High-bandwidth nanopositioning via active control of system resonance

Acknowledgements This work was supported in part by the National Natural Science Foundation of China (Grant Nos. U2013211 and 51975375), the Open Foundation of the State Key Laboratory of Fluid Power and Mechatronic Systems, China (Grant No. GZKF-202003), and the Binks Trust Visiting Research Fellowship (2018), University of Aberdeen, UK, awarded to Dr. Sumeet S. Aphale.Peer reviewedPublisher PD

Robust fractional-order fast terminal sliding mode control with fixed-time reaching law for high-performance nanopositioning

Open Access via the Wiley Agreement ACKNOWLEDGEMENTS This work is supported by the China Scholarship Council under Grant No. 201908410107 and by the National Natural Science Foundation of China under Grant No. 51505133. The authors also thank the anonymous reviewers for their insightful and constructive comments.Peer reviewedPublisher PD

Dynamics and Controls of Fluidic Pressure-Fed Mechanism (FPFM) of Nanopositioning System

Flexure or compliant mechanisms are employed in many precisions engineered devices due to their compactness, linearity, resolution, etc. Yet, critical issues remain in motion errors, thermal instability, limited bandwidth, and vibration of dynamic systems. Those issues cannot be negligible to maintain high precision and accuracy for precision engineering applications. In this thesis, a novel fluidic pressure-fed mechanism (FPFM) is proposed and investigated. The proposed method is designing internal fluidic channels inside the spring structure of the flexure mechanism using the additive manufacturing (AM) process to overcome addressed challenges. By applying pneumatic/hydraulic pressure and filling media into fluidic channels, dynamic characteristics of each spring structure of the flexure mechanism can be altered or adjusted to correct motion errors, increase operating speed, and suppress vibration. Additionally, FPFM can enhance thermal stability by flowing fluids without affecting the motion quality of the dynamic system. Lastly, the motion of the nanopositioning system driven by FPFM can provide sub-nanometer resolution motion, and this enables the nanopositioning system to have two linear motion in a monolithic structure. The main objective of this thesis is to propose and validate the feasibility of FPFM that can ultimately be used for a monolithic FPFM dual-mode stage for providing high positioning performance without motion errors while reducing vibration and increasing thermal stability and bandwidth

Design and experimental validation of a piezoelectric actuator tracking control based on fuzzy logic and neural compensation

This work proposes two control feedback-feedforward algorithms, based on fuzzy logic in combination with neural networks, aimed at reducing the tracking error and improving the actuation signal of piezoelectric actuators. These are frequently used devices in a wide range of applications due to their high precision in micro- and nanopositioning combined with their mechanical stiffness. Nevertheless, the hysteresis is one the main phenomenon that degrades the performance of these actuators in tracking operations. The proposed control schemes were tested experimentally in a commercial piezoelectric actuator. They were implemented with a dSPACE 1104 device, which was used for signal generation and acquisition purposes. The performance of the proposed control schemes was compared to conventional structures based on proportional-integral-derivative and fuzzy logic in feedback configuration. Experimental results show the advantages of the proposed controllers, since they are capable of reducing the error to significant magnitude orders.The authors wish to express their gratitude to the Basque Government, through the project EKOHEGAZ (ELKARTEK KK-2021/00092), to the Diputación Foral de Álava (DFA), through the project CONAVANTER, and to the UPV/EHU, through the project GIU20/063, for supporting this work

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

Finite-time sliding mode control strategies and their applications

In many engineering applications, faster convergence is always sought, such as manufacturing plants, defence sectors, mechatronic systems. Nowadays, most of the physical systems are operated in a closed-loop environment in conjunction with a controller. Therefore, the controller plays a critical role in determining the speed of the convergence of the entire closed-loop system. Linear controllers are quite popular for their simple design. However, linear controllers provide asymptotic convergence speed, i.e., the actual convergence is obtained when the time reaches an infinitely large amount. Furthermore, linear controllers are not entirely robust in the presence of non-vanishing types of disturbances. It is always important to design robust controllers because of the presence of model imperfections and unknown disturbances in almost all kinds of systems. Therefore, it is necessary to design controllers that are not only robust, but will also provide faster convergence speed. Out of many robust non-linear control strategies, a further development in sliding mode control (SMC) strategy is considered in this thesis because of its simplicity and robustness. There have been many contributions in the SMC field in the last decade. Many existingmethods are available for the SMC design for second-order systems. However, the SMC design becomes extremely complex if the system order increases. Therefore, the first part of this thesis focuses on developing arbitrary-order SMC strategies with a relatively simpler design while providing finite-time convergence. Novel methods are developed with both continuous and discontinuous control structures. The second part of this thesis focuses on developing algorithms to provide even faster convergence speed than that of finite-time convergent algorithms. Some practical applications need strict constraints on time response due to security reasons or to ameliorate the productiveness. For example, a missile or any aerial launch vehicle can be hugely affected by a strong wind gust deviating it from the desired trajectory, thus yielding a significant degree of initial tracking error. It is worth mentioning that the state convergence achieved in SMC during sliding can be either asymptotic or in finite-time, depending on the selection of the surface. Furthermore, it primarily depends on the initial conditions of the states. This provides a motivation to focus on developing SMC controllers where the convergence time does not depend on initial conditions, and a well-defined theoretical analysis is provided in the thesis regarding arbitrary-order fixed-time convergent SMC design. Subsequently, a predefined-time convergent second-order differentiator and observer are proposed. The main advantage of the proposed differentiator is to calculate the derivative of a given signal in fixed-time while the least upper bound of the fixed stabilisation time is equal to a tunable parameter. Similarly, the proposed predefined-time observer is robust with respect to bounded uncertainties and can also be used to estimate the uncertainties. The final part of the thesis is focused on the applications of the proposed algorithms. First of all, a novel third-order SMC is designed for a piezoelectric-driven motion systems achieving better accuracy and control performance. Later on, an experimental validation of the proposed controller is conducted on an induction motor setup. Later, a fixed-time convergent algorithm is proposed for an automatic generation control (AGC) of a multi-area interconnected power system while considering the non-linearities in the dynamic system. The final part is focused on developing fixed-time convergent algorithms in a co-operative environment. The reason for selecting such a system is the presence of the highest degree of uncertainties. To this end, a novel distributed algorithm is developed for achieving second-order consensus in the multiagent systems by designing a full-order fixed-time convergent sliding surface

