Fractional order modeling and control of a smart beam

Smart beams are one of the most frequently used means of studying vibrations in airplane wings. Their mathematical models have been so far solely based on classical approaches that ultimately involve integer order transfer functions. In this paper, a different approach towards modeling such smart beams is considered, an approach that is based on fractional calculus. In this way, a fractional order model of the smart beam is obtained, which is able to better capture the dynamics of the system. Based on this novel fractional order model, a fractional order PD mu controller is then tuned according to a set of three design constraints. This design leads to a closed loop system that exhibits a much smaller resonant peak compared to the uncompensated smart beam system. Experimental results are provided, considering both passive and active control responses of the smart beam, showing that a significant improvement of the closed loop behavior is obtained using the designed controller

Mathematical modelling with experimental validation of viscoelastic properties in non-Newtonian fluids

The paper proposes a mathematical framework for the use of fractional-order impedance models to capture fluid mechanics properties in frequency-domain experimental datasets. An overview of non-Newtonian (NN) fluid classification is given as to motivate the use of fractional-order models as natural solutions to capture fluid dynamics. Four classes of fluids are tested: oil, sugar, detergent and liquid soap. Three nonlinear identification methods are used to fit the model: nonlinear least squares, genetic algorithms and particle swarm optimization. The model identification results obtained from experimental datasets suggest the proposed model is useful to characterize various degree of viscoelasticity in NN fluids. The advantage of the proposed model is that it is compact, while capturing the fluid properties and can be identified in real-time for further use in prediction or control applications. This article is part of the theme issue 'Advanced materials modelling via fractional calculus: challenges and perspectives'

An alternative design approach for Fractional Order Internal Model Controllers for time delay systems

Introduction: Fractional Order Internal Model Control (FO-IMC) extends the capabilities of the classical IMC approach into the generalized domain of fractional calculus. When dealing with processes that exhibit time delays, implementation of such controllers in a classical feedback loop requires the approximation of the fractional order terms, as well as of the corresponding time delays. Objectives: The present study proposes an alternative design procedure of FO-IMC controllers based on a novel approximation method of the process time delay, proving the efficiency of the proposed method and its suitability for time delay systems. Methods: The generalized IMC control laws are obtained analytically, based on a novel approximation of time delay, the Non-Rational Transfer Function approach. Results: Several numerical examples are chosen to illustrate the efficiency of the proposed approach. In addition, a vertical take-off and landing unit exhibiting second order plus time delay dynamics is chosen to experimentally validate the proposed control strategy. The obtained results are used to compare the proposed tuning strategy with a popular FO-IMC tuning approach, based on the Taylor series approximation of the time delay. Conclusion: All the chosen examples, both numerical and experimental ones, validate the proposed method. The overall closed loop results obtained with the proposed approach demonstrate an improved performance compared to the existing method. Ultimately, the purpose of the paper to provide an alternative design strategy that extends the existing FO-IMC control field is reached

Approximation Methods for FO-IMC Controllers for Time Delay Systems

Fractional Order Internal Model Control (FO-IMC) is among the newest trends in extending fractional calculus to the integer order control. Approximation of the FO-IMC is one of the key problems. Apart from this, when dealing with time delay systems, the time delay needs also to be approximated. All these approximations can alter the closed loop performance of the controller. In this paper, FO-IMC controllers will be tested in terms of the approximation accuracy. The case study is a first order system with time delay. Several scenarios will be considered, aiming for a conclusion regarding the choice of the approximation method as a function of the process characteristics, closed loop performance and FO-IMC fractional order. To approximate the time delay, two extensively used techniques will be considered, such as the series and Pade approximations. These will be compared to a novel approximation technique. An analysis of the test cases presented show that the series approximation proves more suitable in a single scenario, whereas the novel approximation method produces better results for the rest of the test cases

Uncertainty Minimization and Feasibility Study for Managing the Complex and Interacting Anesthesia-Hemodynamic System

A novel control strategy is proposed to enable uncertainty minimization through knowledge infusion into the closed loop. The developed methodology aims the application of predictive control to regulate the complex anesthetic- hemodynamic (AH) interaction in a set of patients during general anesthesia. A special focus is given to solutions for minimizing the risk of instability arising from large uncertainty in the patient model dynamics. The paper explores the concept of digitalizing surgical actions as part of the natural mimicking strategy of actual anesthesiologists' real-life decision-making process. The simulations supporting the claims use an AH simulator. A feasibility study for solutions in an actual constrained input-output variable set is performed. Results confirm that the feasibility is enhanced when minimizing uncertainty conditions, having important clinical relevance in multi-drug optimization