Effective procedure for the optimization of the linear controller in an industrial drive for a nonlinear mechanism

Il progetto di tesi è incentrato sull’ottimizzazione del procedimento di taratura dei regolatori lineari degli anelli di controllo di posizione e velocità presenti negli azionamenti usati industrialmente su macchine automatiche, specialmente quando il carico è ad inerzia variabile in dipendenza dalla posizione, dunque non lineare, come ad esempio un quadrilatero articolato. Il lavoro è stato svolto in collaborazione con l’azienda G.D S.p.A. ed il meccanismo di prova è realmente utilizzato nelle macchine automatiche per il packaging di sigarette. L’ottimizzazione si basa sulla simulazione in ambiente Matlab/Simulink dell’intero sistema di controllo, cioè comprensivo del modello Simulink degli anelli di controllo del drive, inclusa la dinamica elettrica del motore, e del modello Simscape del meccanismo, perciò una prima necessaria fase del lavoro è stata la validazione di tali modelli affinché fossero sufficientemente fedeli al comportamento reale. Il secondo passo è stato fornire una prima taratura di tentativo che fungesse da punto di partenza per l’algoritmo di ottimizzazione, abbiamo fatto ciò linearizzando il modello meccanico con l’inerzia minima e utilizzando il metodo delle formule di inversione per determinare i parametri di controllo. Già questa taratura, seppur conservativa, ha portato ad un miglioramento delle performance del sistema rispetto alla taratura empirica comunemente fatta in ambito industriale. Infine, abbiamo lanciato l’algoritmo di ottimizzazione definendo opportunamente la funzione di costo, ed il risultato è stato decisamente positivo, portando ad un miglioramento medio del massimo errore di inseguimento di circa il 25%, ma anche oltre il 30% in alcuni casi.

Digital design of an EPC Gen2 controller for enhanced RFID tags

This thesis presents an improvement of the long range battery-less UHF RFID platform for sensor applications which is based on the open source Wireless Identification and Sensing Platform (WISP) project. The purpose of this work is to design a digital logic that performs the RFID EPC gen2 protocol communication, is able to acquire information by sensors and provide an accurate estimation of tag location ensuring low energy consumption. This thesis will describe the hardware architecture on which the digital logic was inserted, the Verilog code developed, the methods by which the digital logic was tested and an explorative study of chip synthesis on Cadence.

Flexible Computing Systems For AI Acceleration At The Extreme Edge Of The IoT

Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors into actionable information, directly on IoT end-nodes. This computing paradigm, in which end-nodes no longer depend entirely on the Cloud, offers undeniable benefits, driving a large research area (TinyML) to deploy leading Machine Learning (ML) algorithms on micro-controller class of devices. To fit the limited memory storage capability of these tiny platforms, full-precision Deep Neural Networks (DNNs) are compressed by representing their data down to byte and sub-byte formats, in the integer domain. However, the current generation of micro-controller systems can barely cope with the computing requirements of QNNs. This thesis tackles the challenge from many perspectives, presenting solutions both at software and hardware levels, exploiting parallelism, heterogeneity and software programmability to guarantee high flexibility and high energy-performance proportionality. The first contribution, PULP-NN, is an optimized software computing library for QNN inference on parallel ultra-low-power (PULP) clusters of RISC-V processors, showing one order of magnitude improvements in performance and energy efficiency, compared to current State-of-the-Art (SoA) STM32 micro-controller systems (MCUs) based on ARM Cortex-M cores. The second contribution is XpulpNN, a set of RISC-V domain specific instruction set architecture (ISA) extensions to deal with sub-byte integer arithmetic computation. The solution, including the ISA extensions and the micro-architecture to support them, achieves energy efficiency comparable with dedicated DNN accelerators and surpasses the efficiency of SoA ARM Cortex-M based MCUs, such as the low-end STM32M4 and the high-end STM32H7 devices, by up to three orders of magnitude. To overcome the Von Neumann bottleneck while guaranteeing the highest flexibility, the final contribution integrates an Analog In-Memory Computing accelerator into the PULP cluster, creating a fully programmable heterogeneous fabric that demonstrates end-to-end inference capabilities of SoA MobileNetV2 models, showing two orders of magnitude performance improvements over current SoA analog/digital solutions.

