Sliding mode control based piezoelectric actuator control

In this paper a method for piezoelectric stack actuator control is proposed. In addition a brief discussion about the usage of the same methods for estimation of external force acting to the actuator in contact with environment is made. The method uses sliding mode framework to design both the observer and the controller based on an electromechanical lumped model of the piezoelectric actuator. Furthermore, using a nonlinear differential equation the internal hysteresis disturbance is removed from the total disturbance in an attempt to estimate the external force acting on the actuator. It is then possible to use this external force estimate as a means of force control of the actuator. Simulation and experiments are compared for validating the disturbance and external force estimation technique. Some experiments that incorporate disturbance compensation in a closed-loop SMC control algorithm are also presented to prove the effectiveness of this method in producing high precision motion

Evaluation of error bound for a DT sliding mode control with disturbance observer

In this paper an estimate of the upper bound of control error for discrete-time implementation of a Sliding Mode Control (DTSMC) combined with disturbance observer is investigated. Having in mind application to PZT high bandwidth actuators and since high accuracy is required the special attention is paid to avoid chattering. Selected structure of proposed SMC controller is proven to offer chattering-free motion. The proposed structure also avoids deadbeat poles that are the cause of large control action which is not desirable in practical applications. The proposed scheme is shown to allow a maximum error bound of O(T) for the system with disturbance. The main disturbances are represented by hysteresis and the time variation of the piezo stack parameters. The evaluation of the upper bound of error in such a system is shown and experimentally verified. Closed-loop experiments are presented using the proposed method to verify the theoretical results

Fuzzy-enhanced Dual-loop Control Strategy for Precise Nanopositioning

Postprin

Global fast non-singular terminal sliding-mode control for high-speed nanopositioning

Peer reviewedPostprin

Enhanced Positioning Bandwidth in Nanopositioners via Strategic Pole Placement of the Tracking Controller

Funding: This research received no external funding.Peer reviewedPublisher PD

Modeling and robust control strategy for a control-optimized piezoelectric microgripper.

International audienceIn this paper, modeling and robust control strategy for a new control-optimized piezoelectric microgripper are presented. The device to be controlled is a piezoelectric flexible mechanism dedicated to micromanipulation. It has been previously designed with an emphasis to control strategy, using a new topological optimization method, by considering innovative frequency-based criteria. A complete non-linear model relating the voltage and the resulting deflection is established taking into account hysteresis as a plurilinear model subjected to uncertainties. The approach used for controlling the actuator tip is based on a mixed High Authority Control (HAC) / Low Authority Control (LAC) strategy for designing a wide-band regulator. It consists of a Positive Position Feedback (PPF) damping controller approach combined with a low-frequency integral controller which is shown to have robustness performances as good as a RST-based robust pole placement approach for the microgripper. The rejection of the vibrations, naturally induced by the flexible structure, and the control of the tip displacement have been successfully performed. Because we had taken into account frequency-based criteria from the first designing step of our device, we demonstrate that the tuning of the HAC/LAC can be easily performed and leads to low regulator order

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

Quadrilateral modelling and robust control of a nonlinear piezoelectric cantilever.

International audiencePiezocantilevers are commonly used for the actuation of micromechatronic systems. These systems are generally used to perform micromanipulation tasks which require high positioning accuracy. However, the nonlinearities, i.e. the hysteresis and the creep, of piezoelectric materials and the influence of the environment (vibrations, temperature change, etc.) create difficulties for such a performance to be achieved. Various models have been used to take into account the nonlinearities but they are often complex. In this paper, we study a one degree of freedom piezoelectric cantilever. For that, we propose a simple new model where the hysteresis curve is approximated by a quadrilateral and the creep is considered to be a disturbance. To facilitate the modelling, we first demonstrate that the dynamic hysteresis of the piezocantilever is equivalent to a static hysteresis, i.e. a varying gain, in series with a linear dynamic part. The obtained model is used to synthesize a linear robust controller, making it possible to achieve the performances required in micromanipulation tasks. The experimental results show the relevance of the combination of the developed model and the synthesized robust H∞ controller

Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation

first_page settings Open AccessArticle Advances in Tracking Control for Piezoelectric Actuators Using Fuzzy Logic and Hammerstein-Wiener Compensation by Cristian Napole 1,* [OrcID] , Oscar Barambones 1,* [OrcID] , Isidro Calvo 1 [OrcID] , Mohamed Derbeli 1 [OrcID] , Mohammed Yousri Silaa 1 [OrcID] and Javier Velasco 2 [OrcID] 1 System Engineering and Automation Deparment, Faculty of Engineering of Vitoria-Gasteiz, Basque Country University (UPV/EHU), 01006 Vitoria-Gasteiz, Spain 2 Fundación Centro de Tecnologías Aeronáuticas (CTA), Juan de la Cierva 1, 01510 Miñano, Spain * Authors to whom correspondence should be addressed. Mathematics 2020, 8(11), 2071; https://doi.org/10.3390/math8112071 Received: 23 October 2020 / Revised: 16 November 2020 / Accepted: 17 November 2020 / Published: 20 November 2020 (This article belongs to the Special Issue Fuzzy Applications in Industrial Engineering) Download PDF Browse Figures Abstract Piezoelectric actuators (PEA) are devices that are used for nano- microdisplacement due to their high precision, but one of the major issues is the non-linearity phenomena caused by the hysteresis effect, which diminishes the positioning performance. This study presents a novel control structure in order to reduce the hysteresis effect and increase the PEA performance by using a fuzzy logic control (FLC) combined with a Hammerstein–Wiener (HW) black-box mapping as a feedforward (FF) compensation. In this research, a proportional-integral-derivative (PID) was contrasted with an FLC. From this comparison, the most accurate was taken and tested with a complex structure with HW-FF to verify the accuracy with the increment of complexity. All of the structures were implemented in a dSpace platform to control a commercial Thorlabs PEA. The tests have shown that an FLC combined with HW was the most accurate, since the FF compensate the hysteresis and the FLC reduced the errors; the integral of the absolute error (IAE), the root-mean-square error (RMSE), and relative root-mean-square-error (RRMSE) for this case were reduced by several magnitude orders when compared to the feedback structures. As a conclusion, a complex structure with a novel combination of FLC and HW-FF provided an increment in the accuracy for a high-precision PEA.This research was funded by Basque Government and UPV/EHU projects