To improve the glycemic regulation in clamping, a modification of the recursive least squares (RLS) estimation to be applied to any self-tuning adaptive control algorithm has been developed. It has been used in combination with a pole assignment controller, and its results have been compared through computer simulation in 12 test models with 3 other algorithms. It produces an improvement in the efficiency and the control cost, and it shows indications of ameliorating the stability. It also has been observed that for glycemic control, a minimum variance controller (control advance moving average controller [CAMAC]) is very efficient, whereas an empirical type of controller (Clemens) requires low control action. Some recommendations are made for the use of the algorithm in clamping in a hypothetical electromechanical endocrine artificial pancreas.