Tracking Control for Non-Minimum Phase System and Brain Computer Interface

For generations, humans dreamed about the ability to communicate and interact with machines through thought alone or to create devices that can peer into a person’s mind and thoughts. Researchers have developed new technologies to create brain computer interfaces (BCIs), communication systems that do not depend on the brain’s normal output pathways of peripheral nerves and muscles. The objective of the first part of this thesis is to develop a new BCI based on electroencephalography (EEG) to move a computer cursor over a short training period in real time. The work motivations of this part are to increase: speed and accuracy, as in BCI settings, subject has a few seconds to make a selection with a relatively high accuracy. Recently, improvements have been developed to make EEG more accurate by increasing the spatial resolution. One such improvement is the application of the surface Laplacian to the EEG, the second spatial derivative. Tripolar concentric ring electrodes (TCREs) automatically perform the Laplacian on the surface potentials and provide better spatial selectivity and signal-to-noise ratio than conventional EEG that is recorded with conventional disc electrodes. Another important feature using TCRE is the capability to record the EEG and the TCRE EEG (tEEG) signals concurrently from the same location on the scalp for the same electrical activity coming from the brain. In this part we also demonstrate that tEEG signals can enable users to control a computer cursor rapidly in different directions with significantly higher accuracy during their first session of training for 1D and 2D cursor control. Output tracking control of non-minimum phase systems is a highly challenging problem encountered in many practical engineering applications. Classical inversion techniques provide exact output tracking but lead to internal instability, whereas modern inversion methods provide stable asymptotic tracking but produce large transient errors. Both methods provide an approximation of feedback control, which leads to non robust systems, very sensitive to noise, considerable tracking errors and a significant singularity problem. Aiming at the problem of system inversion to the true system, the objective of the second part of this thesis is to develop a new method based on true inversion for minimum phase system and approximate inversion for non-minimum phase systems. The proposed algorithm is automatic and has minimal computational complexities which make it suitable for real-time control. The process to develop the proposed algorithm is partitioned into (1) minimum phase feedforward inverse filter, and (2) non-minimum phase inversion. In a minimum phase inversion, we consider the design of a feedforward controller to invert the response of a feedback loop that has stable zero locations. The complete control system consists of a feedforward controller cascaded with a closed-loop system. The outputs of the resulting inverse filter are delayed versions of the corresponding reference input signals, and delays are given by the vector relative degree of the closed-loop

Self-Learning Longitudinal Control for On-Road Vehicles

Fahrerassistenzsysteme (Advanced Driver Assistance Systems) sind ein wichtiges Verkaufsargument für PKWs, fordern jedoch hohe Entwicklungskosten. Insbesondere die Parametrierung für Längsregelung, die einen wichtigen Baustein für Fahrerassistenzsysteme darstellt, benötigt viel Zeit und Geld, um die richtige Balance zwischen Insassenkomfort und Regelgüte zu treffen. Reinforcement Learning scheint ein vielversprechender Ansatz zu sein, um dies zu automatisieren. Diese Klasse von Algorithmen wurde bislang allerdings vorwiegend auf simulierte Aufgaben angewendet, die unter idealen Bedingungen stattfinden und nahezu unbegrenzte Trainingszeit ermöglichen. Unter den größten Herausforderungen für die Anwendung von Reinforcement Learning in einem realen Fahrzeug sind Trajektorienfolgeregelung und unvollständige Zustandsinformationen aufgrund von nur teilweise beobachteter Dynamik. Darüber hinaus muss ein Algorithmus, der in realen Systemen angewandt wird, innerhalb von Minuten zu einem Ergebnis kommen. Außerdem kann das Regelziel sich während der Laufzeit beliebig ändern, was eine zusätzliche Schwierigkeit für Reinforcement Learning Methoden darstellt. Diese Arbeit stellt zwei Algorithmen vor, die wenig Rechenleistung benötigen und diese Hürden überwinden. Einerseits wird ein modellfreier Reinforcement Learning Ansatz vorgeschlagen, der auf der Actor-Critic-Architektur basiert und eine spezielle Struktur in der Zustandsaktionswertfunktion verwendet, um mit teilweise beobachteten Systemen eingesetzt werden zu können. Um eine Vorsteuerung zu lernen, wird ein Regler vorgeschlagen, der sich auf eine Projektion und Trainingsdatenmanipulation stützt. Andererseits wird ein modellbasierter Algorithmus vorgeschlagen, der auf Policy Search basiert. Diesem wird eine automatisierte Entwurfsmethode für eine inversionsbasierte Vorsteuerung zur Seite gestellt. Die vorgeschlagenen Algorithmen werden in einer Reihe von Szenarien verglichen, in denen sie online, d.h. während der Fahrt und bei geschlossenem Regelkreis, in einem realen Fahrzeug lernen. Obwohl die Algorithmen etwas unterschiedlich auf verschiedene Randbedingungen reagieren, lernen beide robust und zügig und sind in der Lage, sich an verschiedene Betriebspunkte, wie zum Beispiel Geschwindigkeiten und Gänge, anzupassen, auch wenn Störungen während des Trainings einwirken. Nach bestem Wissen des Autors ist dies die erste erfolgreiche Anwendung eines Reinforcement Learning Algorithmus, der online in einem realen Fahrzeug lernt

