Arbitrary‐order sliding mode‐based robust control algorithm for the developing artificial pancreas mechanism

Alam, Waqar; Khan, Qudrat; Riaz, Raja Ali; Akmeliawati, Rini

doi:10.1049/iet-syb.2018.5075

Cited by 5 publications

(2 citation statements)

References 39 publications

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“…Other controller technique like an inverse optimal control (IOC) that integrates neural identification, a multi-step prediction (MSP) technique, and Takagi–Sugeno (T–S) fuzzy inference is designed in 12 . While the nonlinear control approaches were proposed to regulate the BGL such as terminal synergetic controller and state feedback linearization based controller 13 , arbitrary-order sliding mode based robust controller 14 , backstepping sliding mode controller and super-twisting controller 15 , observer based nonlinear controller 16 , robust observer based adaptive controller 1 , finite‐time robust feedback controller based using backstepping approach 17 , integral backstepping controller, backstepping controller 18 , fuzzy logic based controller 19 .…”

Section: Related Workmentioning

confidence: 99%

Optimized type-2 fuzzy controller based on IoMT for stabilizing the glucose level in type-1 diabetic patients

Sayed,

Zalam,

Elhoushy

et al. 2023

Sci Rep

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Due to advancements in existing Internet of Medical Things (IoMT) systems and devices, the blood glucose level (BGL) for type-1 diabetic patients (T1DPs) is effectively and continually monitored and controlled by Artificial Pancreas. Because the regulation of BGL is a very complex process, many efforts have been conducted to design a powerful and effective controller for the exogenous insulin infusion system. The main objective of this study is to propose an optimized interval type-2 fuzzy (IT2F) based controller of artificial pancreas for regulation BGL of T1DP based on IoMT. The proposed controller should avoid the risk of hyperglycemia and hypoglycemia situations that T1DP faces during the infusion of exogenous insulin. The main contribution of this work is using meta-heuristic method called grey wolf optimizer (GWO) to tune the footprint of uncertainty for IT2F’s membership functions to inject the proper dose of insulin under different conditions. The nonlinear extended Bergman minimal model (EBMM) with uncertainty is used to represent the blood glucose regulation and represent the dynamics of meal disturbance in T1DP. The effectiveness and the performance of the proposed controller are investigated using MATLAB/Simulink platform. Simulation results show that the proposed controller can avoid both severe hypoglycemia and hyperglycemia for nominal parameters of the model, in addition to model under the presence of both parametric uncertainty and uncertain meal disturbance.

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Section: Related Workmentioning

confidence: 99%

Optimized type-2 fuzzy controller based on IoMT for stabilizing the glucose level in type-1 diabetic patients

Sayed,

Zalam,

Elhoushy

et al. 2023

Sci Rep

View full text Add to dashboard Cite

show abstract

“…While its control functioning is directly related to the operating characteristics, economic effective generation and equipment security stability. So far, various kinds of control strategies are proposed for MPPT design, which include [ 6 , 7 ], PID control, model predictive control [ 8 ], neuro-fuzzy control [ 9 , 10 ], adaptive backstepping control [ 11 , 12 ], sliding mode control scheme [ 13 – 15 ] and an integral-based terminal sliding mode control strategy [ 16 ]. Moreover, interconnection and damping assignment-based control schemes are presented in [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Certainty equivalence-based robust sliding mode control strategy and its application to uncertain PMSG-WECS

et al. 2023

Self Cite

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This work focuses on maximum power extraction via certainty equivalence-based robust sliding mode control protocols for an uncertain Permanent Magnet Synchronous Generator-based Wind Energy Conversion System (PMSG-WECS). The considered system is subjected to both structured and unstructured disturbances, which may occur through the input channel. Initially, the PMSG-WECS system is transformed into a Bronwsky form, i.e., controllable canonical form, which is composed of both internal and visible dynamics. The internal dynamics are proved stable, i.e., the system is in the minimum phase. However, the control of visible dynamics, to track the desired trajectory, is the main concern. To carry out this task, the certainty equivalence-based control strategies, i.e., conventional sliding mode control, terminal sliding mode control and integral sliding mode control are designed. Consequently, a chattering phenomenon is suppressed by the employment of equivalent estimated disturbances, which also enhance the robustness of the proposed control strategies. Eventually, a comprehensive stability analysis of the proposed control techniques is presented. All the theoretical claims are verified via computer simulations, which are performed in MATLAB/Simulink.

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Robust dynamic output feedback control of blood glucose level in diabetic rat with robust descriptor Kalman filter

Rahmanian

Asemani

Dehghani

et al. 2022

Biomedical Signal Processing and Control

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Arbitrary‐order sliding mode‐based robust control algorithm for the developing artificial pancreas mechanism

Cited by 5 publications

References 39 publications

Optimized type-2 fuzzy controller based on IoMT for stabilizing the glucose level in type-1 diabetic patients

Optimized type-2 fuzzy controller based on IoMT for stabilizing the glucose level in type-1 diabetic patients

Certainty equivalence-based robust sliding mode control strategy and its application to uncertain PMSG-WECS

Robust dynamic output feedback control of blood glucose level in diabetic rat with robust descriptor Kalman filter

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