Event-based MPC for propofol administration in anesthesia.

BACKGROUND AND OBJECTIVE: The automatic control of anesthesia is a demanding task mostly due to the presence of nonlinearities, intra- and inter-patient variability and specific clinical requirements to be meet. The traditional approach to achieve the desired depth of hypnosis level is based on knowledge and experience of the anesthesiologist. In contrast to a typical automatic control system, their actions are based on events that are related to the effect of the administrated drug. Thus, it is interesting to build a control system that will be able to mimic the behavior of the human way of actuation, simultaneously keeping the advantages of an automatic system. METHODS: In this work, an event-based model predictive control system is proposed and analyzed. The nonlinear patient model is used to form the predictor structure and its linear part is exploited to design the predictive controller, resulting in an individualized approach. In such a scenario, the BIS is the controlled variable and the propofol infusion rate is the control variable. The event generator governs the computation of control action applying a dead-band sampling technique. The proposed control architecture has been tested in simulation considering process noise and unmeasurable disturbances. The evaluation has been made for a set of patients using nonlinear pharmacokinetic/pharmacodynamic models allowing realistic tests scenarios, including inter- and intra-patient variability. Results For the considered patients dataset the number of control signal changes has been reduced of about 55% when compared to the classical control system approach and the drug usage has been reduced of about 2%. At the same time the control performance expressed by the integrated absolute error has been degraded of about 11%. CONCLUSIONS: The event-based MPC control system meets all the clinical requirements. The robustness analysis also demonstrates that the event-based architecture is able to satisfy the specifications in the presence of significant process noise and modelling errors related to inter- and intra-patient variability, providing a balanced solution between complexity and performance.

A seasonal simulation approach for culture depth influence on the temperature for different characterized microalgae strains.

Irradiance and temperature are among the most important variables that affect microalgae growth, being both difficult to control in outdoor raceway reactors utilized for large-scale production of microalgae biomass. They are mainly a function of the location of the reactors, thus, producing certain strains of microalgae in inappropriate places conduces to the failure of the systems. To be able to determine important parameters of any microalgae strains on the performance of the culture, such as the influence of irradiance and temperature, is a powerful tool in decision-making processes. In addition, whatever the strain and location, operation strategies must be defined for each specific case, such as the imposed dilution rate and culture depth, both influencing the light availability and temperature of the culture as major variables determining the biomass productivity. In this paper, a simulation-based methodology is proposed to establish the influence of season and culture depth on the 1-year age irradiance and temperature of the culture, and thus on the biomass productivity of different microalgae strains. Up to five of the most frequently produced strains, such as Spirulina platensis, Chlorella vulgaris, Nannochloropsis gaditana, Isochrysis galbana, and Scenedesmus almeriensis have been considered. The challenge is to develop an easy-to-manage decision-making tool for the optimal design and operation of large-scale microalgae facilities. Especially, dates for microalgae production and culture depth at which the reactors must be operated will be provided, being valid for any microalgae strain. The proposed methodology will largely contribute to the risk of investment in this field, then to enlarge the relevance of the microalgae production industry.

A modified PID-based control scheme for depth-of-hypnosis control: Design and experimental results.

BACKGROUND AND OBJECTIVE: Many methodologies have been proposed for the control of total intravenous anesthesia in general surgery, as this yields a reduced stress for the anesthesiologist and an increased safety for the patient. The objective of this work is to design a PID-based control system for the regulation of the depth of hypnosis by propofol and remifentanil coadministration that takes into account the clinical practice. METHODS: With respect to a standard PID control system, additional functionalities have been implemented in order to consider specific requirements related to the clinical practice. In particular, suitable boluses are determined and used in the induction phase and a nonzero baseline infusion is used in the maintenance phase when the predicted effect-site concentration drops below a safety threshold. RESULTS: The modified controller has been experimentally assessed on a group of 10 patients receiving general anesthesia for elective plastic surgery. The control system has been able to induce and maintain adequate anesthesia without any manual intervention from the anesthesiologist. CONCLUSIONS: Results confirm the effectiveness of the overall design approach and, in particular, highlight that the new version of the control system, with respect to a standard PID controller, provides significant advantages from a clinical standpoint.

Teaching control courses online during the covid-19 pandemic: some experiences at the University of Brescia.

In this paper we present the experience of online teaching of some control courses during two years of covid-19 pandemic at the University of Brescia. Different (undergraduate and postgraduate) courses are considered and a survey has been conducted with the students to evaluate pros and cons of the new way of teaching. A specific initiative employed in the second year to increase the student engagement has also been evaluated. It is believed that the results of the survey can help in discussing and learning best practices to apply during the pandemic and when this will be finished.

A new model to analyze the temperature effect on the microalgae performance at large scale raceway reactors.

