Robust nonlinear control of blood glucose in diabetic patients subject to model uncertainties.

Recent advances in the artificial pancreas system provide an emerging treatment option for type 1 diabetes. The performance of the blood glucose regulation directly relies on the accuracy of the glucose-insulin modeling. Sorenson model involves the behavior of different organs and offers precise representation.

Model predictive-based reset gain-scheduling dynamic control law for polytopic LPV systems.

This paper proposes a novel systematic approach for designing a reset gain-scheduling dynamic controller based on a model predictive method for a class of nonlinear systems represented by polytopic linear parameter varying models. The proposed design procedure involves offline and online steps. In the offline step, sufficient conditions of the gain-scheduling dynamic controller design in terms of linear matrix inequalities are derived through a novel D-stability region.

Nonlinear system identification based on Takagi-Sugeno fuzzy modeling and unscented Kalman filter.

This paper proposes two novel Kalman-based learning algorithms for an online Takagi-Sugeno (TS) fuzzy model identification. The proposed approaches are designed based on the unscented Kalman filter (UKF) and the concept of dual estimation. Contrary to the extended Kalman filter (EKF) which utilizes derivatives of nonlinear functions, the UKF employs the unscented transformation.

An optimal general type-2 fuzzy controller for Urban Traffic Network.

Urban traffic network model is illustrated by state-charts and object-diagram. However, they have limitations to show the behavioral perspective of the Traffic Information flow. Consequently, a state space model is used to calculate the half-value waiting time of vehicles.

T-S fuzzy model predictive speed control of electrical vehicles.

This paper proposes a novel nonlinear model predictive controller (MPC) in terms of linear matrix inequalities (LMIs). The proposed MPC is based on Takagi-Sugeno (TS) fuzzy model, a non-parallel distributed compensation (non-PDC) fuzzy controller and a non-quadratic Lyapunov function (NQLF). Utilizing the non-PDC controller together with the Lyapunov theorem guarantees the stabilization issue of this MPC.