Robust nonlinear control design: state-space and Lyapunov techniques
Robust nonlinear control design: state-space and Lyapunov techniques
Kalman Filtering and Neural Networks
Kalman Filtering and Neural Networks
Physiologic insulin delivery with insulin feedback: A control systems perspective
Computer Methods and Programs in Biomedicine
Discrete-Time Nonlinear HJB Solution Using Approximate Dynamic Programming: Convergence Proof
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
High-order neural network structures for identification of dynamical systems
IEEE Transactions on Neural Networks
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Inverse optimal trajectory tracking via a control Lyapunov function (CLF) for discrete time non-linear systems is developed and applied to type 1 diabetes mellitus patients control. The control law calculates the insulin delivery rate in order to prevent hyperglycemia and hypoglycemia levels. To synthesize the inverse optimal control law a quadratic candidate CLF is used. The proposed algorithm is tuned to follow a desired trajectory; this trajectory reproduces the glucose absorption of a healthy person. Simulation results applied for two different patients illustrate the applicability of the control law and a comparison with inverse optimal neural control via passivity is included.