Automated service provisioning in programmable network infrastructures

Modern networks are undergoing a fast and drastic evolution, with software taking a more predominant role. Virtualization and cloud-like approaches are replacing physical network appliances, reducing the management burden of the operators. Furthermore, networks now expose programmable interfaces for fast and dynamic control over traffic forwarding. This evolution is backed by standard organizations such as ETSI, 3GPP, and IETF. This thesis will describe which are the main trends in this evolution. Then, it will present solutions developed during the three years of Ph.D. to exploit the capabilities these new technologies offer and to study their possible limitations to push further the state-of-the-art. Namely, it will deal with programmable network infrastructure, introducing the concept of Service Function Chaining (SFC) and presenting two possible solutions, one with Openstack and OpenFlow and the other using Segment Routing and IPv6. Then, it will continue with network service provisioning, presenting concepts from Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC). These concepts will be applied to network slicing for mission-critical communications and Industrial IoT (IIoT). Finally, it will deal with network abstraction, with a focus on Intent Based Networking (IBN). To summarize, the thesis will include solutions for data plane programming with evaluation on well-known platforms, performance metrics on virtual resource allocations, novel practical application of network slicing on mission-critical communications, an architectural proposal and its implementation for edge technologies in Industrial IoT scenarios, and a formal definition of intent using a category theory approach.

Integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment

The computer controlled screwdriver is a modern technique to perform automatic screwing/unscrewing operations.The main focus is to study the integration of the computer controlled screwdriver for Robotic manufacturing in the ROS environment.This thesis describes a concept of automatic screwing mechanism composed by universal robots, in which one arm of the robot is for inserting cables and the other is for screwing the cables on the control panel switch gear box. So far this mechanism is carried out by human operators and is a fairly complex one to perform, due to the multiple cables and connections involved. It's for this reason that an automatic cabling and screwing process would be highly preferred within automotive/automation industries. A study is carried out to analyze the difficulties currently faced and a controller based algorithm is developed to replace the manual human efforts using universal robots, thereby allowing robot arms to insert the cables and screw them onto the control panel switch gear box. Experiments were conducted to evaluate the insertion and screwing strategy, which shows the result of inserting and screwing cables on the control panel switch gearbox precisely.

Valutazione sperimentale di approcci di TinyML per problemi di classificazione: un caso di studio con Arduino Nano 33 BLE

Il TinyMachineLearning (TinyML) è un campo di ricerca nato recentemente che si inserisce nel contesto dell’Internet delle cose (IoT). Mentre l’idea tradizionale dell’IoT era che i dati venissero inviati da un dispositivo locale a delle infrastrutture cloud per l’elaborazione, il paradigma TinyML d’altra parte, propone di integrare meccanismi basati sul Machine Learning direttamente all’interno di piccoli oggetti alimentati da microcontrollori (MCU ). Ciò apre la strada allo sviluppo di nuove applicazioni e servizi che non richiedono quindi l’onnipresente supporto di elaborazione dal cloud, che, come comporta nella maggior parte dei casi, consumi elevati di energia e rischi legati alla sicurezza dei dati e alla privacy. In questo lavoro sono stati svolti diversi esperimenti cercando di identificare le sfide e le opportunità correlate al TinyML. Nello specifico, vengono valutate e analizzate le prestazioni di alcuni algoritmi di ML integrati in una scheda Arduino Nano 33 BLE Sense, attraverso un framework TinyML. Queste valutazioni sono state effettuate conducendo cinque diversi macro esperimenti, ovvero riconoscimento di Colori, di Frequenze, di Vibrazioni, di Parole chiave e di Gesti. In ogni esperimento, oltre a valutare le metriche relative alla bontà dei classificatori, sono stati analizzati l’occupazione di memoria e il tasso di inferenza (tempo di predizione). I dati utilizzati per addestrare i classificatori sono stati raccolti direttamente con i sensori di Arduino Nano. I risultati mostrano che il TinyML può essere assolutamente utilizzato per discriminare correttamente tra diverse gamme di suoni, colori, modelli di vibrazioni, parole chiave e gesti aprendo la strada allo sviluppo di nuove promettenti applicazioni sostenibili.

