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Drug regulatory paradigms are dependent on the hemodynamic system as it serves to distribute and clear the drug in/from the body. While focusing on the objective of the drug paradigm at hand, it is important to maintain stable hemodynamic variables. In this work, a biomedical application requiring robust control properties has been used to illustrate the potential of an autotuning method, referred to as the fractional order robust autotuner. The method is an extension of a previously presented autotuning principle and produces controllers which are robust to system gain variations. The feature of automatic tuning of controller parameters can be of great use for data-driven adaptation during intra-patient variability conditions. Fractional order PI/PD controllers are generalizations of the well-known PI/PD controllers that exhibit an extra parameter usually used to enhance the robustness of the closed loop system. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Fractional order PI/PD controllers are generalizations of the well-known PI/PD controllers with an extra parameter usually used to enhance the robustness of the closed loop system. In this paper, an autotuning method, referred to as the fractional order KC autotuner, is presented for tuning fractional order PI/PD controllers. The method is an extension of a previously presented autotuning principle and produces controllers, which are robust to system gain variations. Additionally, the method can also be adapted to obtain robust controllers to time delay, time constant variations, etc. The advantages of this autotuning method reside in the simplicity of the approach: 1) it requires solely one single sine test on the process; 2) it does not need the process model and 3) it eliminates the complex nonlinear equations in the traditional fractional order controller design procedure. Numerical examples are included to validate the method. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

In this paper the application of robust Fractional Order Proportional-Integral (FO-PI) autotuning control strategy is presented and applied to heterogeneous dynamic systems using decentralized control. The automatic tuning of controller gains is based on a single sine test, with user-defined robustness margins guaranteed. Its performance is compared against two other fractional order controllers based on PI gain-crossover autotuning method and Internal Model Control (IMC). The closed loop control simulations applied on the heterogeneous dynamic systems indicate that the proposed method performs properly.

This paper proposes fractional order autotuner controller for the benchmark refrigeration system. The method is an extension of a previously presented autotuning principle and produces a robust fractional order PI controller to gain variations. Fractional order PI controllers are generalizations of the integer order PI controllers, which have a supplementary parameter that is usually used to enhance the robustness of the closed loop system. The method is not restricted to robustness to gain variations and can be adapted to obtain robust fractional order controllers to time delay or time constant variations, for example. The autotuning method presented in this paper has several advantages such as the need for a single sine test to be applied to the process to extract the necessary information and the elimination of complex nonlinear equations in the tuning procedure for fractional order controllers. The results obtained on the benchmark system indicate the method has high potential for real-life applications.

This paper presents a data-driven gain adaptation mechanism in order to make the usability of the UGent Knee Rig (UGKR) more flexible. The design of the UGKR is unique as it is characterized by a movable ankle joint contrary to traditional dynamic knee rigs which are used to investigate knee kinematics and surgical techniques. This feature allows the UGKR to perform both bicycle motions and squat motions while applying a quadriceps force and hamstring forces. The control of the UGKR is a model-based control strategy which requires time-consuming system identification for each new knee specimen. A data-driven gain adaptation mechanism is developed reducing the necessary time for identification creating a flexible usability. Two adaptation mechanisms are implemented and tested on both a mechanical hinge and a cadaver knee: a rectangular sequence and a polar sequence. The results from squat and bicycle tests indicate that rectangular sequence provides good performance for the rigid mechanical hinge, however, it fails for the elastic cadaver knee during full extension. It is shown that the polar sequence results in good performance for the cadaver knee compared to the rectangular mechanism. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Optimal and safe control of drug delivery systems with continuous infusion protocol is of key importance to avoid over- or under-dosing of the patient. By implementing close-loops one is able to optimize the amount of drug given to the patient. In this paper a robust control methodology is presented. Emerging tools from fractional calculus have been considered and a fractional order PI controller for drug dosing during hypnosis has been designed. In this paper a robust fractional order control of hypnosis is proposed. The controller has been evaluated on an artificial data set of 24 patients and the results indicate that such a control strategy is robust to uncertainty stemming from the inter- and intra-patient variability. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Many regulatory loops in drug delivery systems for depth of anesthesia optimization problem consider only the effect of the controller output on the patient pharmacokinetic and pharmacodynamic response. In reality, these drug assist devices are over-ruled by the anesthesiologist for setpoint changes, bolus intake and additional disturbances from the surgical team. Additionally, inter-patient variability imposes variations in the dynamic response and often intra-patient variability is also present. This paper introduces for the first time in literature a study on the effect of both controller and anesthesiologist in the loop for hypnosis regulation. Among the many control loops, model based predictive control is closest to mimic the anticipatory action of the anesthesiologist in real life and can actively deal with issues as time lags, delays, constraints, etc. This control algorithm is here combined with the action of the anesthesiologist. A disturbance signal to mimic surgical excitation has been introduced and a database of 25 patients has been derived from clinical insight. The results given in this paper reveal the antagonist effect in closed loop of the intervention from the anaesthesiologist when additional bolus intake is present. This observation explains induced dynamics in the closed loop observed in clinical trials and may be used as a starting point for next step in developing tools for improved assistance in clinical care. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

In this paper, a non-cooperative distributed model predictive control (DMPC) algorithm for tracking constant references is developed and evaluated. As such, an augmented model is employed (i.e. the control loop is embedded with integrators) and the augmented state contains the state increments and the error between the reference and the predicted output. The algorithm is tested in real life experiments on the quadruple tank process with non-minimum phase behaviour. The experimental results show acceptable performance index for the DMPC method when compared with the centralized approach.

This work presents a linear, constrained, multivariable predictive control strategy, i.e. EPSAC (Extended Prediction Self-Adaptive Control) applied to a train of three distillation columns. The columns are used to obtain the carbon isotope 13C used widely in medicine and specific industries. The oversimplified models of the three columns stem from a real-life plant designed and constructed in the National Institute for Research and Development for Isotopic and Molecular Technologies, in Cluj Napoca, Romania. The simulation results suggest the strategy is applicable to this process.

In multi-modular process architectures with independent but interacting subsystems, identification may not be the first choice at hand for closed loop control. A robust relay-based PID autotuning strategy is presented and validated on a quadruple tank system with non-minimum phase dynamics. The controller ensures a specified closed loop robustness, which is of great benefit to the overall performance. The experimental results suggest that the proposed method fulfils the robustness requirement and performs well in various operating conditions of the testbench.

This paper presents the structure, functionality and application of an improved Remote Laboratory for engineering students hosted at Ghent University. The Remote Laboratory consists of two setups: Ball and Plate system and Quadruple Water Tank system. These setups introduce basic control aspects such as PID control design and non-minimum phase systems. Also more challenging aspects such as multiple-input-multiple-output control, decoupled and decentralized systems and advanced control strategies such as Internal Model Control or Model Predictive Control can be investigated on the setups. Based on a feedback study that targeted the bachelor degree students, the level of effectiveness of this concept has been shown but also possible functional enhancements that can be applied to the systems have been pointed out. The feedback survey data concluded that the Remote Laboratory has attracted the attention of students and had a positive impact in their training.