Interferometric-spatial-phase imaging for sub-nanometer three-dimensional positioning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 203-206).Current alignment technology is incapable of satisfying the needs of imminent generations of lithography. This dissertation delineates a novel method of alignment and three-dimensional position metrology that is compatible with many forms of proximity lithography. The method is called Interferometric-Spatial-Phase Imaging (ISPI), and is based on encoding three-dimensional position information in the spatial phase and frequency of interference fringes, viewed with specialized oblique-incidence, dark-field optical microscopes. Alignment detectivity is 500 gm. Unlike amplitude-based interferometers, this spatial-phase-encoding interferometer achieves high alignment detectivity without sensitivity to variations in wavelength, gap and other factors, such as resist layers and changes in the index of refraction in the beampath. Several novel gap detection methods are introduced, with gap detectivity 500 jgm.(cont.) Gap is confirmed with exposure of patterns in resist, taking advantage of near-field interference in a novel Chirped Talbot Effect. Alignment and pattern overlay are confirmed in experiments combining x-ray exposures with continuous ISPI position feedback. Dynamic overlay of patterns in resist is demonstrated to be 2.7 nm, with a clear path for further improvement. Gate structures in a double-gate MOSFET are dynamically aligned to 2.5 nm.by Euclid Eberle Moon.Ph.D

Discrete Modeling and Sliding Mode Control of Piezoelectric Actuators

With the ability to generate fine displacements with a resolution down to sub-nanometers, piezoelectric actuators (PEAs) have found wide applications in various nano-positioning systems. However, existence of various effects in PEAs, such as hysteresis and creep, as well as dynamics can seriously degrade the PEA performance or even lead to instability. This raises a great need to model and control PEAs for improved performance, which have drawn remarkable attention in the literature. Sliding mode control (SMC) shows its potential to the control of PEA, by which the hysteresis and other nonlinear effects can be regard as disturbance to the dynamic model and thus rejected or compensated by its switching control. To implement SMC in digital computers, this research is aimed at developing novel discrete models and discrete SMC (DSMC)-based control schemes for PEAs, along with their experimental validation. The first part of this thesis concerns with the modeling and control of one-degree of freedom (DOF) PEA, which can be treated as a single-input-single-output (SISO) system. Specifically, a novel discrete model based on the concept of auto-regressive moving average (ARMA) was developed for the PEA hysteresis; and to compensate for the PEA hysteresis and improve its dynamics, an output tracking integrated discrete proportional-integral-derivative-based SMC (PID-SMC) was developed. On this basis, by making use of the availability of PEA hysteresis models, two control schemes, named “the discrete inversion feedforward based PID-SMC” and “the discrete disturbance observer (DOB)-based PID-SMC”, were further developed. To illustrate the effectiveness of the developed models and control schemes, experiments were designed and conducted on a commercially available one-DOF PEA, as compared with the existing ones. The second part of the thesis presents the extension of the developed modeling and control methods to multi-DOF PEAs. Given the fact that details with regard to the PEA internal configurations is not typically provided by the manufacturer, a state space model based on the black box system identification was developed for the three-DOF PEA. The developed model was then integrated in the output tracking based discrete PID-SMC, with its effectiveness verified through the experiments on a commercially available three-DOF PEA. The superiority of the proposed control method over the conventional PID controller was also experimentally investigated and demonstrated. Finally, by integrating with a DOB in the discrete PID-based SMC, a novel control scheme is resulted to compensate for the nonlinearities of the three-DOF PEA. To verify its effectiveness, the discrete DOB based PID-SMC was applied in the control experiments and compared with the existing SMC. The significance of this research lies in the development of the discrete models and PID-based SMC for PEAs, which is of great help to improve their performance. The successful application of the proposed method in the control of multi-DOF PEA allows the application of SMC to the control of complicated multi-inputs-multi-outputs (MIMO) systems without details regarding the internal configuration. Also, integration of the inversion based feedforward control and the DOB in the SMC design has been proven effective for the tracking control of PEAs