Environmental test chamber for the support of learning and teaching in intelligent control

The paper describes the utility of a low cost, 1 m2 by 2 m forced ventilation, micro-climate test chamber, for the support of research and teaching in mechatronics. Initially developed for the evaluation of a new ventilation rate controller, the fully instrumented chamber now provides numerous learning opportunities and individual projects for both undergraduate and postgraduate research students

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

Next Generation Inverters Equipped with Virtual Synchronous Compensators for Grid Services and Grid Support

L'abstract è presente nell'allegato / the abstract is in the attachmen

High performance disturbance observer based control system design for permanent magnet synchronous AC machine applications

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonAn electrical machine is one of the main workforces in different industries and serves them in various applications. Machine drive control design involves many technical issues for efficient and robust exploitation. Over several decades, Permanent Magnet Synchronous Motor (PMSM) is getting preferred for industrial applications over its counterpart Squirrel Cage Induction Motor (SCIM) drive, because of their higher efficiency, power density, and higher torque to inertia ratio. In the prospective that PMSM drives are considered the drives of the future, there are still technical challenges and issues related to PMSM control. Many studies have been devoted to PMSM control in the past, but there are still some open research areas that bring worldwide researchers’ interests back to PMSM drive control. One of the approaches that may facilitate better performance, higher efficiency, and robust and reliable work of the control system is the disturbance observer-based control (DOBC) with linear and nonlinear output feedback control for PM synchronous machine applications. DOBC is adopted due to its ability to reject external and internal disturbances with improving tracking performance in the variable speed wind energy conversion system (WECS) to maximize power extraction. The high order disturbance observer (HODO) is utilized to estimate the aerodynamic torque-based wind speed without the use of a traditional anemometer, which reduces the overall cost and improves the reliability of the whole system. Also, this method has been designed to improve the angular shaft speed tracking of the PMSM system under load torque disturbance and speed variations. The model-based linear and nonlinear feedback control are used in the proposed control systems. The sliding mode control (SMC) with switching output feedback control law and integral SMC with linear feedback and state-dependent Riccati equation (SDRE) based approaches have been designed for the systems. The SDRE control accounts for the nonlinear multivariable structure of the WECS and is approximated with Taylor series expansion terms. The chattering inherited from SMC is eliminated by the continuous approximation technique. The sliding mode is guaranteed by eliminating the reaching mode in the proposed integral SMC. The model-free cascaded linear feedback control system based on the proportional-integral (PI) controllers use a back-calculation algorithm anti-windup scheme. The proposed speed controllers are synthesized with HODO to compensate for the external disturbance, model uncertainty, noise, and modelling errors. Moreover, servomechanism-based SDRE control, a near-optimal control system is designed to suppress the model uncertainty and noise without the use of disturbance observers. The proposed control systems for PMSM speed regulation have demonstrated a significant improvement in the angular shaft speed-tracking performance at the transients. Their performances have been tested under speed, load torque variations, and model uncertainty. For example, HODO-based SMC with switching output feedback control law (SOFCL) has demonstrated improvement by more than 78% than the PI-PI control system of the PMSM. The performance of the HODOs-based Integral SMC with SDRE nonlinear feedback is improved by 80.5% under external disturbance, model uncertainty, and noise than Integral SMC with linear feedback in the WECS. The HODO-based SDRE control with servomechanism has shown an 80.2% improvement of mean absolute percentage error under disturbances than Integral SMC with linear feedback in the WECS. The PMSM speed tracking performance of the proposed HODO-based discrete-time PI-PI control system with back-calculation algorithm anti-windup scheme is improved by 87.29% and 90.2% in the speed commands and load torque disturbance variations scenarios respectively. The simulations for testing the proposed control system of the PMSM system and WECS have been implemented in Matlab/Simulink environment. The PMSM speed control experimental results have been obtained with Lucas-Nuelle DSP-based rapid control prototyping kit.Center for International Program “Bolashak” of the Ministry of Education and Science Republic of Kazakhsta

