions [24], defined below, can be employed.…”

Section: B Integral Control Barrier Functionsmentioning

confidence: 99%

“…Then, h is an integral control barrier function (I-CBF) if for any (x, u) ∈ R nx × R nu and t ≥ 0, p(x, u) = 0 ⇒ d(x, u, t) ≤ 0, where the expressions of p(x, u) and d(x, u, t) are given in [24].…”

Section: Definition 2 ( [24]mentioning

confidence: 99%

“…In other words, we would like the set of values of SOC, e, above a desired minimum threshold to be forward invariant, which is equivalent to saying that we would like e to be always greater than or equal to a desired minimum threshold. With this above definition of I-CBFs, Theorem 1 in [24] gives sufficient conditions for the forward invariance of sets defined through an I-CBF.…”

Section: Definition 2 ( [24]mentioning

confidence: 99%

“…Theorem 1 in [24] ensures that h u (x(t), u(t), e(t)) ≥ 0, ∀t ≥ 0. By the definition of h u in (9), a positive h u implies thaṫ h x (x, e, u) + γ x (h x (x, e)) ≥ 0.…”

Section: Persistent Environmental Monitoringmentioning

confidence: 99%

See 3 more Smart Citations

Online Robot Trajectory Optimization for Persistent Environmental Monitoring

Notomista¹,

Pacchierotti

Giordano

2022

IEEE Control Syst. Lett.

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This paper presents a control-theoretic approach for trajectory optimization of mobile robots suitable for environmental monitoring. The method is based on the optimization of the Constructability Gramian in order to maximize the information collected while traversing a state trajectory. The maximization of the collected information is combined with energy constraints to define an optimization-based controller that achieves persistent environmental monitoring. The results of its application to the estimation of the concentration of a diffusing gas using a mobile robot are shown in simulation.

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Section: B Integral Control Barrier Functionsmentioning

confidence: 99%

Section: Definition 2 ( [24]mentioning

confidence: 99%

Section: Definition 2 ( [24]mentioning

confidence: 99%

“…Theorem 1 in [24] ensures that h u (x(t), u(t), e(t)) ≥ 0, ∀t ≥ 0. By the definition of h u in (9), a positive h u implies thaṫ h x (x, e, u) + γ x (h x (x, e)) ≥ 0.…”

Section: Persistent Environmental Monitoringmentioning

confidence: 99%

See 2 more Smart Citations

Online Robot Trajectory Optimization for Persistent Environmental Monitoring

Notomista¹,

Pacchierotti

Giordano

2022

IEEE Control Syst. Lett.

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“…However, the condition of passivity, recalled in 1, involves the input u. Recently introduced integral CBFs (I-CBFs) [1]-which generalize control dependent CBFs [9]-can be leveraged to enforce passivity conditions. In order to take advantage of I-CBFs, the system (1) needs to be dynamically extended as follows:…”

Section: Introductionmentioning

confidence: 99%

A Safety and Passivity Filter for Robot Teleoperation Systems

Notomista

Cai

2021

Preprint

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In this paper, we present a way of enforcing safety and passivity properties of robot teleoperation systems, where a human operator interacts with a dynamical system modeling the robot. The approach does so in a holistic fashion, by combining safety and passivity constraints in a single optimization-based controller which effectively filters the desired control input before supplying it to the system. The result is a safety and passivity filter implemented as a convex quadratic program which can be solved efficiently and employed in an online fashion in many robotic teleoperation applications. Simulation results show the benefits of the approach developed in this paper applied to the human teleoperation of a second-order dynamical system.

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Adaptive robust safety‐critical control of switched systems via single barrier function

Huang,

Long

2024

Intl J Robust & Nonlinear

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SummaryThis paper addresses the problem of adaptive robust safety‐critical control (ARSCC) for switched systems, where the safety of subsystems is not necessary. A novel ARSCC framework and an executable algorithm are presented to solve the ARSCC problem by finding a switching signal and controllers of subsystems. To estimate uncertainties, a novel switched piecewise‐constant adaptive law is presented, which guarantees a pre‐computable estimation error boundary. A single barrier function (SBF) method is proposed to ensure safety of switched systems with uncertainties, where the safety of subsystems is satisfied only in some subregion of a given safe set, instead of the whole safe set. Based on the SBF method, a novel state‐dependent switching law possessing different dwell times for different subsystems, is established to orchestrate the switching among potentially unsafe subsystems. As a special case of the SBF method, a common barrier function method is presented to achieve safety of switched systems with uncertainties under switching signals with given dwell times. In addition, some sufficient conditions are derived to obtain safety and asymptotic stability for switched systems with uncertainties by combining SBF and single Lyapunov function. Finally, a switched RLC circuit system is given to illustrate the effectiveness of the theoretical results.

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Integral Control Barrier Functions for Dynamically Defined Control Laws

Cited by 35 publications

References 19 publications

Online Robot Trajectory Optimization for Persistent Environmental Monitoring

Online Robot Trajectory Optimization for Persistent Environmental Monitoring

A Safety and Passivity Filter for Robot Teleoperation Systems

Adaptive robust safety‐critical control of switched systems via single barrier function

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