Fractional order controllers are more frequently encountered in industrial applications due to their robustness and the improved performance they offer to the system. A large majority of research papers focus on methods for tuning controllers that are robust to gain variations. A novel approach to the design of a robust fractional order PID controller to variations in the time constant is studied in this manuscript. The procedure mentioned is developed for a first order plus time delay system. The robustness criterion used in the control algorithm is based on partial derivatives. The nonlinear system of equations obtained from all the imposed performance criteria is solved using the graphical method. To prove the efficiency of the proposed strategy, numerical simulations and experimental validation of the resulting controller are performed on a model of the DC servo system. The experimental results explicitly prove that the controller is robust to time-constant variations within the range of $\pm 70\%$.

Anesthesia is arguably one of the most significant milestones in medical history, fundamentally transforming surgery from a traumatic last resort into a safe, humane, and sophisticated science. Closed-loop anesthesia represents the cutting edge of surgical pharmacology, utilizing automated systems to maintain a patient’s state of sedation or analgesia. Designing and testing controllers can be easily facilitated using dedicated patient simulators. This review provides a critical assessment of current patient simulators, specifically examining their mathematical models, functional capabilities, and utility in control system engineering. Through a series of simulation examples and a comparative analysis, the paper illustrates the incremental value of each tool relative to earlier iterations. Additionally, the scope extends to web-based simulators and engines, culminating in a roadmap for future research and technological advancements in the field. By highlighting the advantages and limitations of existing patient simulators and providing insight into possible developments, this survey emphasizes the need for further and deeper research on this topic. Such improvements are vital for the possible acceptance of closed-loop anesthesia in clinical settings.

According to data from the World Federation of Societies of Anesthesiologists, numerous countries across Asia and Africa have fewer than one anaesthesiologist per 100,000 people. Upskilling nurse anaesthetists in these regions is critical to improving clinical outcomes, and interactive virtual patient simulators offer a safe environment to explore complex clinical scenarios. This paper introduces an advanced general anaesthesia patient simulator engineered to bridge the accessibility gap left by existing platforms, which often require expert programming knowledge and restrict users to manual titration. Our simulator features an intuitive graphical user interface optimised for clinical education and natively supports both manual and closed-loop anaesthesia administration. The platform includes a suite of pre-designed controllers, specifically standard PIDs and two distinct fractional-order FO-PID variants, highlighting a novel robust FO-PID framework engineered to mitigate high patient variability. The deployment of these embedded controllers is demonstrated via a Depth of Hypnosis regulation case study and validated across a diverse cohort of 19 virtual patients. Closed-loop evaluation reveals that while the standard PID achieves a lower average mean squared error during the maintenance phase, the fractional-order alternatives deliver significantly superior robustness and inter-patient consistency. Ultimately, integrating this simulator into clinical training frameworks offers a viable pathway to reduce nursing workload and enhance patient safety through optimised automated drug delivery.

Hemodynamic management is extremely important in cardiac patients undergoing surgery. Traditionally, the approach towards hemodynamic stabilization included the control of both mean arterial pressure (MAP) and cardiac output (CO) using Sodium Nitroprusside and Dopamine. More efficient and safer drugs have been introduced, such as Norepinephrine. The focus of this manuscript is to provide some preliminary results regarding the closed loop control of MAP using Norepinephrine. However, to design a dedicated control system, a mathematical model describing the effect of Norepinephrine on mean arterial pressure is required. Only a handful of papers describe a pharmacokinetic–pharmacodynamic (PK-PD) model. In this paper, a simplified model suitable for designing a controller is determined based on PK-PD insights and existing clinical data. Existing closed loop controllers are based on the simple proportional integral derivative (PID) controller, with limited robustness to patient variability. In this paper, two advanced control strategies are proposed to replace PID. The closed loop simulation results include reference tracking and disturbance rejection and show the efficiency and robustness of the proposed control algorithms. The preliminary results set the background for further research in this area.