Supporto alla creazione e gestione di una rete virtualizzata basata su controller Ryu

L'erogazione dei servizi informatici tramite cloud è ormai una delle soluzioni più in voga nel mercato odierno, tant'è che, analizzando le statistiche fornite dalle piattaforme principali, anche il futuro sembra andare proprio in quella direzione. Quest'evoluzione avrà un forte impatto persino nelle telecomunicazioni, dove le tecniche di virtualizzazione e softwarizzazione vengono già oggi impiegate per facilitare la gestione delle infrastrutture di rete, creando le cosiddette SDN (Software Defined Network). I provider che scelgono di adottare queste soluzioni ottengono un elevato grado di flessibilità dei propri servizi, facilitando notevolmente lo sviluppo di nuove funzionalità, grazie alla presenza di controller esterni a cui vengono demandati gli aspetti di gestione della rete stessa. In uno scenario di questo tipo è fondamentale che gli strumenti volti allo studio e alla sperimentazione di reti software-based siano in grado di stare al passo con i tempi, utilizzando tecnologie all'avanguardia ed accessibili anche agli utenti che si interfacciano per la prima volta con queste metodologie. Perché questo sia possibile è necessario che telecomunicazioni e sviluppo software, aspetti storicamente appartenenti a due mondi dell'informatica paralleli, si uniscano. Ad oggi gli strumenti che permettono di operare su SDN sono innumerevoli, ma spesso accomunati dalla mancanza di qualsivoglia interfaccia grafica, restringendo l'utenza di riferimento ad un gruppo ancor più di nicchia, escludendo gli utilizzatori alle prime armi. L'obiettivo di questo progetto è proporre uno strumento alternativo, basato su Ryu, che permetta all’utente di creare, configurare e gestire secondo le proprie esigenze una rete virtuale, attraverso un’interfaccia grafica e un simulatore interattivo per controllare e visualizzare lo stato dei dispositivi connessi. Infine, verranno analizzati i vantaggi didattici ottenuti dall'impiego dell'applicativo rispetto alle metodologie classiche.

Removal torque of zirconia abutment screws under dry and wet conditions

The aim of this study was to verify whether screw abutment lubrication can generate higher preload values compared to non-lubricated screws, a titanium abutment was screwed onto an implant analog and scanned with the Procera System to generate 20 zirconia abutments. MKIII Brånemark implants were clamped to a precision torque device, and the abutments were distributed in dry and wet groups with 10 specimens each. In the wet groups, the inner threads of the implants were filled with artificial saliva. All abutments were fastened with a Torqtite screw under 32 Ncm. Ten detorque measurements were performed per group pushing the reverse button of the Torque controller soon after screw tightening with values registered. The mean detorque values were calculated and compared by a Student's t test (?=0.05). The wet condition presented significantly higher mean detorque than the dry condition (31.5 ± 1.2 versus 27.5 ± 1.5 Ncm, respectively; p=0.0000024). In conclusion, there was always a loss in the initial torque values when the removal torque was measured under both conditions. The wet condition presented higher mean torque than the dry condition. Better preload values were established in the wet group, suggesting that the abutment screw must be lubricated in saliva to avoid further loosening.

Aspectos estratégicos e econômicos da política de bonificação em quantidade de produto

ste trabalho objetiva identificar a percepção dos gestores de controladoria de indústrias sobre os aspectos estratégicos e econômicos da decisão de bonificação em quantidade de produto. A premissa é que os resultados econômicos gerados pela decisão de desconto no preço e de bonificação em quantidade de produto são iguais, considerando a mesma quantidade de produto entregue ao cliente. Com base no banco de dados da FIPECAFI- FEA-USP, analisaram-se 91 questionários encaminhados a controllers atuantes em diversos setores. Os resultados revelam: 1) um número muito significativo de empresas da amostra selecionada adota a bonificação em produtos; 2) a área comercial é a principal responsável por essa decisão; e 3) identificação da percepção dos controllers sobre aspectos decisórios de bonificação em quantidade de produtos.

