Fabricio Garelli

Safety Auxiliary Feedback Element for the Artificial Pancreas in Type 1 Diabetes

The artificial pancreas aims at the automatic delivery of insulin for glycemic control in patients with type 1 diabetes, i.e., closed-loop glucose control. One of the challenges of the artificial pancreas is to avoid controller overreaction leading to hypoglycemia, especially in the late postprandial period. In this study, an original proposal based on sliding mode reference conditioning ideas is presented as a way to reduce hypoglycemia events induced by a closed-loop glucose controller. The method is inspired in the intuitive advantages of two-step constrained control algorithms. It acts on the glucose reference sent to the main controller shaping it so as to avoid violating given constraints on the insulin-on-board. Some distinctive features of the proposed strategy are that 1) it provides a safety layer which can be adjusted according to medical criteria; 2) it can be added to closed-loop controllers of any nature; 3) it is robust against sensor failures and overestimated prandial insulin doses; and 4) it can handle nonlinear models. The method is evaluated in silico with the ten adult patients available in the FDA-accepted UVA simulator.

Reactive Sliding-Mode Algorithm for Collision Avoidance in Robotic Systems

This brief presents a reactive reference conditioning algorithm for robot collision avoidance based on geometric invariance and sliding-mode (SM) ideas. First, constraints are defined in terms of the measurements given by the robots sensors in order to guarantee that collisions will not occur. Then, a supervisory loop ensures the fulfillment of the constraints modifying the reference trajectory as much as necessary by means of a discontinuous control law. The proposed algorithm activates only when the constraints are about to be violated and, thus, in contrast to conventional SM approaches, there exists no reaching mode to the limit surface of the constraints (sliding surface). The validity and effectiveness of the proposed approach is substantiated by simulation and experimental results using a mobile robot equipped with infrared sensors.

Sliding mode speed auto-regulation technique for robotic tracking

In advanced industry manufacturing involving robotic operations, the required tasks can be frequently formulated in terms of a path or trajectory tracking. In this paper, an approach based on sliding mode conditioning of a path parametrization is proposed to achieve the greatest tracking speed which is compatible with the robot input constraints (joint speeds). Some distinctive features of the proposal are that: (1) it is completely independent of the robot parameters, and it does not require a priori knowledge of the desired path either, (2) it avoids on-line computations necessary for conventional analytical methodologies, and (3) it can be easily added as a supervisory block to pre-existing path tracking schemes. A sufficient condition (lower bound on desired tracking speed) for the sliding mode regulation to be activated is derived, while a chattering amplitude estimation is obtained in terms of the sampling period and a tunable first-order filter bandwidth. The algorithm is evaluated on the freely accessible 6R robot model PUMA-560, for which a path passing through a wrist singularity is considered to show the effectiveness of the proposal under hard tracking conditions.

Postprandial response improvement via safety layer in closed-loop blood glucose controllers

Abstract Traditional type 1 diabetes therapies are prone to show poor glucose regulation especially in the postprandial period owing to both physiological and technological limitations. Although a closed-loop controller for glucose regulation has to be tuned to minimize the postprandial excursion and avoid late hypoglycemia, the intrinsic limitations of the problem lead to a trade-off between postprandial peak and late hypoglycemia risk. This paper reveals through an intensive in-silico study with multiple controller tuning combinations that a novel safety layer for glucose controllers, the so-called SAFE loop (Revert et al., 2013), not only reduces the hypoglycemia events but also allows reducing the postprandial glucose excursion, thus breaking the implicit trade-off present in single controllers. The SAFE outer loop monitors the estimated amount of insulin on board, and modifies the control action if it is close to a unique constraint which can be adjusted with clinical criteria. A very challenging test scenario is here implemented including the rate of blood glucose appearance from intakes of mixed meals, diurnal and day-to-day time-varying metabolic changes, inherent drawbacks in sensor and actuator, and other realistic conditions. The results show a significant reduction of hypoglycemia events when SAFE is added, regardless the closed-loop glucose controller, together with a potential postprandial response improvement.

Postprandial blood glucose control using a hybrid adaptive PD controller with insulin-on-board limitation

Abstract This paper addresses the design of blood glucose control during the postprandial period for Type 1 diabetes patients. An artificial pancreas for ambulatory purposes has to deal with the delays inherent to the subcutaneous route, the carbohydrate intakes, the metabolic changes, the glucose sensor errors and noise, and the insulin pump constraints. A time response typically obtained in closed-loop insulin delivery shows hyperglycemia in the early postprandial period caused by the lag in the insulin absorbtion, followed by hypoglycemia caused by control over-reaction. A hybrid control system is proposed in this paper to overcome these problems. An insulin bolus is administered prior to the meals like in open-loop control, whereas a PD controller is used for robust glucose regulation. The controller gain is progressively increased after the bolus from zero up to its nominal value as function of the insulin on board, so that the PD controller becomes fully operational just when the insulin on board falls below a prescribed value. An excessive accumulation of active insulin is avoided in this way, drastically reducing the risk of hypoglycemia. The controller gain is adapted by means of a variable structure algorithm, allowing a very simple software implementation. The robust performance of the control algorithm is intensively assessed in silico on a cohort of virtual patients under challenging realistic scenarios considering mixed meals, circadian variations, time-varying uncertainties, discrete measurement and actuation, sensor errors and other disturbances.

