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Background and Objective: New proposals to improve the regulation of hypnosis in anaesthesia based on the development of advanced control structures emerge continuously. However, a fair study to analyse the real benefits of these structures compared to simpler clinically validated PID-based solutions has not been presented so far. The main objective of this work is to analyse the performance limitations associated with using a filtered PID controller, as compared to a high-order controller, represented through a Youla parameter. Methods: The comparison consists of a two-steps methodology. First, two robust optimal filtered PID controllers, considering the effect of the inter-patient variability, are synthesised. A set of 47 validated paediatric pharmacological models, identified from clinical data, is used to this end. This model set provides representative inter-patient variability Second, individualised filtered PID and Youla controllers are synthesised for each model in the set. For fairness of comparison, the same performance objective is optimised for all designs, and the same robustness constraints are considered. Controller synthesis is performed utilising convex optimisation and gradient-based methods relying on algebraic differentiation. The worst-case performance over the patient model set is used for the comparison. Results: Two robust filtered PID controllers for the entire model set, as well as individual-specific PID and Youla controllers, were optimised. All considered designs resulted in similar frequency response characteristics. The performance improvement associated with the Youla controllers was not significant compared to the individually tuned filtered PID controllers. The difference in performance between controllers synthesized for the model set and for individual models was significantly larger than the performance difference between the individual-specific PID and Youla controllers. The different controllers were evaluated in simulation. Although all of them showed clinically acceptable results, the robust solutions provided slower responses. Conclusion: Taking the same clinical and technical considerations into account for the optimisation of the different controllers, the design of individual-specific solutions resulted in only marginal differences in performance when comparing an optimal Youla parameter and its optimal filtered PID counterpart. The inter-patient variability is much more detrimental to performance than the limitations imposed by the simple structure of the filtered PID controller.

The high concern about climate change has boosted the promotion of renewable energy systems, being the wind power one of the key generation possibilities in this field. In this context, with the aim of ensuring the energy efficiency, the present work deals with the fault detection in the power electronic circuits of a wind generator system placed in a bioclimatic house. To do so, different outliers that emulate harmonic distortion appearance are tested. To implement a system capable of detecting this anomalous situations, six different one-class techniques are used, whose performance is thoroughly analyzed, offering interesting performance. info:eu-repo/semantics/publishedVersion

[Resumen] En este trabajo se presenta una metodología para desarrollar un gemelo digital para un proceso industrial. El proceso es una lavandería industrial hospitalaria que puede ser caracterizada como una cadena de suministro de lazo cerrado. Una característica del proceso estudiado es la presencia de incertidumbre en la entrada, lo que dificulta la toma de decisiones en el proceso de producción. Para facilitar esta toma de decisiones se plantea el desarrollo de un gemelo digital basado en un sistema de lógica borrosa multinivel. La evaluación de la herramienta propuesta se ha hecho con datos reales obtenidos de una lavandería. Se ha comprobado que la propuesta ofrece resultados satisfactorios demostrando el potencial de esta herramienta en los procesos de producción. [Abstract] This paper presents a methodology to develop a digital twin for an industrial process. The process is a hospital industrial laundry, that can be characterized as a Closed-loop supply chain. A characteristic of the process studied is the presence of uncertainty in the input, which makes decision making in the production process difficult. To facilitate this decision making, the development of a Digital Twin based on a multilevel fuzzy logic system is considered. The evaluation of the proposed tool has been done with real data obtained from a laundry. It has been proven that the proposal offers satisfactory results, demonstrating the potential of this tool in the production processes.

"Diabetes is one of the most prevalent chronic diseases in the world, especially in middle- and low-income countries. Inter- and intra-patient variability greatly hinders the establishment of effective treatments by clinicians, even among those most experienced. This variability also prevents health administrations to establish adequate controls that guarantee the application of the most cost-effective interventions. In this work, we propose a decision support system that uses simulation and machine learning as tools to provide the clinician with information adapted to the patient on the best intervention for a patient in terms of effectiveness and cost-effectiveness."

