Robust hovering and trajectory tracking control of a quadrotor helicopter using acceleration feedback and a novel disturbance observer

Hovering and trajectory tracking control of rotary-wing aircrafts in the presence of uncertainties and external disturbances is a very challenging task. This thesis focuses on the development of the robust hovering and trajectory tracking control algorithms for a quadrotor helicopter subject to both periodic and aperiodic disturbances along with noise and parametric uncertainties. A hierarchical control structure is employed where high-level position controllers produce reference attitude angles for the low-level attitude controllers. Reference attitude angles are usually determined analytically from the position command signals that control the positional dynamics. However, such analytical formulas may produce large and non-smooth reference angles which must be saturated and low-pass filtered. In this thesis, desired attitude angles are determined numerically using constrained nonlinear optimization where certain magnitude and rate constraints are imposed. Furthermore, an acceleration based disturbance observer (AbDOB) is designed to estimate and suppress disturbances acting on the positional dynamics of the quadrotor. For the attitude control, a nested position, velocity, and inner acceleration feedback control structure consisting of PID and PI type controllers are developed to provide high sti ness against external disturbances. Reliable angular acceleration is estimated through an extended Kalman filter (EKF) cascaded with a classical Kalman lter (KF). This thesis also proposes a novel disturbance observer which consists of a bank of band-pass filters connected parallel to the low-pass filter of a classical disturbance observer. Band-pass filters are centered at integer multiples of the fundamental frequency of the periodic disturbance. Number and bandwidth of the band-pass filters are two crucial parameters to be tuned in the implementation of the new structure. Proposed disturbance observer is integrated with a sliding mode controller to tackle the robust hovering and trajectory tracking control problem. The sensitivity of the proposed disturbance observer based control system to the number and bandwidth of the band-pass filters are thoroughly investigated via several simulations. Simulations are carried out on a high delity model where sensor biases and measurement noise are also considered. Results show that the proposed controllers are very effective in providing robust hovering and trajectory tracking performance when the quadrotor helicopter is subject to the wind gusts generated by the Dryden wind model along with plant uncertainties and measurement noise. A comparison with the classical disturbance observer-based control is also provided where better tracking performance with improved robustness is achieved in the presence of noise and external disturbance

Adaptive Control

Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems

Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on the Energy Internet, blockchain technology and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

Benelux meeting on systems and control, 23rd, March 17-19, 2004, Helvoirt, The Netherlands

Book of abstract

Sliding Mode Control

The main objective of this monograph is to present a broad range of well worked out, recent application studies as well as theoretical contributions in the field of sliding mode control system analysis and design. The contributions presented here include new theoretical developments as well as successful applications of variable structure controllers primarily in the field of power electronics, electric drives and motion steering systems. They enrich the current state of the art, and motivate and encourage new ideas and solutions in the sliding mode control area

UDE-based controller equipped with a multiple-time-delayed filter to improve the voltage quality of inverters

In this paper, a two-degrees-of-freedom control algorithm based on uncertainty and disturbance estimator (UDE), aimed to minimize the total harmonic distortion of inverter output voltage is proposed, possessing enhanced robustness to base frequency variations. A multiple-time-delay action is combined with a commonly utilized low-pass UDE filter to increase the range of output impedance magnitude minimization around odd multiples of base frequency for enhanced rejection of typical single-phase nonlinear loads harmonics. Marginal robustness improvement achieved by increasing the number of time delays is quantified analytically and revealed to be independent of delay order. The performance of the proposed control approach and its superiority over two recently proposed methods is validated successfully by experimental results

Design Of Robust Feedback Controllers For A Laser Beam Stabilizer

This work addresses this challenge by employing two different control strategies, namely, Proportional Integral Derivative (PID) and State Feedback with an observer for control

Modeling, Analysis, and Optimization Issues for Large Space Structures

Topics concerning the modeling, analysis, and optimization of large space structures are discussed including structure-control interaction, structural and structural dynamics modeling, thermal analysis, testing, and design

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