Iterative Learning Control design for uncertain and time-windowed systems

Iterative Learning Control (ILC) is a control strategy capable of dramatically increasing the performance of systems that perform batch repetitive tasks. This performance improvement is achieved by iteratively updating the command signal, using measured error data from previous trials, i.e., by learning from past experience. This thesis deals with ILC for time-windowed and uncertain systems. With the term "time-windowed systems", we mean systems in which actuation and measurement time intervals differ. With "uncertain systems", we refer to systems whose behavior is represented by incomplete or inaccurate models. To study the ILC design issues for time-windowed systems, we consider the task of residual vibration suppression in point-to-point motion problems. In this application, time windows are used to modify the original system to comply with the task. With the properties of the time-windowed system resulting in nonconverging behavior of the original ILC controlled system, we introduce a novel ILC design framework in which convergence can be achieved. Additionally, this framework reveals new design freedom in ILC for point-to-point motion problems, which is unknown in "standard" ILC. Theoretical results concerning the problem formulation and control design for these systems are supported by experimental results on a SISO and MIMO flexible structure. The analysis and design results of ILC for time-windowed systems are subsequently extended to the whole class of linear systems whose input and output are filtered with basis functions (which include time windows). Analysis and design theory of ILC for this class of systems reveals how different ILC objectives can be reached by design of separate parts of the ILC controller. Our research on ILC for uncertain systems is divided into two parts. In the first part, we formulate an approach to analyze the robustness properties of existing ILC controllers, using well developed µ theory. To exemplify our findings, we analyze the robustness properties of linear quadratic (LQ) norm optimal ILC controllers. Moreover, we show that the approach is applicable to the class of linear trial invariant ILC controlled systems with basis functions. In the second part, we present a finite time interval robust ILC control strategy that is robust against model uncertainty as given by an additive uncertainty model. For that, we exploit H1 control theory, however, modified such that the controller is not restricted to be causal and operates on a finite time interval. Furthermore, we optimize the robust controller so as to optimize performance while remaining robustly monotonically convergent. By means of experiments on a SISO flexible system, we show that this control strategy can indeed outperform LQ norm optimal ILC and causal robust ILC control strategies

Muscle Force Estimation and Fatigue Detection Based on sEMG Signals

Ph.DDOCTOR OF PHILOSOPH

Waveform Advancements and Synchronization Techniques for Generalized Frequency Division Multiplexing

To enable a new level of connectivity among machines as well as between people and machines, future wireless applications will demand higher requirements on data rates, response time, and reliability from the communication system. This will lead to a different system design, comprising a wide range of deployment scenarios. One important aspect is the evolution of physical layer (PHY), specifically the waveform modulation. The novel generalized frequency division multiplexing (GFDM) technique is a prominent proposal for a flexible block filtered multicarrier modulation. This thesis introduces an advanced GFDM concept that enables the emulation of other prominent waveform candidates in scenarios where they perform best. Hence, a unique modulation framework is presented that is capable of addressing a wide range of scenarios and to upgrade the PHY for 5G networks. In particular, for a subset of system parameters of the modulation framework, the problem of symbol time offset (STO) and carrier frequency offset (CFO) estimation is investigated and synchronization approaches, which can operate in burst and continuous transmissions, are designed. The first part of this work presents the modulation principles of prominent 5G candidate waveforms and then focuses on the GFDM basic and advanced attributes. The GFDM concept is extended towards the use of OQAM, introducing the novel frequency-shift OQAM-GFDM, and a new low complexity model based on signal processing carried out in the time domain. A new prototype filter proposal highlights the benefits obtained in terms of a reduced out-of-band (OOB) radiation and more attractive hardware implementation cost. With proper parameterization of the advanced GFDM, the achieved gains are applicable to other filtered OFDM waveforms. In the second part, a search approach for estimating STO and CFO in GFDM is evaluated. A self-interference metric is proposed to quantify the effective SNR penalty caused by the residual time and frequency misalignment or intrinsic inter-symbol interference (ISI) and inter-carrier interference (ICI) for arbitrary pulse shape design in GFDM. In particular, the ICI can be used as a non-data aided approach for frequency estimation. Then, GFDM training sequences, defined either as an isolated preamble or embedded as a midamble or pseudo-circular pre/post-amble, are designed. Simulations show better OOB emission and good estimation results, either comparable or superior, to state-of-the-art OFDM system in wireless channels

Design, Construction, and Applications of a High-Resolution Terahertz Time-Domain Spectrometer

This thesis reports on the design, construction, and initial applications of a high-resolution terahertz time-domain ASOPS spectrometer. The instrument employs asynchronous optical sampling (ASOPS) between two Ti:sapphire ultrafast lasers operating at a repetition rate of approximately 80 MHz, and we thus demonstrate a THz frequency resolution approaching the limit of that repetition rate. This is an order of magnitude improvement in resolution over typical THz time-domain spectrometers. The improved resolution is important for our primary effort of collecting THz spectra for far-infrared astronomy. We report on various spectroscopic applications including the THz rotational spectrum of water, where we achieve a mean frequency error, relative to established line centers, of 27.0 MHz. We also demonstrate application of the THz system to the long-duration observation of a coherent magnon mode in a anti-ferromagnetic yttrium iron oxide (YFeO3) crystal. Furthermore, we apply the all-optical virtual delay line of ASOPS to a transient thermoreflectance experiment for quickly measuring the thermal conductivity of semiconductors

Wireless Sensors and Actuators for Structural Health Monitoring of Fiber Composite Materials

