Computing actuator bandwidth limits for model reference adaptive control

Gruenwald, Benjamin C.; Wagner, Daniel; Yucelen, Tansel; Muse, Jonathan A.

doi:10.1080/00207179.2016.1161236

Cited by 50 publications

(28 citation statements)

References 16 publications

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“…Remark For the clarity of the exposition, the same bandwidth for all actuator channels is considered in this paper. This is without loss of generality since one can readily replace λ in with a positive‐definite diagonal matrix (see, for example, the works of Gruenwald et al) by following the system‐theoretical analysis steps given later in this paper. In addition, one can also consider an unknown control effectiveness matrix

normalΛ \in {double-struckR}_{+}^{m \times m} \cap {double-struckD}^{m \times m}

in by replacing the term “ v ( t )” with “Λ v ( t ).” This is also without loss of generality by following the system‐theoretical analysis steps of this paper along with the results, for example, in the work of Dogan et al…”

Section: Problem Formulationmentioning

confidence: 99%

“…Furthermore, since e h ( t ) is bounded and x rh ( t ) is now bounded for all

t \in {\overset{double-struckR}{true}}_{+}

, x ( t ) is also bounded from the definition of e h ( t )= x ( t )− x rh ( t ). Note that hedging‐based approach modifies the ideal reference model given by dynamics with a signal “ B [ v ( t )− u ( t )]” that enables design adaptive controllers without affected by the presence of actuator dynamics . We now provide an example that compares the sufficient stability condition for the standard MRAC architecture (Assumption ) with the one for the hedging‐based MRAC architecture (Assumption ).…”

Section: Stability Analysesmentioning

confidence: 99%

“…Gruenwald et al 8 further extend the results in their aforementioned works. 6,7 Specifically, they propose an approach based on an extended reference model to the adaptive control literature that can achieve a better closed-loop system performance in the presence of actuator dynamics when it is compared with the hedging method.…”

Section: Literature Reviewmentioning

confidence: 99%

“…While some authors [1][2][3][4][5][6][7][8] study actuator dynamics problem and some others [10][11][12][13][14][15] study unmodeled dynamics problem for model reference adaptive control architectures, the effects of both dynamics are strictly present in feedback loops for a wide array of applications. To elucidate this point, for example, consider the flight control problem of flexible aerospace vehicles (eg, see other works [16][17][18].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Building on the results in the works of Johnson et al, Gruenwald et al develop sufficient stability conditions that guarantee the stability of the hedged, modified reference model trajectories and, therefore, the stability of the closed‐loop system trajectories. Gruenwald et al further extend the results in their aforementioned works . Specifically, they propose an approach based on an extended reference model to the adaptive control literature that can achieve a better closed‐loop system performance in the presence of actuator dynamics when it is compared with the hedging method.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Adaptive architectures for control of uncertain dynamical systems with actuator and unmodeled dynamics

Dogan

Gruenwald

Yucelen

et al. 2019

Intl J Robust & Nonlinear

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Summary In adaptive control of uncertain dynamical systems, it is well known that the presence of actuator and/or unmodeled dynamics in feedback loops can yield to unstable closed‐loop system trajectories. Motivated by this standpoint, this paper focuses on the analysis and synthesis of multiple adaptive architectures for control of uncertain dynamical systems with both actuator and unmodeled dynamics. Specifically, we first analyze model reference adaptive control architectures with standard, hedging‐based, and expanded reference models for this class of uncertain dynamical systems and develop sufficient stability conditions. We then synthesize a robustifying term for the latter architecture and analytically show that this term can allow for a relaxed sufficient stability condition. The proposed theoretical treatments involve Lyapunov stability theory, linear matrix inequalities, and matrix mathematics. Finally, we compare the resulting sufficient stability conditions of the considered adaptive control architectures on a benchmark mechanical system subject to actuator and unmodeled dynamics.

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normalΛ \in {double-struckR}_{+}^{m \times m} \cap {double-struckD}^{m \times m}

Section: Problem Formulationmentioning

confidence: 99%

“…Furthermore, since e h ( t ) is bounded and x rh ( t ) is now bounded for all

t \in {\overset{double-struckR}{true}}_{+}

Section: Stability Analysesmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Adaptive architectures for control of uncertain dynamical systems with actuator and unmodeled dynamics

Dogan

Gruenwald

Yucelen

et al. 2019

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

show abstract

Model Reference Adaptive Control

Yucelen

2019

Wiley Encyclopedia of Electrical and Electronics Engineering

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Adaptive control methods present effective system‐theoretical tools in order to achieve closed‐loop system stability and performance in the presence of exogenous disturbances and system uncertainties, where they are generally classified as either direct or indirect. A well‐known class of direct adaptive control methods is model reference adaptive control architectures. In particular, these architectures employ two major components – a reference model and a parameter adjustment mechanism. A desired closed‐loop dynamical system response is captured by the reference model for which its response is compared with the response of the uncertain dynamical system. The system error signal resulting from this comparison drives the parameter adjustment mechanism. This mechanism then adjusts the controller parameters in a real‐time (i.e., online) manner for driving the trajectories of the uncertain dynamical system to the trajectories of the reference model. This article discusses these components in a basic state feedback setting in order to provide an introduction to the model reference adaptive control design procedure. The article also makes connections to several other, relatively advanced model reference adaptive control methods for interested readers.

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Model‐based vs data‐driven adaptive control: An overview

Benosman

2018

Adaptive Control & Signal

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In this paper, we present an overview of adaptive control by contrasting model-based approaches with data-driven approaches. Indeed, we propose to classify adaptive controllers into two main subfields, namely, model-based adaptive control and data-driven adaptive control. In each subfield, we cite monographs, survey papers, and recent research papers published in the last few years. We also include a few simple examples to illustrate some general concepts in each subfield.

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Computing actuator bandwidth limits for model reference adaptive control

Cited by 50 publications

References 16 publications

Adaptive architectures for control of uncertain dynamical systems with actuator and unmodeled dynamics

Adaptive architectures for control of uncertain dynamical systems with actuator and unmodeled dynamics

Model Reference Adaptive Control

Model‐based vs data‐driven adaptive control: An overview

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