In this study a simplified temperature model for raceway reactors is developed, allowing to determine the temperature of the microalgae culture as a function of reactor design and environmental conditions. The model considers the major phenomena taking place in raceway reactors, especially heat absorption by radiation and heat losses by evaporation among others. The characteristic parameters of the model have been calibrated using genetic algorithms, next being validated with a long set of more than 50 days covering different weather conditions. It is worth to highlight the use of the developed model as a tool to analyze the influence of the temperature on the performance of microalgae cultures at large scale. As example, the annual variation of the performance of up to five different microalgae strains has been determined by computing the temperature index, thus the normalized value of performance of whatever microalgae at the real temperature with respect to that achievable at optimal temperature can be established. Results confirm that only strains tolerant to wide ranges of temperature can be efficiently produced all the year around in large scale outdoor raceway reactors without additional temperature control systems.

Event-Based control of depth of hypnosis in anesthesia.

BACKGROUND AND OBJECTIVE: In this paper, we propose the use of an event-based control strategy for the closed-loop control of the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. METHODS: A new event generator with high noise-filtering properties is employed in addition to a PIDPlus controller. The tuning of the parameters is performed off-line by using genetic algorithms by considering a given data set of patients. RESULTS: The effectiveness and robustness of the method is verified in simulation by implementing a Monte Carlo method to address the intra-patient and inter-patient variability. A comparison with a standard PID control structure shows that the event-based control system achieves a reduction of the total variation of the manipulated variable of 93% in the induction phase and of 95% in the maintenance phase. CONCLUSIONS: The use of event based automatic control in anesthesia yields a fast induction phase with bounded overshoot and an acceptable disturbance rejection. A comparison with a standard PID control structure shows that the technique effectively mimics the behavior of the anesthesiologist by providing a significant decrement of the total variation of the manipulated variable.

Optimized PID control of depth of hypnosis in anesthesia.

BACKGROUND AND OBJECTIVE: This paper addresses the use of proportional-integral-derivative controllers for regulating the depth of hypnosis in anesthesia by using propofol administration and the bispectral index as a controlled variable. In fact, introducing an automatic control system might provide significant benefits for the patient in reducing the risk for under- and over-dosing. METHODS: In this study, the controller parameters are obtained through genetic algorithms by solving a min-max optimization problem. A set of 12 patient models representative of a large population variance is used to test controller robustness. The worst-case performance in the considered population is minimized considering two different scenarios: the induction case and the maintenance case. RESULTS: Our results indicate that including a gain scheduling strategy enables optimal performance for induction and maintenance phases, separately. Using a single tuning to address both tasks may results in a loss of performance up to 102% in the induction phase and up to 31% in the maintenance phase. Further on, it is shown that a suitably designed low-pass filter on the controller output can handle the trade-off between the performance and the noise effect in the control variable. CONCLUSIONS: Optimally tuned PID controllers provide a fast induction time with an acceptable overshoot and a satisfactory disturbance rejection performance during maintenance. These features make them a very good tool for comparison when other control algorithms are developed.

Tuning rules for robust FOPID controllers based on multi-objective optimization with FOPDT models.

In this paper a set of optimally balanced tuning rules for fractional-order proportional-integral-derivative controllers is proposed. The control problem of minimizing at once the integrated absolute error for both the set-point and the load disturbance responses is addressed. The control problem is stated as a multi-objective optimization problem where a first-order-plus-dead-time process model subject to a robustness, maximum sensitivity based, constraint has been considered. A set of Pareto optimal solutions is obtained for different normalized dead times and then the optimal balance between the competing objectives is obtained by choosing the Nash solution among the Pareto-optimal ones. A curve fitting procedure has then been applied in order to generate suitable tuning rules. Several simulation results show the effectiveness of the proposed approach.

On the fragility of fractional-order PID controllers for FOPDT processes.

This paper analyzes the fragility issue of fractional-order proportional-integral-derivative controllers applied to integer first-order plus-dead-time processes. In particular, the effects of the variations of the controller parameters on the achieved control system robustness and performance are investigated. Results show that this kind of controllers is more fragile with respect to the standard proportional-integral-derivative controllers and therefore a significant attention should be paid by the user in their tuning.

An industrial application of a performance assessment and retuning technique for PI controllers.

In this paper we show how a simple methodology for the set-point following performance assessment and automatic tuning of a PI controller can be employed effectively in a real industrial application. In particular, a flow control loop in a pharmaceutical plant is considered. Practical issues related to the implementation in a Distributed Control System are discussed. Results show that the technique is capable of significantly improving the performance of the controller.

Experimental evaluation of a time-optimal plug&control strategy.

In this paper, the application of a time-optimal plug&control strategy is discussed. This strategy automatically makes the controller work properly after simply connecting it to the control architecture, without further intervention from the operator. In particular, a level control task and a temperature control task are considered. Implementation problems are addressed and the effectiveness of the methodology is shown.