Deep learning applied to data-driven dynamic characterization of hysteretic piezoelectric micromanipulators

The presence of nonlinearities such as hysteresis and creep increases the difficulty in the dynamic modeling and control of piezoelectric micromanipulators, in spite of the fact that the application of such devices requires high accuracy. Moreover, sensing in the microscale is expensive, making model feedback the only viable option. On the other hand, data-driven dynamic models are powerful tools within system identification that may be employed to construct models for a given plant. Recently, considerable effort has been devoted in extending the huge success of deep learning models to the identification of dynamic systems. In the present paper, we present the results of the successful application of deep learning based black-boxmodels for characterizing the dynamic behavior of micromanipulators. The excitation signal is a multisine spanning the frequency band of interest and the selected model is validated with semi static individual sinusoidal curves. Various architectures are tested to achieve a reasonable result and we try to summarize the best approach for the fine tuning required for such application. The results indicate the usefulness and predictive power for deep learning based models inthe field of system identification and in particular hysteresis modeling and compensation in micromanipulation applications

Nonlinear black-box system identification through coevolutionary algorithms and radial basis function artificial neural networks

The present work deals with the application of coevolutionary algorithms and artificial neural networks to perform input selection and related parameter estimation for nonlinear black-box models in system identification. In order to decouple the resolution of the input selection and parameter estimation, we propose a problem decomposition formulation and solve it by a coevolutionary algorithm strategy. The novel methodology is successfully applied to identify a magnetorheological damper, a continuous polymerization reactor and a piezoelectric robotic micromanipulator. The results show that the method provides valid models in terms of accuracy and statistical properties. The main advantage of the method is the joint input and parameter estimation, towards automating a tedious and error prone procedure with global optimization algorithms

Adaptation and Learning for Manipulators and Machining

This thesis presents methods for improving the accuracy and efficiency of tasks performed using different kinds of industrial manipulators, with a focus on the application of machining. Industrial robots offer a flexible and cost-efficient alternative to machine tools for machining, but cannot achieve as high accuracy out of the box. This is mainly caused by non-ideal properties in the robot joints such as backlash and compliance, in combination with the strong process forces that affect the robot during machining operations. In this thesis, three different approaches to improving the robotic machining accuracy are presented. First, a macro/micro-manipulator approach is considered, where an external compensation mechanism is used in combination with the robot, for compensation of high-frequency Cartesian errors. Two different milling scenarios are evaluated, where a significant increase in accuracy was obtained. The accuracy specification of 50 μm was reached for both scenarios. Because of the limited workspace and the higher bandwidth of the compensation mechanism compared to the robot, two different mid-ranging approaches for control of the relative position between the robot and the compensator are developed and evaluated. Second, modeling and identification of robot joints is considered. The proposed method relies on clamping the manipulator end effector and actuating the joints, while measuring joint motor torque and motor position. The joint stiffness and backlash can subsequently be extracted from the measurements, to be used for compensation of the deflections that occur during machining. Third, a model-based iterative learning control (ILC) approach is proposed, where feedback is provided from three different sensors of varying investment costs. Using position measurements from an optical tracking system, an error decrease of up to 84 % was obtained. Measurements of end-effector forces yielded an error decrease of 55 %, and a force-estimation method based on joint motor torques decreased the error by 38 %. Further investigation of ILC methods is considered for a different kind of manipulator, a marine vibrator, for the application of marine seismic acquisition. A frequency-domain ILC strategy is proposed, in order to attenuate undesired overtones and improve the tracking accuracy. The harmonics were suppressed after approximately 20 iterations of the ILC algorithm, and the absolute tracking error was r educed by a factor of approximately 50. The final problem considered in this thesis concerns increasing the efficiency of machining tasks, by minimizing cycle times. A force-control approach is proposed to maximize the feed rate, and a learning algorithm for path planning of the machining path is employed for the case of machining in non-isotropic materials, such as wood. The cycle time was decreased by 14 % with the use of force control, and on average an additional 28 % decrease was achieved by use of a learning algorithm. Furthermore, by means of reinforcement learning, the path-planning algorithm is refined to provide optimal solutions and to incorporate an increased number of machining directions