Improving small signal stability of power systems in the presence of harmonics

This thesis investigates the impact of harmonics as a power quality issue on the dynamic behaviour of the power systems. The effectiveness of the power system stabilizers in distorted conditions is also investigated. This thesis consists of three parts as follows:The first part focuses on the operation of the power system under distorted conditions. The conventional model of a synchronous generator in the dq-frame of reference is modified to include the impact of time and space harmonics. To do this, the synchronous generator is first modelled in the harmonic domain. This model helps in calculating the additional parts of the generator fundamental components due to the harmonics. Then the Park transformation is used for calculating the modified fundamental components of the synchronous generator in dq axes. The modified generator rotor angle due to the presence of harmonics is calculated and the impact of damper windings under the influence of harmonics is investigated. This model is used to study the small-signal stability of a distorted Single Machine Infinite Bus (SMIB) system. The eigenvalue analysis method is employed and the system state space equations are calculated by linearizing the differential equations around the operating point using an analytical method. The simulation results are presented for a distorted SMIB system under the influence of different harmonic levels. The impact of damper windings and also harmonics phase angles are also investigated.In the second part of the thesis, the effectiveness of the power system damping controllers under distorted conditions is studied. This investigation is done based on a distorted SMIB system installed with a Static Synchronous Series Compensator (SSSC). In the first step, the system state space equations are derived. A Power Oscillation Damping (POD) controller with a conventional structure is installed on the SSSC to improve the system dynamic behaviour. A genetic-fuzzy algorithm is proposed for tuning the POD parameters. This method along with the observability matrix is employed to design a POD controller under sinusoidal and distorted conditions. The impact of harmonics on the effectiveness of the POD controller under distorted conditions is investigated.In the last part, the steady state and dynamic operation of an actual distributed generation system under sinusoidal and distorted conditions are studied. A decoupled harmonic power flow program is employed for steady state analysis. The nonlinear loads are modelled as decoupled harmonic current sources and the nonlinear model of synchronous generator in harmonic domain is used to calculate the injected current harmonics. For the system dynamic stability study, the power system toolbox with the modified model of the synchronous generator is used. The system eigenvalues are calculated and the effectiveness of the installed Power System Stabilisers (PSS) is investigated under sinusoidal and distorted conditions. Simulation results show that in order to guarantee the effectiveness of a PSS in distorted conditions, it is necessary to consider the harmonics in tuning its parameters

Physics-Based and Data-Driven Analytics for Enhanced Planning and Operations in Power Systems with Deep Renewable Penetration

This dissertation is motivated by the lack of combined physics-based and data-driven framework for solving power system challenges that are introduced by the integration of new devices and new system components. As increasing number of stochastic generation, responsive loads, and dynamic measurements are involved in the planning and operations of modern power systems, utilities and system operators are in great need of new analysis framework that could combine physical models and measuring data together for solving challenging planning and operational problems. In view of the above challenges, the high-level objective of this dissertation is to develop a framework for integrating measurement data into large physical systems modeled by dynamical equations. To this end, the dissertation first identifies four critical tasks for the planning and operations of the modern power systems: the data collection and pre-processing, the system situational awareness, the decision making process, as well as the post-event analysis. The dissertation then takes one concrete application in each of these critical tasks as the example, and proposes the physics-based/data-driven approach for solving the challenging problems faced by this specific application. To this end, this dissertation focuses on solving the following specific problems using physics-based/data-driven approaches. First, for the data collection and pre-processing platform, a purely data-driven approach is proposed to detect bad metering data in the phasor measurement unit (PMU) monitoring systems, and ensure the overall PMU data quality. Second, for the situational awareness platform, a physics-based voltage stability assessment method is presented to improve the situational awareness of system voltage instabilities. Third, for the decision making platform, a combined physics-based and data-driven framework is proposed to support the decision making process of PMU-based power plant model validation. Forth, for the post-event analysis platform, a physics-based post-event analysis is presented to identify the root causes of the sub-synchronous oscillations induced by the wind farm integration. The above problems and proposed solutions are discussed in detail in Section 2 through Section 5. The results of this work can be integrated to address practical problems in modern power system planning and operations