The significant industrial developments in terms of digitalization and optimization, have focused the attention on anomaly detection techniques. This work presents a detailed study about the performance of different one-class intelligent techniques, used for detecting anomalies in the performance of an ultrasonic sensor. The initial dataset is obtained from a control level plant, and different percentage variations in the sensor measurements are generated. For each variation, the performance of three one-class classifiers are assessed, obtaining very good results.

BACKGROUND Delay in the propofol pharmacodynamics effect is commonly observed in total intravenous anesthesia (TIVA). To face the delay in the hypnosis control, we have proposed a proportional-integral (PI) controller with a Smith predictor (PI+Smith). We have evaluated the feasibility of this closed-loop control for propofol administration and compared the performance with manual administration guided by the Bispectral Index (BIS). METHODS Fifty-seven adult patients under TIVA with propofol and remifentanil were randomly assigned to a PI+Smith or a manual control (MC) group. The BIS target was set to 50. The performance was compared through the global score (GS), median performance error (MDPE), median absolute performance error (MDAPE), offset and Wobble. RESULTS A total of 29 patients in the MC and 25 in the PI+Smith groups completed this study. Performance was significantly better in the PI+Smith group: global score was 25 (19 to 37) for PI+Smith versus 44 (32 to 57) for MC (P

Current advanced control strategies developed in Adaptive Optics field are based on optimal techniques in order to reject the effect of atmosphere turbulence on the phase of wavefront of the incoming light. The widely researched LQG controller relies basically on models that try to capture the temporal evolution of the atmospheric wavefront. Models based on both Cn2 spatial priors and temporal dynamics have been proposed for SCAO and MOAO systems. The attractive performance of LQG is based on having an accurate model of the wavefront distortion. However, abrupt changes in conditions that directly affect the atmosphere produce a significant decrease in the LQG performance. To deal with this problem, an Active Disturbance Rejection Control (ADRC) strategy is proposed. ADRC, is an unconventional design strategy capable of overcoming the internal dynamics of the system and the external disturbances. The key idea is to treat the unknown information mainly due to atmosphere turbulence as state variable that can be estimated by an Extended State Observer (ESO). Instead of depending on a model, the controller draws the information needed to control the system from the ESO. Consequently, the control law for the Adaptive Optics system can be designed without the mathematical expression of the disturbances. As a result, the combined effect of the non-considered internal dynamics and the external disturbances is estimated and actively rejected. This contribution is focused on adapting ADRC method to Adaptive Optics requirements.

Objective The main objective of this research is the design and implementation of a new fuzzy logic tool for automatic drug delivery in patients undergoing general anesthesia. The aim is to adjust the drug dose to the real patient needs using heuristic knowledge provided by clinicians. A two-level computer decision system is proposed. The idea is to release the clinician from routine tasks so that he can focus on other variables of the patient. Methods The controller uses the Bispectral Index (BIS) to assess the hypnotic state of the patient. Fuzzy controller was included in a closed-loop system to reach the BIS target and reject disturbances. BIS was measured using a BIS VISTA monitor, a device capable of calculating the hypnosis level of the patient through EEG information. An infusion pump with propofol 1% is used to supply the drug to the patient. The inputs to the fuzzy inference system are BIS error and BIS rate. The output is infusion rate increment. The mapping of the input information and the appropriate output is given by a rule-base based on knowledge of clinicians. Results To evaluate the performance of the fuzzy closed-loop system proposed, an observational study was carried out. Eighty one patients scheduled for ambulatory surgery were randomly distributed in 2 groups: one group using a fuzzy logic based closed-loop system (FCL) to automate the administration of propofol (42 cases); the second group using manual delivering of the drug (39 cases). In both groups, the BIS target was 50. Conclusions The FCL, designed with intuitive logic rules based on the clinician experience, performed satisfactorily and outperformed the manual administration in patients in terms of accuracy through the maintenance stage.