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This paper presents an active disturbance rejection control scheme to automatically regulate the glucose level in type 1 diabetic patients. Although the blood glucose system is nonlinear, in this control approach, it is represented as a linear perturbed system, whose lumped disturbance input is estimated by an Extended State Observer (ESO) and then compensated by an robust controller tuned with Quantitative Feedback Theory (QFT). The robust control scheme uses a Smith predictor for the time delay compensation and allows taking into account the inter-patient variability presented in the glucose control problem. In order to validate the effectiveness of this approach, the controller is tested in silico on a cohort of adult patients of the UVA/Padova metabolic simulator, which has been accepted by the Food and Drug Administration (FDA). In silico results indicate that safe blood glucose control can be achieved by the proposed controller.

This paper presents the modification of the well-known pole placement method for first-order systems and PI control for the tracking problem. The main drawback of the original method is the presence of a zero in the closed-loop transfer function, which has a negative influence in the desired closed-loop response. Typically, this effect is cancelled by using a reference filter within a two-degree-of-freedom control scheme. However, in this work we present a simple modification of the original method that allows us to consider the zero effect in advance. First, the effect of a zero term in the response of second-order systems is analyzed to see how the time response parameters (overshoot, peak time, rise time and settling time) are affected. Afterwards, this analysis and the resulting equations are combined with the pole placement method to propose the new solution. Finally, simulation results are presented to demonstrate the advantages of the proposed method, where it is shown that faster responses than by using a reference filter are obtained.

Feedforward control schemes to compensate for disturbances are very well known in process control. In those control approaches, PID controllers are usually considered in the feedback loop, where nominal design for both feedback and feedforward controllers are commonly performed. This paper presents a robustness analysis to study how uncertainties can affect the classical feedforward control scheme. Afterwards, a robust PID controller is designed by using Quantitative Feedback Theory to account for these uncertainties and to fulfill robust specificaitons for the regulation control problem. Results based on frequency and time domains are presented.

This document addresses the problem of controlling a one-stage refrigeration cycle by using the opening of the expansion valve and the compressor speed as control variables, while the outlet temperature of evaporator secondary flux and the superheating degree of refrigerant at evaporator outlet are the controlled variables. An uncertain matrix function is obtained in order to represent the full operating range of the nonlinear system. Thus, the control decentralized approach control consists of designing Generalized- Proportional-Integral (GPI) observers for the internal loops of each controlled variable while PID controllers are tuned based on the Quantitative Feedback Theory for the respective external loops. Simulations results show that the robust controllers reacts quickly reference settings, despite the non-measurement of the disturbance variables and the dynamic coupling of the multi-variable system, compared to decentralised single PIDs proposed with the benchmark.

This paper presents the black-box modelling and the simulator of a non-commercial hex-rotor platform created completely at the University of Almeria, in order to have a tool for teaching control and robotics subjects in industrial engineering and computer science degrees. This tool aims to be a real and simulated scenario for control and robotics students who will be able to implement their controllers in both the simulator and the real UAV.

This paper presents the idea about how to combine a set of software and hardware resources available in literature to be used as support to control engineering education. The available tools allow to mix topics related to programming, communications, operating systems, and control theory. The well-known Raspberry Pi board is used as platform to exploit the di_erent proposed concepts. SciPy, Matplotlib, and NumPy libraries, which are Python-based open-source libraries for scienti_c computing and graphical representation, are used to perform Matlab-like simulations and to implement classical control loops. On the other hand, virtual processes developed in Easy Java Simulations are adapted to be controlled through the network from a controller implemented on the Raspberry Pi with Python. This option is very useful from a teaching point of view since time-based, networked-based, or event-based control approaches can be easily introduced on this proposed architecture. Furthermore, once students know how to implement control loops on the Raspberry Pi using Python, external real processes can be easily controlled by using the GPIO interface available in the this electronic board. Then, a project based on these tools and ideas is motivated and presented in this paper to control a two-tank level process © Copyright IFAC 2015.