A supervisory loop approach to fulfill workspace constraints in redundant robots

An approach based on geometric invariance and sliding mode ideas is proposed for redundancy resolution in robotic systems to fulfill configuration and workspace constraints caused by robot mechanical limits, collision avoidance, industrial security, etc. Some interesting features of the proposal are that: (1) it can be interpreted as a limit case of the classical potential field-based approach for collision avoidance which requires using variable structure control concepts, (2) it allows reaching the limit surface of the constraints smoothly, depending on a free design parameter, and (3) it can be easily added as a supervisory block to pre-existing redundancy resolution schemes. The algorithm is evaluated in simulation on a 6R planar robot and on the freely accessible 6R robot model PUMA-560, for which the main features of the method are illustrated.

Sliding mode reference conditioning for coordination in swarms of non-identical multi-agent systems

A novel approach is proposed for coordination of swarms of dynamical systems in order to provide them with a desired collective behavior. The approach is based on the sliding mode reference conditioning technique as local interaction handler among neighbor systems. Neighbor systems become connected when a virtual constraint between them is violated, leading to a time-varying switching topology for the connections in the swarm. The approach addresses the problem of coordinating dynamical systems with possibly different dynamics (e.g. linear and nonlinear, different orders, constraints, etc.), assuming there is no leader. The main idea is to shape the systems local feasible references in order to keep them coordinated. Coordination is understood as invariance of a set defined by some aimed relationship among the references. This implies considering the local goals, the systems constraints and the achievable performances as well. To show the applicability of the approach, the problem of coordinating a swarm of different dynamical systems with control saturations is addressed as a particular case.

Dynamical Systems Coordination via Sliding Mode Reference Conditioning

Abstract A novel methodology is proposed for coordination of dynamical systems. The scheme is based on the sliding mode reference conditioning technique in a sort of supervisory level. The approach addresses the problem of coordinating dynamical systems with possible different dynamics ( e.g. linear and nonlinear, different orders, constraints, etc. ). To achieve this, the dynamics of each subsystem are hidden from the coordination mechanism. The main idea is to shape the systems local references in order to keep them coordinated. This implies considering the global goals, the systems constraints and the achievable performances as well. Sliding Mode Reference Conditioning (SMRC) is used for this purpose by means of a hierarchical supervisory structure. To show the applicability of the approach, the problem of coordinating a number of different dynamical systems with control saturations is addressed as a particular case. Coordination will be understood as actuating on the systems references to achieve some collective behavior considering the individual restrictions of each system.

Specific growth rate observer for the growing phase of a Polyhydroxybutyrate production process

This paper focuses on the specific growth rate estimation problem in a Polyhydroxybutyrate bioplastic production process by industrial fermentation. The kinetics of the process are unknown and there are uncertainties in the model parameters and inputs. During the first hours of the growth phase of the process, biomass concentration can be measured online by an optical density sensor, but as cell density increases this method becomes ineffective and biomass measurement is lost. An asymptotic observer is developed to estimate the growth rate for the case without biomass measurement based on corrections made by a pH control loop. Furthermore, an exponential observer based on the biomass measurement is developed to estimate the growth rate during the first hours, which gives the initial condition to the asymptotic observer. Error bounds and robustness to uncertainties in the models and in the inputs are found. The estimation is independent of the kinetic models of the microorganism. The characteristic features of the observer are illustrated by numerical simulations and validated by experimental results.

Model-based scale-up methodology for aerobic fed-batch bioprocesses: application to polyhydroxybutyrate (PHB) production

This work presents a general model-based methodology to scale-up fed-batch bioprocesses. The idea behind this approach is to establish a dynamics hierarchy, based on a model of the process, that allows the designer to determine the proper scale factors as well as at which point of the fed-batch the process should be scaled up. Here, concepts and tools of linear control theory, such as the singular value decomposition of the Hankel matrix, are exploited in the context of process design. The proposed scale-up methodology is first described in a bioprocesses general framework highlighting its main features, key variables and parameters. Then, it is applied to a polyhydroxybutyrate (PHB) fed-batch bioreactor and compared with three empirical criteria, that are traditionally employed to determine the scale factors of these processes, showing the usefulness and distinctive features of this proposal. Moreover, this methodology provides theoretical support to a frequently used empirical rule: scale-up aerobic bioreactors at constant volumetric oxygen transfer coefficient. Finally, similar process dynamic behavior and PHB production set at the laboratory scale are predicted at the new operating scale, while it is also determined that is rarely possible to reproduce similar dynamic behavior of the bioreactor using empirical scale-up criteria.