Set-theoretic model reference adaptive control with time-varying performance bounds

Arabi, Ehsan; Yucelen, Tansel

doi:10.1080/00207179.2018.1442026

Cited by 42 publications

(50 citation statements)

References 10 publications

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“…In order to achieve strict performance constraints, the generalized restricted potential function is introduced.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

“…Adaptive control algorithm has the ability to deal with the uncertainty of system structure and parameter, but one of the challenging issues of adaptive control is how to realize a priori user‐defined performance constraints. In order to solve this problem, many control methods are proposed to achieve strict performance guarantees . Recently, the set‐theoretic model reference adaptive control framework is proposed to ensure the system error within the user‐defined performance bounds .…”

Section: Introductionmentioning

confidence: 99%

“…In order to solve this problem, many control methods are proposed to achieve strict performance guarantees . Recently, the set‐theoretic model reference adaptive control framework is proposed to ensure the system error within the user‐defined performance bounds . In the work of Arabi et al, an adaptive tracking control strategy for an uncertain system is developed to guarantee performance bounds, which is a priori given, user defined.…”

Section: Introductionmentioning

confidence: 99%

“…In the work of Arabi et al, an adaptive tracking control strategy for an uncertain system is developed to guarantee performance bounds, which is a priori given, user defined. Different from the aforementioned work, the proposed controller can achieve user‐defined time‐varying performance bounds rather than a priori, user‐defined constant bounds . In the work of Yucelen et al, the proposed control method can guarantee partial performance constraints to a desired subset of the tracking error.…”

Section: Introductionmentioning

confidence: 99%

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Robust adaptive fault‐tolerant tracking control for uncertain linear systems with time‐varying performance bounds

Xiao

Dong

2018

Intl J Robust & Nonlinear

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In this paper, the problem of robust adaptive fault-tolerant tracking control with time-varying performance bounds is investigated for a class of linear systems subject to parameter uncertainties, external disturbances and actuator failures.In order to ensure the norm of the tracking error less than the user-defined time-varying performance bounds, we propose a new control strategy which is predicated on the generalized restricted potential function. Compared with the existing result, a novel method which provides two design freedoms is developed to reduce the tracking error. According to the online estimation information provided by adaptive mechanism, a fault-tolerant tracking control method guaranteeing time-varying performance bounds is developed for robust tracking of reference model. It is shown that the closed-loop signals are bounded and the tracking error within an a priori given, time-varying performance bounds.A simulation result is provided to demonstrate the efficacy of the proposed fault-tolerant tracking control method.

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“…In order to achieve strict performance constraints, the generalized restricted potential function is introduced.…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust adaptive fault‐tolerant tracking control for uncertain linear systems with time‐varying performance bounds

Xiao

Dong

2018

Intl J Robust & Nonlinear

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“…In [10,11] this framework was further extended to guarantee time-varying user-defined performance bounds.…”

Section: Introductionmentioning

confidence: 99%

Human-in-the-Loop Systems with Inner and Outer Feedback Control Loops: Adaptation, Stability Conditions, and Performance Constraints

Arabi

Yucelen

Sipahi

et al. 2019

AIAA Scitech 2019 Forum

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In this paper, we focus on human-in-the-loop physical systems with inner and outer feedback control loops. Specifically, our problem formulation considers that inner loop control laws use a model reference adaptive control approach to suppress the effect of system uncertainties such that the overall physical system operates close to its ideal behavior as desired in the presence of adverse conditions due to failures and/or modeling inaccuracies. Moreover, we consider that the outer loop control laws exist owing to employing either sequential loop closure and/or high-level guidance methods. As it is true in practice, in addition, humans are considered to inject commands directly to the outer loop dynamics in response to the changes in the physical system, where the outer loop commands affect inner loop dynamics in response to the commands received from the humans as well as in response to the changes in the physical system. The presence of humans can result in system instability, even when the resulting physical system augmented with inner and outer feedback control loops yield to stable trajectories in the absence of humans. This paper addresses this problem by proving a sufficient stability condition for the overall physical system with human dynamics modeled as a linear timeinvariant system with human reaction time-delay, where this condition does not depend on system uncertainties similar to our recent theoretical results. Furthermore, inner loop system errors during the transient phase of adaptively suppressing system uncertainties can severely affect the human-outer loop interactions. We also address this issue by utilizing a recently proposed set-theoretic model reference adaptive control approach at the inner loop for enforcing a user-defined performance constraint on the norm of the system error trajectories, where we show how the selection of this constraint affects the overall physical system. Finally, the efficacy of our results is demonstrated through an illustrative numerical example for an adaptive flight control application with a Neal-Smith pilot model.

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Model reference safety‐critical adaptive control for nonlinear and switched systems

Rong

Huang

Long

2022

Adaptive Control & Signal

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Summary This paper studies the problem of model reference safety‐critical adaptive control for a class of nonlinear and switched systems with nonlinear reference models. An adaptive law is designed to estimate unknown parameters, while an energy function is proposed to guarantee the boundedness and safety of nonlinear systems. Also, a model reference safety‐critical adaptive control framework is established to ensure that the state trajectory of nonlinear systems is always within the safe set in the presence of unknown parameters. Moreover, the results obtained are extended to switched uncertain nonlinear systems under arbitrary switchings. A switched adaptive controller is designed to reduce the conservativeness caused by adoption of a common update law for all subsystems. Also, the safety of switched systems under arbitrary switchings is guaranteed as well as the boundedness of the error states between the switched nonlinear systems and the switched reference models by utilizing the common Lyapunov function method. Finally, two illustrative numerical examples are given to demonstrate the effectiveness of the proposed control architecture.

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Set-theoretic model reference adaptive control with time-varying performance bounds

Cited by 42 publications

References 10 publications

Robust adaptive fault‐tolerant tracking control for uncertain linear systems with time‐varying performance bounds

Robust adaptive fault‐tolerant tracking control for uncertain linear systems with time‐varying performance bounds

Human-in-the-Loop Systems with Inner and Outer Feedback Control Loops: Adaptation, Stability Conditions, and Performance Constraints

Model reference safety‐critical adaptive control for nonlinear and switched systems

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