This work evaluates and investigates the wireless generation and detection of Lamb-waves on fiber-reinforced materials using surface applied or embedded piezo elements. The general target is to achieve wireless systems or sensor networks for Structural Health Monitoring (SHM), a type of Non-Destructive-Evaluation (NDE). In this sense, a fully wireless measurement system that achieves power transmission implementing inductive coils is reported. This system allows a reduction of total system weight as well as better integration in the structure. A great concern is the characteristics of the material, in which the system is integrated, because the properties can have a direct impact on the strength of the magnetic field. Carbon-Fiber-Reinforced-Polymer (CFRP) is known to behave as an electrical conductor, shielding radio waves with increasing worse effects at higher frequencies. Due to the need of high power and voltage, interest is raised to evaluate the operation of piezo as actuators at the lower frequency ranges. To this end, actuating occurs at the International Scientific and Medical (ISM) band of 125 kHz or low-frequency (LF) range. The feasibility of such system is evaluated extensively in this work. Direct excitation, is done by combining the actuator bonded to the surface or embedded in the material with an inductive LF coil and setting the circuit in resonance. A more controlled possibility, also explored, is the use of electronics to generate a Hanning-windowed-sine to excite the PWAS in a narrow spectrum. In this case, only wireless power is transmitted to the actuator node, and this lastly implements a Piezo-driver to independently excite Lamb-waves. Sensing and data transfer, on the other hand, is done using the high-frequency (HF) 13.56 MHz. The HF range covers the requirements of faster sampling rate and lower energy content. A re-tuning of the antenna coils is performed to obtain better transmission qualities when the system is implemented in CFRP. Several quasi-isotropic (QI) CFRP plates with sensor and actuator nodes were made to measure the quality of transmission and the necessary energy to stimulate the actuator-sensor system. In order to produce baselines, measurements are prepared from a healthy plate under specific temperature and humidity conditions. The signals are evaluated to verify the functionality in the presence of defects. The measurements demonstrate that it is possible to wirelessly generate Lamb-waves while early results show the feasibility to determine the presence of structural failure. For instance, progress has been achieved detecting the presence of a failure in the form of drilled holes introduced to the structure. This work shows a complete set of experimental results of different sensor/-actuator nodes

Bench-Top Validation of Intelligent Mouth Guard

Concussion is the signature athletics injury of the 21st Century. Scientists are hard at work monitoring effects of hard impacts on the human brain. However, existing tools and devices are inadequate to screen the effects. Hence, a new approach is required to accurately quantify peak values of head impacts or concussions and relate these values to clinical brain health outcomes. A new head impact dosimeter, the Intelligent Mouth Guard (IMG) has been developed and can be conveniently located inside the mouth. In this study, the IMG printed circuit board (PCB) including four (4) high-quality shock resistant sensors has been developed and implemented as a tri-axial impact analyzer in a mouthpiece. The bench-top validation process of the IMG was divided into theoretical uncertainty analysis of linear accelerometers, theoretical uncertainty analysis of angular rate sensors, bench-top uniaxial impact testing of linear accelerometers and bench-top uniaxial static testing of angular rate sensors. More specifically, this study also presents a method based on National Bureau of Standards (NBS) of analyzing measurement error for any components of a specialized electrical circuit and any types of data acquisition system. In the current application of an IMG printed circuit board (PCB), utilized for linear acceleration, angular acceleration and angular velocity measurements, has sensor uncertainties quantified. The uncertainty model is branched into two parts: The bias error (B) and the random error (R). In this paper, expected measurement error types for PCB components (ADXL001 linear accelerometer, L3G4200D gyroscope) are quantified and their effects on the IMG system are computed. The uncertainty analysis presented here can be a guide in future in vitro and in vivo IMG validation tests. During bench-top testing, IMG linear accelerometers quantified peak linear acceleration with 98.2 accuracy and 98.0 precision. The IMG gyroscope quantified peak angular velocity with 97.0 accuracy and 99.7 precision. In su

Bench-Top Validation of Intelligent Mouth Guard

Concussion is the signature athletics injury of the 21st Century. Scientists are hard at work monitoring effects of hard impacts on the human brain. However, existing tools and devices are inadequate to screen the effects. Hence, a new approach is required to accurately quantify peak values of head impacts or concussions and relate these values to clinical brain health outcomes. A new head impact dosimeter, the Intelligent Mouth Guard (IMG) has been developed and can be conveniently located inside the mouth. In this study, the IMG printed circuit board (PCB) including four (4) high-quality shock resistant sensors has been developed and implemented as a tri-axial impact analyzer in a mouthpiece. The bench-top validation process of the IMG was divided into theoretical uncertainty analysis of linear accelerometers, theoretical uncertainty analysis of angular rate sensors, bench-top uniaxial impact testing of linear accelerometers and bench-top uniaxial static testing of angular rate sensors. More specifically, this study also presents a method based on National Bureau of Standards (NBS) of analyzing measurement error for any components of a specialized electrical circuit and any types of data acquisition system. In the current application of an IMG printed circuit board (PCB), utilized for linear acceleration, angular acceleration and angular velocity measurements, has sensor uncertainties quantified. The uncertainty model is branched into two parts: The bias error (B) and the random error (R). In this paper, expected measurement error types for PCB components (ADXL001 linear accelerometer, L3G4200D gyroscope) are quantified and their effects on the IMG system are computed. The uncertainty analysis presented here can be a guide in future in vitro and in vivo IMG validation tests. During bench-top testing, IMG linear accelerometers quantified peak linear acceleration with 98.2 accuracy and 98.0 precision. The IMG gyroscope quantified peak angular velocity with 97.0 accuracy and 99.7 precision. In su