Life at Low Reynolds Number

Advances in medical robots promise to improve modern medicine and the quality of life. Miniaturization of these robotic platforms has led to numerous applications that leverages precision medicine. In this review, the current trends of medical micro and nanorobotics for therapy, surgery, diagnosis, and medical imaging are discussed. The use of micro and nanorobots in precision medicine still faces technical, regulatory, and market challenges for their widespread use in clinical settings. Nevertheless, recent translations from proof of concept to in vivo studies demonstrate their potential toward precision medicine.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/advs.202002203

Medical Micro/Nanorobots in Precision Medicine.

Load frequency control (LFC) is one of the essential process in interconnected power systems. To provide high quality, reliable and stable electrical power, designed controller should perform satisfactorily, i.e. suppress area frequency and tie-line power deviations. Within this scope, in this study, a high order differential feedback controller (HODFC) and a developed fractional high order differential feedback controller (FHODFC) are proposed for LFC problem in multi-area power systems for the first time. The gains of the HODFC and FHODFC are optimally tuned by particle swarm optimization (PSO) algorithm aiming to minimize integral of time weighted absolute error (ITAE) performance index. The superiority of the developed FHODFC are verified by comparing reported controller structures in the recent state-of-the-art literature and HODFC for two identical non-reheat thermal power system and two-area multi-source power system consisting of gas, thermal and hydro generation units with/without consideration of HVDC link. To test the robustness of the designed controllers, varying system parameters and loading conditions are investigated. The governor dead band (GDB) and generation rate constraint (GRC) limitations are also considered for the system under study to examine non-linearity handling success of the proposed controllers. Performance results indicate that the developed FHODFC provides better dynamic response and robustness than other published techniques under nonlinearities, random load pattern, and variations in system parameters and loading conditions.

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Design of an Optimized Fractional High Order Differential Feedback Controller for Load Frequency Control of a Multi-Area Multi-Source Power System With Nonlinearity

Life at low Reynolds' number revisited

Classical fractional order controller tuning techniques usually establish the parameters of the controller by solving a system of nonlinear equations resulted from the frequency domain specifications like phase margin, gain crossover frequency, iso-damping property, robustness to uncertainty, etc. In the present paper a novel fractional order generalized optimum method for controller design using frequency domain is presented. The tuning rules are inspired from the symmetrical optimum principles of Kessler. In the first part of the paper are presented the generalized tuning rules of this method. Introducing the fractional order, one more degree of freedom is obtained in design, offering solution for practically any desired closed-loop performance measures. The proposed method has the advantage that takes into account both robustness aspects and desired closed-loop characteristics, using simple tuning-friendly equations. It can be applied to a wide range of process models, from integer order models to fractional order models. Simulation results are given to highlight these advantages.

https://www.mdpi.com/2227-7390/7/12/1166/pdf

Simplified Fractional Order Controller Design Algorithm

The beauty of the proportional-integral-derivative (PID) algorithm for feedback control is its simplicity and efficiency. Those are the main reasons why PID controller is the most common form of feedback. PID combines the three natural ways of taking into account the error: the actual (proportional), the accumulated (integral), and the predicted (derivative) values; the three gains depend on the magnitude of the error, the time required to eliminate the accumulated error, and the prediction horizon of the error. This paper explores the new meaning of integral and derivative actions, and gains, derived by the consideration of non-integer integration and differentiation orders, i.e., for fractional order PID controllers. The integral term responds with selective memory to the error because of its non-integer order λ , and corresponds to the area of the projection of the error curve onto a plane (it is not the classical area under the error curve). Moreover, for a fractional proportional-integral (PI) controller scheme with automatic reset, both the velocity and the shape of reset can be modified with λ . For its part, the derivative action refers to the predicted future values of the error, but based on different prediction horizons (actually, linear and non-linear extrapolations) depending on the value of the differentiation order, μ . Likewise, in case of a proportional-derivative (PD) structure with a noise filter, the value of μ allows different filtering effects on the error signal to be attained. Similarities and differences between classical and fractional PIDs, as well as illustrative control examples, are given for a best understanding of new possibilities of control with the latter. Examples are given for illustration purposes.

https://www.mdpi.com/2227-7390/7/6/530/pdf

Back to Basics: Meaning of the Parameters of Fractional Order PID Controllers

Abstract The only purpose of this paper is to show how fractional calculus can contribute to the development of the very interesting and promising field of micro and nano machines, from the deeper understanding of the world in which they work, to their design and control. The essentials of Brownian motors and untethered swimming microrobots are briefly presented, and two naive examples on how fractional calculus can contribute to open new perspectives are given.

There’s plenty of fractional at the bottom, I: Brownian motors and swimming microrobots

This paper presents an improved locomotion for an N-link swimming artificial eukaryotic flagellum (AEF) microrobot using a fractional order approach for both the navigation waveform and control. The proposed locomotion is tested on a simulator of the robot, developed in the MATLAB/Simulink environment, which allows to select different modes of swimming and control strategies, as well as evaluate the performance of the locomotion in terms of propulsion, power efficiency or tracking. Different robust fractional order proportional-derivative (PD$^{\mu }$) controllers are designed in order to reduce the effects of the load variation of the actuator of each link depending on its position along the flagellum. For comparison purposes, three-parameter integer order controllers are also designed. Simulation results are given in order to show the benefits of the proposed locomotion in comparison with classical waveforms and previous results.

Improved Locomotion of an AEF Swimming Robot Using Fractional Order Control

Artificial bacterial flagella (ABF) is one of the more interesting alternatives for the design of swimming nano and microrobots moving in life environments. In this paper the propulsion of an ABF swimming robot is studied by considering four different travelling waves: harmonic (from Eukaryotic cells), linear and quadratic amplitude modulation (from Carangiform swimmers), and a novel fractional order amplitude growing. The last one, proposed in this paper, allows to preserve, in a different way, two important propulsion properties: 1) the flagellum head is always maintained at zero amplitude (boundary condition), and 2) the wave amplitude along the flagellum can be modulated. A comparison of the propulsion performance obtained with each wave, in terms of the mechanical power developed by the robot and the electrical power supplied to actuators, is given in order to demonstrate that the fractional travelling wave seems to be the most effective for propulsion. For simulation purposes, the robot is modeled by using Simscape, a physical modeling tool included in the Matlab/Simulink package.

A comparative study of planar waveforms for propulsion of a joined artificial bacterial flagella swimming robot

This paper presents a study of motion of an artificial flagellum microrobot in a viscous environment in COMSOL Multiphysics. The microrobot is essentially a body, consisting of a piezoelectric layered beam divided into several segments. Its actuation for propulsion relies on the creation of a non-reciprocal motion along the body. This requires that a voltage with the same frequency but different phases and amplitudes be applied to each segment. The motion pattern is analyzed theoretically and a control strategy in open loop is implemented to emulate a non-reciprocal motion. Simulations are given to demonstrate that a non-reciprocal motion is developed. Likewise, its propulsion can be verified from the drag force observed. Despite extreme size limitations using piezoelectric materials, the design proposed in this work may be able to swim in blood flow.

José Emilio Traver

Papers

Back to Basics: Meaning of the Parameters of Fractional Order PID Controllers

There’s plenty of fractional at the bottom, I: Brownian motors and swimming microrobots

Improved Locomotion of an AEF Swimming Robot Using Fractional Order Control

A comparative study of planar waveforms for propulsion of a joined artificial bacterial flagella swimming robot

Artificial Flagellum Microrobot. Design and Simulation in COMSOL