Nonlinear soft tissue mechanics based on polytopic Tensor Product modeling

Takács, Árpád; Haidegger, Tamás; Galambos, Péter; Kuti, József; Rudas, Imre J.

doi:10.1109/sami.2016.7423009

Cited by 2 publications

(2 citation statements)

References 19 publications

(22 reference statements)

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“…This study extends the previous works of the authors, where a nonlinear soft tissue model was obtained based on the experimental investigation of the force response of beef liver specimens during tool-tissue interaction [12], amended with [13], a polytopic qLPV (quasi Linear Parameter Varying) model of the tissue dynamics that is-regarding its mathematical formalism-suitable for direct use of LMI-based control design methods. As a next step, a model-based force control scheme is presented, utilizing an off-the-shelf tooltissue interaction model.…”

Section: Related Worksupporting

confidence: 67%

“…Regarding the Polytopic TP Model of the nonlinear system described in (10) and (11), the detailed derivation of the model can be found in [13], rearranged in a way that considers the socalled error dynamics. The proposed qLPV model assumes that the control goal is the force control of the surgical instrument at the tissue surface contact.…”

Section: Polytopic Tp Model Of the Systemmentioning

confidence: 99%

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Polytopic model based interaction control for soft tissue manipulation

Takács

Kuti

Haidegger

et al. 2016

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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Section: Related Worksupporting

confidence: 67%

Section: Polytopic Tp Model Of the Systemmentioning

confidence: 99%

Polytopic model based interaction control for soft tissue manipulation

Takács

Kuti

Haidegger

et al. 2016

2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Self Cite

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show abstract

Control of Diabetes Mellitus by Advanced Robust Control Solution

et al. 2019

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The current article investigates the possibilities of designing a robust control solution for a control problem related to type 1 diabetes mellitus. The proposed control methodology exploits linear parameter varying, linear matrix inequality, tensor product model transformation and extended Kalman filtering, four advanced control methods in order to guarantee hard safety control constraints for diabetic patients. In this research we have applied an extension of the minimal model to simulate the glucose-insulin dynamics and the glucose and insulin absorption of a diabetic patient. We have validated our results on numerical simulations by using realistic patient data. During the evaluation we have used randomized glucose intakes both in time and amount (as ''unfavorable'' disturbance signals). Furthermore, we did a long-term (30 days) assessment to confirm the stability of the proposed framework. The results have shown that the developed controller effectively intervenes into the process and provides appropriate control action by avoiding hypoglycemia thereby satisfying the predefined quantity and quality requirements.INDEX TERMS Extended Kalman filter, linear matrix inequality, linear parameter varying-based control, tensor product model transformation, type 1 diabetes mellitus.

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Nonlinear soft tissue mechanics based on polytopic Tensor Product modeling

Abstract: Abstract-Achieving

Cited by 2 publications

References 19 publications

Polytopic model based interaction control for soft tissue manipulation

Polytopic model based interaction control for soft tissue manipulation

Control of Diabetes Mellitus by Advanced Robust Control Solution

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