Precision Control of Piezo Electric Actuator

芝浦工業大学201

Dynamic modeling and bioinspired control of a walking piezoelectric motor

Szufnarowski F. Dynamic modeling and bioinspired control of a walking piezoelectric motor. Bielefeld: Universität Bielefeld; 2013.Piezoelectric motors have increasingly extended their field of applications during recent years. Improved material properties and manufacturing techniques have led to a variety of designs which can achieve theoretically unlimited displacements for moderate voltage levels while retaining a relatively high stiffness. In practical terms, this leads to stronger and faster motors which become a viable alternative to electromagnetic drives, especially if compact size and small weight are important. The piezoelectric motor considered in this work consists of four piezoelectric bender elements which can forward a ceramic bar by means of a frictional interaction. The drive elements can be compared to "legs" walking on a movable plane. The walking motor offers outstanding force generation capabilities for a motor of its size. Despite this fact, this motor has not been used in a force control scenario before and no motor models exist in the literature which can reproduce the effect of load on its performance. In this work, two dynamic motor models are developed to address the latter issue. Both of them faithfully reproduce the non-linear motor velocity decrease under load. The first model is based on an analytic approach and describes the low-level frictional interactions between the legs and the ceramic bar by means of several physically meaningful assumptions. This analytic model explains several non-linear phenomena in the operation of the walking motor within the full bandwidth of its rated operation. Non-linear influences due to the impact dynamics of the legs, ferroelectric hysteresis and friction are identified in the motor and new insights for an improved motor design as well as an improved motor-drive strategy gained. Moreover, the analytic model finds its application in a theoretical investigation of an alternative motor-drive strategy which is based on findings in insect walking. Specifically, it is shown that the performance of the motor can be improved by a half in terms of its force generation and doubled in terms of its maximal velocity, as compared to classical drive approaches, if the bioinspired drive strategy as proposed in this work is used. The second model is based on an experimental approach and system identification. Although less general, the second model is well-suited for a practical application in a force-control scenario. In particular, the experimental model is used in this work for the development of a load compensation strategy based on force feedback which restores the linearity of motor operation for moderate levels of loading. Based on the linearized motor model, a force controller is developed whose performance is evaluated both theoretically and experimentally. The developed force controller is also used in a bioinspired control scenario. Specifically, two walking motors together with their force controllers are employed in a 1-DOF antagonistic joint as force generators. The motors are supposed to partially mimic the functionality of a muscle based on the non-linear force-length relation as derived by Hill. A simple positioning task shows the feasibility of this kind of non-standard application of a piezoelectric motor. Beside the development of motor models and bioinspired control approaches, this work addresses the issue of drive-signal generation for the walking motor. Specifically, the development of motor-drive electronics is presented which supersedes the commercially available products due to its compactness and the possibility of waveform generation at much higher drive frequencies, above 50 kHz, as compared to the nominal limit of 3 kHz and commercial products. In this context, the possibility of motor operation at ultrasonic frequencies is discussed which would benefit the motor in terms of its speed and the absence of audible noises

Visual Servoing

The goal of this book is to introduce the visional application by excellent researchers in the world currently and offer the knowledge that can also be applied to another field widely. This book collects the main studies about machine vision currently in the world, and has a powerful persuasion in the applications employed in the machine vision. The contents, which demonstrate that the machine vision theory, are realized in different field. For the beginner, it is easy to understand the development in the vision servoing. For engineer, professor and researcher, they can study and learn the chapters, and then employ another application method

Design and Control of Flapping Wing Micro Air Vehicles

Flapping wing Micro Air Vehicles (MAVs) continues to be a growing field, with ongoing research into unsteady, low Re aerodynamics, micro-fabrication, and fluid-structure interaction. However, research into flapping wing control of such MAVs continues to lag. Existing research uniformly consists of proposed control laws that are validated by computer simulations of quasi-steady blade-element formulae. Such simulations use numerous assumptions and cannot be trusted to fully describe the flow physics. Instead, such control laws must be validated on hardware. Here, a novel control technique is proposed called Bi-harmonic Amplitude and Bias Modulation (BABM) which can generate forces and moments in 5 vehicle degrees of freedom with only two actuators. Several MAV prototypes were designed and manufactured with independently controllable wings capable of prescribing arbitrary wing trajectories. The forces and moments generated by a MAV utilizing the BABM control technique were measured on a 6-component balance. These experiments verified that a prototype can generate uncoupled forces and moments for motion in five degrees of freedom when using the BABM control technique, and that these forces can be approximated by quasi-steady blade-element formulae. Finally, the prototype performed preliminary controlled flight in constrained motion experiments, further demonstrating the feasibility of BABM