Inverse modelling and inverse simulation for system engineering and control applications

Following extensive development over the past two decades, techniques of inverse simulation have led to a range of successful applications, mainly in the fields of helicopter flight mechanics, aircraft handling qualities and associated issues in terms of model validation. However, the available methods still have some well-known limitations. The traditional methods based on the Newton-Raphson algorithm suffer from numerical problems such as high-frequency oscillations and can have limitations in their applicability due to problems of input-output redundancy. The existing approaches may also show a phenomenon which has been termed “constraint oscillations” which leads to low-frequency oscillatory behaviour in the inverse solutions. Moreover, the need for derivative information may limit their applicability for situations involving manoeuvre discontinuities, model discontinuities or input constraints. Two new methods are developed to overcome these issues. The first one, based on sensitivity-analysis theory, allows the Jacobian matrix to be calculated by solving a sensitivity equation and also overcomes problems of input-output redundancy. In addition, it can improve the accuracy of results compared with conventional methods and can deal with the problem of high-frequency oscillations to some extent. The second one, based on a constrained Nelder-Mead search-based optimisation algorithm, is completely derivative-free algorithm for inverse simulation. This approach eliminates problems which make traditional inverse simulation techniques difficult to apply in control applications involving discontinuous issues such as actuator amplitude or rate limits. This thesis also offers new insight into the relationship between mathematically based techniques of model inversion and the inverse simulation approach. The similarities and shortcomings of both these methodologies are explored. The findings point to the possibility that inverse simulation can be used successfully within the control system design process for feedforward controllers for model-based output-tracking control system structures. This avoids the more complicated and relatively tedious techniques of model inversion which have been used in the past for feedforward controller design. The methods of inverse simulation presented in this thesis have been applied to a number of problems which are concerned mainly with helicopter and ship control problems and include cases involving systems having nonminimum-phase characteristics. The analysis of results for these practical applications shows that the approaches developed and presented in this thesis are of practical importance. It is believed that these developments form a useful step in moving inverse simulation methods from the status of an academic research topic to a practical and robust set of tools for engineering system design

Performance improvement of professional printing systems : from theory to practice

