Supervised multi-model adaptive control of neuromuscular blockade with off-set compensation

Oliveira, Pedro; Hespanha, João P.; Lemos, João M.; Mendonça, Teresa

doi:10.23919/ecc.2009.7074875

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…3, only selects the "correct" cluster of the dynamic model of the system in 22% of the simulations performed. Even though this ratio is larger than the one in [34], where the correct cluster was selected in 12% of the cases, this large number of erroneous model selection leads to the conclusion that different clusters may share dynamic models. In other words, for the given levels of measurement noise and model uncertainty, there are muscular activity responses that can be described by models that belong to different clusters.…”

Section: B Simulation Resultsmentioning

confidence: 78%

“…However, unlike the approach in [2], rather than designing a controller for each of these models, robust controllers were synthesized that yield performance and stability guarantees for subsets of S M . In particular, we adopted the approach described in [34] to characterize each response and to construct the clusters of models. Indeed, each model in S M is classified according to two features.…”

Section: Local Controllersmentioning

confidence: 99%

“…Therefore, 12 controllers were designed, as in Section III-D, so that each of them is associated to a cluster of dynamic NMB models. For further details, the reader is referred to [34].…”

Section: Local Controllersmentioning

confidence: 99%

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A set-valued observer approach to multiple-model adaptive control of neuromuscular blockade

Rosa¹,

Lemos

Mendonça

et al. 2012

2012 American Control Conference (ACC)

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Due to their underlying complexity, biomedical systems are typically described by dynamic models with a significant level of uncertainty. Hence, classical control methods cannot be readily applied, as they do not render satisfactory results in terms of performance and even stability. Therefore, this paper proposes a multiple-model adaptive approach to the neuromuscular blockade control problem, based on the recent advances in set-valued observers for model falsification, that explicitly account for unknown parameters in the model. Some of the indistinguishability issues that usually arise in control problems with such levels of model uncertainty are also mentioned, The suggested method outperforms the alternatives in the literature, in terms of reference tracking error and of the number of successful model selections, as illustrated in simulation. P. Rosa is with Institute for Systems and Robotics -Instituto Superior Tecnico, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal prosa@isr.ist.utl.pt J. M. Lemos is with INESC-ID and also with Instituto Superior Tecnico, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal jlml@inesc.pt C. Silvestre is with Institute for Systems and Robotics -Instituto Superior Tecnico, Av. Rovisco Pais, 1, 1049-001 Lisboa,

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Section: B Simulation Resultsmentioning

confidence: 78%

Section: Local Controllersmentioning

confidence: 99%

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A set-valued observer approach to multiple-model adaptive control of neuromuscular blockade

Rosa¹,

Lemos

Mendonça

et al. 2012

2012 American Control Conference (ACC)

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“…[13], [16], [17], the features of the problem mainly the high inter-and intra-patient variability The novelty of the strategy proposed in this paper is the use of a minimally parameterized model for the description of the effect of the muscle relaxant atracurium in the NeuroMuscular Blockade [6] and the incorporation of an online identification strategy (an Extended Kalman Filter) in the controller structure, providing adaptivity to the nonlinear controller. As a consequence the variability of the patient parameters does not interfere with the performance of the controller.…”

Section: Discussionmentioning

confidence: 99%

Nonlinear adaptive control of the NeuroMuscular Blockade in anesthesia

Silva

Mendonça

Wigren

2011

IEEE Conference on Decision and Control and European Control Conference

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This paper presents a nonlinear adaptive control strategy based on the Wiener model for control of the NeuroMuscular Blockade in anesthesia. The structure combines the inversion of the static nonlinearity present in the Wiener model with a pole-placement controller for the linearized system. The overall strategy exploits identification of a minimally parameterized model for the description of the effect of the muscle relaxant atracurium in the NeuroMuscular Blockade. An Extended Kalman Filter was developed for that purpose, providing estimates of the model parameters for both the linear controller and the blocks where the inversion of the static linearity is performed. Simulations were run in a database of 100 patients simulated with the standard physiologically-based pharmacokinetic/pharmacodynamic model for the NeuroMuscular Blockade. The results show that the nonlinear adaptive controller performs well regarding reference following and tackles changes in the patient's dynamics. Noisy scenarios were also simulated to test the robustness of the proposed strategy.

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“…To improve patient recovery, lessen anesthetic drug usage, and reduce time spent at drug saturation levels, a variety of approaches to controlling depth of anesthesia have been proposed e.g. in [37,14,39,8,34,28].…”

Section: Safety In Anesthesia Automation (Discrete-time)mentioning

confidence: 99%

Computing the viability kernel using maximal reachable sets

Kaynama

Maidens

Oishi

et al. 2012

Proceedings of the 15th ACM International Conference on Hybrid Systems: Computation and Control

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We present a connection between the viability kernel and maximal reachable sets. Current numerical schemes that compute the viability kernel suffer from a complexity that is exponential in the dimension of the state space. In contrast, extremely efficient and scalable techniques are available that compute maximal reachable sets. We show that under certain conditions these techniques can be used to conservatively approximate the viability kernel for possibly high-dimensional systems. We demonstrate the results on two practical examples, one of which is a seven-dimensional problem of safety in anesthesia.

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Supervised multi-model adaptive control of neuromuscular blockade with off-set compensation

Cited by 4 publications

References 17 publications

A set-valued observer approach to multiple-model adaptive control of neuromuscular blockade

A set-valued observer approach to multiple-model adaptive control of neuromuscular blockade

Nonlinear adaptive control of the NeuroMuscular Blockade in anesthesia

Computing the viability kernel using maximal reachable sets

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