The Hand-Held Force Magnifier: Surgical Tools to Augment the Sense of Touch

Modern surgeons routinely perform procedures with noisy, sub-threshold, or obscured visual and haptic feedback,either due to the necessary approach, or because the systems on which they are operating are exceeding delicate. For example, in cataract extraction, ophthalmic surgeons must peel away thin membranes in order to access and replace the lens of the eye. Elsewhere, dissection is now commonly performed with energy-delivering tools – rather than sharp blades – and damage to deep structures is possible if tissue contact is not well controlled. Surgeons compensate for their lack of tactile sensibility by relying solely on visual feedback, observing tissue deformation and other visual cues through surgical microscopes or cameras. Using visual information alone can make a procedure more difficult, because cognitive mediation is required to convert visual feedback into motor action. We call this the “haptic problem” in surgery because the human sensorimotor loop is deprived of critical tactile afferent information, increasing the chance for intraoperative injury and requiring extensive training before clinicians reach independent proficiency. Tools that enhance the surgeon’s direct perception of tool-tissue forces can therefore potentially reduce the risk of iatrogenic complications and improve patient outcomes. Towards this end, we have developed and characterized a new robotic surgical tool, the Hand-Held Force Magnifier (HHFM), which amplifies forces at the tool tip so they may be readily perceived by the user, a paradigm we call “in-situ” force feedback. In this dissertation, we describe the development of successive generations of HHFM prototypes, and the evaluation of a proposed human-in-the-loop control framework using the methods of psychophysics. Using these techniques, we have verified that our tool can reduce sensory perception thresholds, augmenting the user’s abilities beyond what is normally possible. Further, we have created models of human motor control in surgically relevant tasks such as membrane puncture, which have shown to be sensitive to push-pull direction and handedness effects. Force augmentation has also demonstrated improvements to force control in isometric force generation tasks. Finally, in support of future psychophysics work, we have developed an inexpensive, high-bandwidth, single axis haptic renderer using a commercial audio speaker

Applied Mathematics to Mechanisms and Machines

This book brings together all 16 articles published in the Special Issue "Applied Mathematics to Mechanisms and Machines" of the MDPI Mathematics journal, in the section “Engineering Mathematics”. The subject matter covered by these works is varied, but they all have mechanisms as the object of study and mathematics as the basis of the methodology used. In fact, the synthesis, design and optimization of mechanisms, robotics, automotives, maintenance 4.0, machine vibrations, control, biomechanics and medical devices are among the topics covered in this book. This volume may be of interest to all who work in the field of mechanism and machine science and we hope that it will contribute to the development of both mechanical engineering and applied mathematics

A continuum robotic platform for endoscopic non-contact laser surgery: design, control, and preclinical evaluation

