Performance-driven control of nano-motion systems

The performance of high-precision mechatronic systems is subject to ever increasing demands regarding speed and accuracy. To meet these demands, new actuator drivers, sensor signal processing and control algorithms have to be derived. The state-of-the-art scientific developments in these research directions can significantly improve the performance of high-precision systems. However, translation of the scientific developments to usable technology is often non-trivial. To improve the performance of high-precision systems and to bridge the gap between science and technology, a performance-driven control approach has been developed. First, the main performance limiting factor (PLF) is identified. Then, a model-based compensation method is developed for the identified PLF. Experimental validation shows the performance improvement and reveals the next PLF to which the same procedure is applied. The compensation method can relate to the actuator driver, the sensor system or the control algorithm. In this thesis, the focus is on nano-motion systems that are driven by piezo actuators and/or use encoder sensors. Nano-motion systems are defined as the class of systems that require velocities ranging from nanometers per second to millimeters per second with a (sub)nanometer resolution. The main PLFs of such systems are the actuator driver, hysteresis, stick-slip effects, repetitive disturbances, coupling between degrees-of-freedom (DOFs), geometric nonlinearities and quantization errors. The developed approach is applied to three illustrative experimental cases that exhibit the above mentioned PLFs. The cases include a nano-motion stage driven by a walking piezo actuator, a metrological AFM and an encoder system. The contributions of this thesis relate to modeling, actuation driver development, control synthesis and encoder sensor signal processing. In particular, dynamic models are derived of the bimorph piezo legs of the walking piezo actuator and of the nano-motion stage with the walking piezo actuator containing the switching actuation principle, stick-slip effects and contact dynamics. Subsequently, a model-based optimization is performed to obtain optimal drive waveforms for a constant stage velocity. Both the walking piezo actuator and the AFM case exhibit repetitive disturbances with a non-constant period-time, for which dedicated repetitive control methods are developed. Furthermore, control algorithms have been developed to cope with the present coupling between and hysteresis in the different axes of the AFM. Finally, sensor signal processing algorithms have been developed to cope with the quantization effects and encoder imperfections in optical incremental encoders. The application of the performance-driven control approach to the different cases shows that the different identified PLFs can be successfully modeled and compensated for. The experiments show that the performance-driven control approach can largely improve the performance of nano-motion systems with piezo actuators and/or encoder sensors

Force control of piezoelectric walker

This paper is concerned with the force control of a walking piezoelectric motor, a commercially available Piezo LEGS motor. The motor is capable of providing high precision positioning control on nanometer scale, but also relatively high forces up to 6 N. The proposed force control algorithm is very simple, but effective, and it is based on a recently presented coordinate transformation. The transformation allows definition of the driving waveforms for the motor according to a desired motion of the motor legs in the plane of motion. Such a possibility opens a path for creating the y-direction interaction force between the motor legs and the rod which is enough to ensure no relative motion between the legs and the rod. Once that is achieved, one can control the x-direction force imposed by the motor rod on its environment. The presented force control scheme has been successfully validated through a series of experiments

Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Design of a terrain detection system for foot drop

The ankle foot orthotic (AFO) has been around for centuries. They were created to augment functionality of an ankle damaged due to injury or disease. A common reason a patient might be prescribed an AFO is a condition called foot drop. Foot drop can be caused by many conditions, but the most common reason is a stroke. Foot drop can be characterized by the inability to raise and/or lower a patient\u27s foot. This incapacitation of the patient\u27s foot leads to unnatural gaits and joint fatigue, as well as increasing the patient\u27s likelihood of tripping and becoming seriously injured. Hard plastic AFOs that hold a patient\u27s foot in a neutral position are the current standard for combating foot drop. These AFOs come in many different shapes and sizes, which emphasizes the wide variety in functionality of someone with foot drop. Unfortunately, the restrictive nature of the AFO can cause unnatural movements in the patient\u27s foot; these unnatural tendencies are more exaggerated when walking down stairs and ramps, as the natural gait is to land toe first, the opposite of what the brace allows the patient to do. The purpose of this project is to create a sensor system for an AFO to help identify varying terrain. In the future this information can then be made to control an active AFO. Each terrain type will be first measured by a pair of simple infrared range finder, attached on the lower leg, one range finder looks ahead of the user and the other looks straight down at the ground. Models for the ground conditions can be established by representing each with Fourier series created using RANdom Sample Consensus (RANSAC). RANSAC coefficients will be scaled off the rate of data coming in and gait speed. Each model has a period term so the data can easily be scaled to match the pattern of walking regardless of pace. Gait speed will be measured using the downward facing ankle-mounted rangefinder, but with a threshold to determine when the foot is in contact with the ground. Once this initial set-up is completed, the system can take in data live and provide a prediction of the type of ground the patient is walking over, using pattern recognition techniques. The hope for this project is that if the system can accurately predict the change in ground type from, for example, level walking to walking down a ramp, an AFO could then be made to adjust itself, giving the patient a more natural gait, even when encountering adverse conditions. A byproduct of constantly using a patient\u27s own gait to measure ground type is the ability to track a patient\u27s changing gait over time, giving therapists a valuable new tool for tracking progress in a patient

