Passification-Based Adaptive Control with Implicit Reference Model*

Fradkov, Alexander L.; Andrievsky, Boris

doi:10.3182/20070829-3-ru-4911.00052

Cited by 8 publications

(3 citation statements)

References 44 publications

(53 reference statements)

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“…Following (Fradkov and Andrievsky, 2007;Andrievskii and Fradkov, 2006) let us recall design of the variable-structure controllers (Utkin, 1992) and the signal-parametric adaptive controllers with the implicit reference model (Andrievskii et al, 1988;Stotsky, 1994;Andrievskii et al, 1996;Druzhinina et al, 1996) based on the passification method (Fradkov, 1974(Fradkov, , 1980Fradkov et al, 1999;Fradkov, 2003).…”

Section: Signal-parametric Adaptive Controlmentioning

confidence: 99%

Passification based signal-parametric adaptive controller for agents in formation∗∗The work was performed in the IPME RAS, supported by RSF (grant 14-29-00142).

Andrievsky

Tomashevich

2015

IFAC-PapersOnLine

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In the paper the novel method for ensuring an overall formation stability for the case of significant variations of the agents parameters in formation is proposed. The local agent controller is designed by employment of the signal-parametric adaptive strategy, based on the passification method. The approach is demonstrated by an example of altitude control of the quadrocopter formation. The simulation results for a group of 25 quadrocopters are given, showing efficiency of the suggested method.

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Section: Signal-parametric Adaptive Controlmentioning

confidence: 99%

Passification based signal-parametric adaptive controller for agents in formation∗∗The work was performed in the IPME RAS, supported by RSF (grant 14-29-00142).

Andrievsky

Tomashevich

2015

IFAC-PapersOnLine

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“…Moreover, the passification problem has the following important feature in terms of adaptive control (see for example Fradkov and Andrievsky [2007], Barkana [2007]): Theorem 1. If there exists a solution to Problem 2, then, for any Γ > 0, the following adaptive control law u(t) = K(t)y(t) + w(t) ,K(t) = −y(t)y T (t)Γ (8) makes the closed-loop globally x-strictly passive.…”

Section: Matrix Inequalities For Passivity Based Adaptive Controlmentioning

confidence: 99%

Structured adaptive control for solving LMIs

Luzi

Fradkov

Biannic

et al. 2013

IFAC Proceedings Volumes

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Numerical problems such as finding eigenvalues, singular value decomposition, linear programming, are traditionally solved with algorithms that can be interpreted as discrete-time processes. One can also find in the literature continuous-time methods for these same problems where solutions are the equilibrium points to which converge stable differential equations. The paper exposes one such continuous-time method for solving linear matrix inequalities. The proposed differential equations are those of an adaptive control feedback loop on an LTI system. The adaptive law is passivity-based with additional structural constraints of two types. The first constraint imposes the gain to be block-diagonal at all times. It can be interpreted as a decentralized control structure. The second constraint is only required asymptotically. It for example reads as requiring the feedback gain to be symmetric when time goes to infinity. Point-wise global stability is proved with quadratic Lyapunov functions. Results are illustrated on LMIs related to an H ∞ norm computation problem. Solutions to the LMIs are obtained by simulations in Simulink.

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“…8 As this scheme is often based on passivity properties, it is equally called passivity-based adaptive control. 9,10 The considered adaptive output feedback law writes, in the general cas, u(t) = K(t)e(t), where e(t) = y(t)−y r (t) is the error with respect to a reference signal y r and where K(t) is the adaptive gain. In this paper, gain and output structuring is considered, such that …”

Section: Introductionmentioning

confidence: 99%

Structured Adaptive Attitude Control Applied on a Myriade Simulation Benchmark

Luzi¹,

Mignot

Biannic³

et al. 2013

AIAA Guidance, Navigation, and Control (GNC) Conference

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This paper considers the problem of reaction-wheel attitude control inside the mission mode of the Myriade satellites. A structured adaptive algorithm, allowing to extend the operating domain of a static proportionalderivative controller is presented and conditions for designing a stabilizing, continuous-time adaptive law are given. In view of implementation, a discrete-time adaptive algorithm is derived and tested on a benchmark of the DEMETER satellite, which was part of the Myriade program. Simulation results show that the structured adaptation and the use of the σ-modification allow the adaptive closed-loop to follow attitude step references of up to 20 degrees without saturating the reaction wheels. This allows the adaptive law to cover the whole mission mode and replace the currently-implemented switched-based control strategy, thus potentially simplifying the verification and validation. process.

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Passification-Based Adaptive Control with Implicit Reference Model*

Cited by 8 publications

References 44 publications

Passification based signal-parametric adaptive controller for agents in formation∗∗The work was performed in the IPME RAS, supported by RSF (grant 14-29-00142).

Passification based signal-parametric adaptive controller for agents in formation∗∗The work was performed in the IPME RAS, supported by RSF (grant 14-29-00142).

Structured adaptive control for solving LMIs

Structured Adaptive Attitude Control Applied on a Myriade Simulation Benchmark

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