The application of laser technologies in surgical interventions has been accepted in the clinical domain due to their atraumatic properties. In addition to manual application of fibre-guided lasers with tissue contact, non-contact transoral laser microsurgery (TLM) of laryngeal tumours has been prevailed in ENT surgery. However, TLM requires many years of surgical training for tumour resection in order to preserve the function of adjacent organs and thus preserve the patient’s quality of life. The positioning of the microscopic laser applicator outside the patient can also impede a direct line-of-sight to the target area due to anatomical variability and limit the working space. Further clinical challenges include positioning the laser focus on the tissue surface, imaging, planning and performing laser ablation, and motion of the target area during surgery. This dissertation aims to address the limitations of TLM through robotic approaches and intraoperative assistance. Although a trend towards minimally invasive surgery is apparent, no highly integrated platform for endoscopic delivery of focused laser radiation is available to date. Likewise, there are no known devices that incorporate scene information from endoscopic imaging into ablation planning and execution. For focusing of the laser beam close to the target tissue, this work first presents miniaturised focusing optics that can be integrated into endoscopic systems. Experimental trials characterise the optical properties and the ablation performance. A robotic platform is realised for manipulation of the focusing optics. This is based on a variable-length continuum manipulator. The latter enables movements of the endoscopic end effector in five degrees of freedom with a mechatronic actuation unit. The kinematic modelling and control of the robot are integrated into a modular framework that is evaluated experimentally. The manipulation of focused laser radiation also requires precise adjustment of the focal position on the tissue. For this purpose, visual, haptic and visual-haptic assistance functions are presented. These support the operator during teleoperation to set an optimal working distance. Advantages of visual-haptic assistance are demonstrated in a user study. The system performance and usability of the overall robotic system are assessed in an additional user study. Analogous to a clinical scenario, the subjects follow predefined target patterns with a laser spot. The mean positioning accuracy of the spot is 0.5 mm. Finally, methods of image-guided robot control are introduced to automate laser ablation. Experiments confirm a positive effect of proposed automation concepts on non-contact laser surgery.Die Anwendung von Lasertechnologien in chirurgischen Interventionen hat sich aufgrund der atraumatischen Eigenschaften in der Klinik etabliert. Neben manueller Applikation von fasergeführten Lasern mit Gewebekontakt hat sich die kontaktfreie transorale Lasermikrochirurgie (TLM) von Tumoren des Larynx in der HNO-Chirurgie durchgesetzt. Die TLM erfordert zur Tumorresektion jedoch ein langjähriges chirurgisches Training, um die Funktion der angrenzenden Organe zu sichern und damit die Lebensqualität der Patienten zu erhalten. Die Positionierung des mikroskopis chen Laserapplikators außerhalb des Patienten kann zudem die direkte Sicht auf das Zielgebiet durch anatomische Variabilität erschweren und den Arbeitsraum einschränken. Weitere klinische Herausforderungen betreffen die Positionierung des Laserfokus auf der Gewebeoberfläche, die Bildgebung, die Planung und Ausführung der Laserablation sowie intraoperative Bewegungen des Zielgebietes. Die vorliegende Dissertation zielt darauf ab, die Limitierungen der TLM durch robotische Ansätze und intraoperative Assistenz zu adressieren. Obwohl ein Trend zur minimal invasiven Chirurgie besteht, sind bislang keine hochintegrierten Plattformen für die endoskopische Applikation fokussierter Laserstrahlung verfügbar. Ebenfalls sind keine Systeme bekannt, die Szeneninformationen aus der endoskopischen Bildgebung in die Ablationsplanung und -ausführung einbeziehen. Für eine situsnahe Fokussierung des Laserstrahls wird in dieser Arbeit zunächst eine miniaturisierte Fokussieroptik zur Integration in endoskopische Systeme vorgestellt. Experimentelle Versuche charakterisieren die optischen Eigenschaften und das Ablationsverhalten. Zur Manipulation der Fokussieroptik wird eine robotische Plattform realisiert. Diese basiert auf einem längenveränderlichen Kontinuumsmanipulator. Letzterer ermöglicht in Kombination mit einer mechatronischen Aktuierungseinheit Bewegungen des Endoskopkopfes in fünf Freiheitsgraden. Die kinematische Modellierung und Regelung des Systems werden in ein modulares Framework eingebunden und evaluiert. Die Manipulation fokussierter Laserstrahlung erfordert zudem eine präzise Anpassung der Fokuslage auf das Gewebe. Dafür werden visuelle, haptische und visuell haptische Assistenzfunktionen eingeführt. Diese unterstützen den Anwender bei Teleoperation zur Einstellung eines optimalen Arbeitsabstandes. In einer Anwenderstudie werden Vorteile der visuell-haptischen Assistenz nachgewiesen. Die Systemperformanz und Gebrauchstauglichkeit des robotischen Gesamtsystems werden in einer weiteren Anwenderstudie untersucht. Analog zu einem klinischen Einsatz verfolgen die Probanden mit einem Laserspot vorgegebene Sollpfade. Die mittlere Positioniergenauigkeit des Spots beträgt dabei 0,5 mm. Zur Automatisierung der Ablation werden abschließend Methoden der bildgestützten Regelung vorgestellt. Experimente bestätigen einen positiven Effekt der Automationskonzepte für die kontaktfreie Laserchirurgie