Unexpected Diversity of Cellular Immune Responses against Nef and Vif in HIV-1-Infected Patients Who Spontaneously Control Viral Replication

Background: HIV-1-infected individuals who spontaneously control viral replication represent an example of successful containment of the AIDS virus. Understanding the anti-viral immune responses in these individuals may help in vaccine design. However, immune responses against HIV-1 are normally analyzed using HIV-1 consensus B 15-mers that overlap by 11 amino acids. Unfortunately, this method may underestimate the real breadth of the cellular immune responses against the autologous sequence of the infecting virus. Methodology and Principal Findings: Here we compared cellular immune responses against nef and vif-encoded consensus B 15-mer peptides to responses against HLA class I-predicted minimal optimal epitopes from consensus B and autologous sequences in six patients who have controlled HIV-1 replication. Interestingly, our analysis revealed that three of our patients had broader cellular immune responses against HLA class I-predicted minimal optimal epitopes from either autologous viruses or from the HIV-1 consensus B sequence, when compared to responses against the 15-mer HIV-1 type B consensus peptides. Conclusion and Significance: This suggests that the cellular immune responses against HIV-1 in controller patients may be broader than we had previously anticipated.

Embedded DSP-Based Compact Fuzzy System and Its Application for Induction-Motor V/f Speed Control

This paper presents a compact embedded fuzzy system for three-phase induction-motor scalar speed control. The control strategy consists in keeping constant the voltage-frequency ratio of the induction-motor supply source. A fuzzy-control system is built on a digital signal processor, which uses speed error and speed-error variation to change both the fundamental voltage amplitude and frequency of a sinusoidal pulsewidth modulation inverter. An alternative optimized method for embedded fuzzy-system design is also proposed. The controller performance, in relation to reference and load-torque variations, is evaluated by experimental results. A comparative analysis with conventional proportional-integral controller is also achieved.

Harmonic identification using parallel neural networks in single-phase systems

In this paper, artificial neural networks are employed in a novel approach to identify harmonic components of single-phase nonlinear load currents, whose amplitude and phase angle are subject to unpredictable changes, even in steady-state. The first six harmonic current components are identified through the variation analysis of waveform characteristics. The effectiveness of this method is tested by applying it to the model of a single-phase active power filter, dedicated to the selective compensation of harmonic current drained by an AC controller. Simulation and experimental results are presented to validate the proposed approach. (C) 2010 Elsevier B. V. All rights reserved.

Robust STATCOM control for the stabilisation of fixed-speed wind turbines during low voltages

This paper presents a robust voltage control scheme for fixed-speed wind generators using a static synchronous compensator (STATCOM) controller. To enable a linear and robust control framework with structured uncertainty, the overall system is represented by a linear part plus a nonlinear part that covers an operating range of interest required to ensure stability during severe low voltages. The proposed methodology is flexible and readily applicable to larger wind farms of different configurations. The performance of the control strategy is demonstrated on a two area test system. Large disturbance simulations demonstrate that the proposed controller enhances voltage stability as well as transient stability of induction generators during low voltage ride through (LVRT) transients and thus enhances the LVRT capability. (C) 2011 Elsevier Ltd. All rights reserved.

Real-Time Voltage Regulation in Power Distribution System Using Fuzzy Control

Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.

Fuzzy pole placement based on piecewise Lyapunov functions

This paper presents a controller design method for fuzzy dynamic systems based on piecewise Lyapunov functions with constraints on the closed-loop pole location. The main idea is to use switched controllers to locate the poles of the system to obtain a satisfactory transient response. It is shown that the global fuzzy system satisfies the requirements for the design and that the control law can be obtained by solving a set of linear matrix inequalities, which can be efficiently solved with commercially available softwares. An example is given to illustrate the application of the proposed method. Copyright (C) 2009 John Wiley & Sons, Ltd.