Design and implementation of high-bandwidth, high-resolution imaging in atomic force microscopy

Video-rate imaging with subnanometer resolution without compromising on the scan range has been a long-awaited goal in Atomic Force Microscopy (AFM). The past decade saw significant advances in hardware used in atomic force microscopes, which further enable the feasibility of high-speed Atomic Force Microscopy. Control design in AFMs plays a vital role in realizing the achievable limits of the device hardware. Almost all AFMs in use today use Proportional-Integral-Derivative(PID) control designs, which can be majorly improved upon for performance and robustness. We address the problem of AFM control design through a systems approach to design model-based control laws that can give major improvements in the performance and robustness of AFM imaging. First, we propose a cascaded control design approach to tapping mode imaging, which is the most common mode of AFM imaging. The proposed approach utilizes the vertical positioning sensor in addition to the cantilever deflection sensor in the feedback loop. The control design problem is broken down into that of an inner control loop and an outer control loop. We show that by appropriate control design, unwanted effects arising out of model uncertainties and nonlinearities of the vertical positioning system are eliminated. Experimental implementation of the proposed control design shows improved imaging quality at up to 30% higher speeds. Secondly, we address a fundamental limitation in tapping mode imaging by proposing a novel transform-based imaging mode to achieve an order of magnitude improvement in AFM imaging bandwidth. We introduce a real-time transform that effects a frequency shift of a given signal. We combine model-based reference generation along with the real-time transform. The proposed method is shown to have linear dynamical characteristics, making it conducive for model-based control designs, thus paving the way for achieving superior performance and robustness in imaging

Desktop microfactory

Micro technology is continuously progressing towards smaller, smarter and reliable forms. Consequently, demand for such miniature and complex systems is arising rapidly in various fields such as industry, medicine, aerospace and automotive. Such fast development of micro technology is achieved thanks to improvements in micromanufacturing tools and techniques. Miniaturization of the machinery and manufacturing equipment is emerging to be an attractive idea that would eventually solve many of the issues existing in conventional micro-manufacturing. This work presents a modular and reconfigurable desktop microfactory for high precision assembly and machining of micro mechanical parts as proof of concept inspired by the downsizing trend of the production tools. The system is constructed based on primary functional and performance requirements such as miniature size, operation with sub-millimeter precision, modular and reconfigurable structure, parallel processing capability, ease of transportation and integration. Proposed miniature factory consists of downsized functional modules such as two parallel kinematic robots for manipulation and assembly, galvanometric laser beam scanning system for micromachining, high precision piezoelectric positioning stage, camera system for detection and inspection, and a rotational conveyor system. Each of the listed modules is designed and tested for fine precision tasks separately and results are presented. Design comprises development of mechanics, electronics and controller for the modules individually. Once stand-alone operation of each unit is achieved further assembly to a single microfactory system is considered. The overall mechanical structure of the proposed microfactory facilitates parallel processing, flexible rearrangement of the layout, and ease of assembling and disassembling capabilities. These important steps are taken to investigate possibilities of a microfactory concept for production of microsystems in near future

Design, Development, and Evaluation of a Teleoperated Master-Slave Surgical System for Breast Biopsy under Continuous MRI Guidance

The goal of this project is to design and develop a teleoperated master-slave surgical system that can potentially assist the physician in performing breast biopsy with a magnetic resonance imaging (MRI) compatible robotic system. MRI provides superior soft-tissue contrast compared to other imaging modalities such as computed tomography or ultrasound and is used for both diagnostic and therapeutic procedures. The strong magnetic field and the limited space inside the MRI bore, however, restrict direct means of breast biopsy while performing real-time imaging. Therefore, current breast biopsy procedures employ a blind targeting approach based on magnetic resonance (MR) images obtained a priori. Due to possible patient involuntary motion or inaccurate insertion through the registration grid, such approach could lead to tool tip positioning errors thereby affecting diagnostic accuracy and leading to a long and painful process, if repeated procedures are required. Hence, it is desired to develop the aforementioned teleoperation system to take advantages of real-time MR imaging and avoid multiple biopsy needle insertions, improving the procedure accuracy as well as reducing the sampling errors. The design, implementation, and evaluation of the teleoperation system is presented in this dissertation. A MRI-compatible slave robot is implemented, which consists of a 1 degree of freedom (DOF) needle driver, a 3-DOF parallel mechanism, and a 2-DOF X-Y stage. This slave robot is actuated with pneumatic cylinders through long transmission lines except the 1-DOF needle driver is actuated with a piezo motor. Pneumatic actuation through long transmission lines is then investigated using proportional pressure valves and controllers based on sliding mode control are presented. A dedicated master robot is also developed, and the kinematic map between the master and the slave robot is established. The two robots are integrated into a teleoperation system and a graphical user interface is developed to provide visual feedback to the physician. MRI experiment shows that the slave robot is MRI-compatible, and the ex vivo test shows over 85%success rate in targeting with the MRI-compatible robotic system. The success in performing in vivo animal experiments further confirm the potential of further developing the proposed robotic system for clinical applications

