A new fractional-order general type-2 fuzzy predictive control system and its application for glucose level regulation

Observer based nonlinear control design for glucose regulation in type 1 diabetic patients: An LMI approach

Preparation and characterization of hydroxyapatite nanoparticles carrying insulin and gallic acid for insulin oral delivery.

Over the past decade, there has been an unprecedented international focus on improved quality and availability of medical care, which has reignited interest in clinical automation and drawn researchers toward novel solutions in the field of physiological closed-loop control systems (PCLCs). Today, multidisciplinary groups of expert scientists, engineers, clinicians, mathematicians, and policy-makers are combining their knowledge and experience to develop both the next generation of PCLC-based medical equipment and a collaborative commercial/academic infrastructure to support this rapidly expanding frontier. In the following article, we provide a robust introduction to the various aspects of this growing field motivated by the recent and ongoing work supporting two leading technologies: the artificial pancreas (AP) and automated anesthesia. Following a brief high-level overview of the main concepts in automated therapy and some relevant tools from systems and control theory, we explore – separately – the developments, challenges, state-of-the-art, and probable directions for AP and automated anesthesia systems. We then close the review with a consideration of the common lessons gleaned from these ventures and the implications they present for future investigations and adjacent research.

Physiological Closed-Loop Control (PCLC) Systems: Review of a Modern Frontier in Automation

Magnetic Levitation systems are nonlinear, frictionless and noiseless which use electromagnetic fields to hover ferromagnetic objects in air. For this purpose, we have proposed Supertwisting and Integral Backstepping sliding mode controllers. The designed controllers ensure the air gap to be maintained at the desired value while tracking the magnetic flux and momentum to their respective references. The stability analysis of the proposed controllers has been presented using Lyapunov theory which proves the global asymptotic stability of the system. The performance of the proposed controllers is analyzed using ODE 45 solver in MATLAB/Simulink environment. The proposed controllers reduce the chattering and improves the dynamic response of the system. Robustness of the proposed controllers has been checked by adding noise and disturbance in system's state space model. Furthermore, comparison of proposed controllers with each other, with conventional PI and recently published nonlinear controllers for MagLev system in terms of dynamic response has also been presented. The results show that the dynamic behavior of supertwisting sliding mode controller is best among analyzed controllers.

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NasimUllah

Papers

Super twisting sliding mode control algorithm for developing artificial pancreas in type 1 diabetes patients