Study and Development of Mechatronic Devices and Machine Learning Schemes for Industrial Applications

Obiettivo del presente progetto di dottorato è lo studio e sviluppo di sistemi meccatronici e di modelli machine learning per macchine operatrici e celle robotizzate al fine di incrementarne le prestazioni operative e gestionali. Le pressanti esigenze del mercato hanno imposto lavorazioni con livelli di accuratezza sempre più elevati, tempi di risposta e di produzione ridotti e a costi contenuti. In questo contesto nasce il progetto di dottorato, focalizzato su applicazioni di lavorazioni meccaniche (e.g. fresatura), che includono sistemi complessi quali, ad esempio, macchine a 5 assi e, tipicamente, robot industriali, il cui utilizzo varia a seconda dell’impiego. Oltre alle specifiche problematiche delle lavorazioni, si deve anche considerare l’interazione macchina-robot per permettere un’efficiente capacità e gestione dell’intero impianto. La complessità di questo scenario può evidenziare sia specifiche problematiche inerenti alle lavorazioni (e.g. vibrazioni) sia inefficienze più generali che riguardano l’impianto produttivo (e.g. asservimento delle macchine con robot, consumo energetico). Vista la vastità della tematica, il progetto si è suddiviso in due parti, lo studio e sviluppo di due specifici dispositivi meccatronici, basati sull’impiego di attuatori piezoelettrici, che puntano principalmente alla compensazione di vibrazioni indotte dal processo di lavorazione, e l’integrazione di robot per l’asservimento di macchine utensili in celle robotizzate, impiegando modelli di machine learning per definire le traiettorie ed i punti di raggiungibilità del robot, al fine di migliorarne l’accuratezza del posizionamento del pezzo in diverse condizioni. In conclusione, la presente tesi vuole proporre soluzioni meccatroniche e di machine learning per incrementare le prestazioni di macchine e sistemi robotizzati convenzionali. I sistemi studiati possono essere integrati in celle robotizzate, focalizzandosi sia su problematiche specifiche delle lavorazioni in macchine operatrici sia su problematiche a livello di impianto robot-macchina. Le ricerche hanno riguardato un’approfondita valutazione dello stato dell’arte, la definizione dei modelli teorici, la progettazione funzionale e l’identificazione delle criticità del design dei prototipi, la realizzazione delle simulazioni e delle prove sperimentali e l’analisi dei risultati.The aim of this Ph.D. project is the study and development of mechatronic systems and machine learning models for machine tools and robotic applications to improve their performances. The industrial demands have imposed an ever-increasing accuracy and efficiency requirement whilst constraining the cost. In this context, this project focuses on machining processes (e.g. milling) that include complex systems such as 5-axes machine tool and industrial robots, employed for various applications. Beside the issues related to the machining process itself, the interaction between the machining centre and the robot must be considered for the complete industrial plant’s improvement. This scenario´s complexity depicts both specific machining problematics (e.g. vibrations) and more general issues related to the complete plant, such as machine tending with an industrial robot and energy consumption. Regarding the immensity of this area, this project is divided in two parts, the study and development of two mechatronic devices, based on piezoelectric stack actuators, for the active vibration control during the machining process, and the robot machine tending within the robotic cell, employing machine learning schemes for the trajectory definition and robot reachability to improve the corresponding positioning accuracy. In conclusion, this thesis aims to provide a set of solutions, based on mechatronic devices and machine learning schemes, to improve the conventional machining centre and the robotic systems performances. The studied systems can be integrated within a robotic cell, focusing on issues related to the specific machining process and to the interaction between robot-machining centre. This research required a thorough study of the state-of-the-art, the formulation of theoretical models, the functional design development, the identification of the critical aspects in the prototype designs, the simulation and experimental campaigns, and the analysis of the obtained results