Performance Improvement of Professional Printing Systems: from theory to practice Markets demand continuously for higher quality, higher speed, and more energy-efficient professional printers. In this thesis, control strategies have been developed to improve the performance of both professional inkjet and laser printers. Drop-on-Demand (DoD) inkjet printing is considered as one of the most promising printing technologies. It offers several advantages including high speed, quiet operation, and compatibility with a variety of printing media. Nowadays, it has been used as low-cost and efficient manufacturing technology in a wide variety of markets. Although the performance requirements, which are imposed by the current applications, are tight, the future performance requirements are expected to be even more challenging. Several requirements are related to the jetted drop properties, namely, drop velocity, drop volume, drop velocity consistency, productivity, and reliability. Meeting the performance requirements is restricted by several operational issues that are associated with the design and operation of inkjet printheads. Major issues that are usually encountered are residual vibrations in and crosstalk among ink channels. This results in a poor printing quality for high-speed printing. Given any arbitrary bitmap, the main objective is to design actuation pulses such that variations in the velocity and volume of the jetted drops are minimized. Several model-based feedfoward control techniques using an existing model are implemented to generate appropriate input pulses for the printhead. Although the implementation of the model-based techniques shows a considerable improvement of the printhead performance compared with the current performance, further improvements are still necessary. We observe that besides the pulse shape the state of the ink surface at the nozzle plate (speed, position) at the start of the pulse influences the drop velocity considerably. This state at firing depends also on previous pixels in the bitmap of the image. Consequently, any pulse design has to guarantee almost the same initial state when firing a drop. Based on these facts, a model-free optimization scheme is developed to minimize the drop velocity variations taking into account the bitmap information. Experimental results show the effectiveness of the optimized pulses. Laser printing systems are highly depending on the appropriate combination of several design factors so as to become functional in a desired working range. The physical printing process involves multiple temperature set points at different places, precise electro-magnetic conditions, transfer of toner through certain pressures and layouts, and many other technical considerations. In the laser printing system there are several challenging issues and unknown disturbances. They originate from different sources, such as the printer itself (unknown phenomena appear, disturbances that are not foreseen, wear, contamination, failures, bugs), the environment of the system (power supply variations, temperature, humidity, vibrations), and the printing media (weight, coating, thermal properties, humidity characteristics, and initial temperature). These issues have a negative effect on the stability and performance of the laser printing system. The objective is to design a control scheme to achieve printing quality requirements and a high productivity. Good printing quality means that the fusing temperature should track a certain reference signal at different operating conditions. Based on the printing system behavior, we propose two different control schemes to cope with the large parameter variations and disturbances, namely, a Model Reference Adaptive Controller (MRAC) and a nonlinear (scheduled) observer-based output feedback control scheme. Both control techniques yield considerable performance improvements compared with the present industrial controller

Design of Low-Order Controllers using Optimization Techniques

In many applications, especially in the process industry, low-level controllers are the workhorses of the automated production lines. The aim of this study has been to provide simple tuning procedures, either optimization-based methods or tuning rules, for design of low-order controllers. The first part of this thesis deals with PID tuning. Design methods or both SISO and MIMO PID controllers based on convex optimization are presented. The methods consist of solving a nonconvex optimization problem by deriving convex approximations of the original problem and solving these iteratively until convergence. The algorithms are fast because of the convex approximations. The controllers obtained minimize low-frequency sensitivity subject to constraints that ensure robustness to process variations and limitations of control signal effort. The second part of this thesis deals with tuning of feedforward controllers. Tuning rules that minimize the integrated-squared-error arising from measurable step disturbances are derived for a controller that can be interpreted as a filtered and possibly time-delayed PD controller. Using a controller structure that decouples the effects of the feedforward and feedback controllers, the controller is optimal both in open and closed loop settings. To improve the high-frequency noise behavior of the feedforward controller, it is proposed that the optimal controller is augmented with a second-order filter. Several aspects on the tuning of this filter are discussed. For systems with PID controllers, the response to step changes in the reference can be improved by introducing set-point weighting. This can be interpreted as feedforward from the reference signal to the control signal. It is shown how these weights can be found by solving a convex optimization problem. Proportional set-point weight that minimizes the integrated-absolute-error was obtained for a batch of over 130 different processes. From these weights, simple tuning rules were derived and the performance was evaluated on all processes in the batch using five different feedback controller tuning methods. The proposed tuning rules could improve the performance by up to 45% with a modest increase in actuation

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

Peer reviewedPostprin

Re-Sonification of Objects, Events, and Environments

abstract: Digital sound synthesis allows the creation of a great variety of sounds. Focusing on interesting or ecologically valid sounds for music, simulation, aesthetics, or other purposes limits the otherwise vast digital audio palette. Tools for creating such sounds vary from arbitrary methods of altering recordings to precise simulations of vibrating objects. In this work, methods of sound synthesis by re-sonification are considered. Re-sonification, herein, refers to the general process of analyzing, possibly transforming, and resynthesizing or reusing recorded sounds in meaningful ways, to convey information. Applied to soundscapes, re-sonification is presented as a means of conveying activity within an environment. Applied to the sounds of objects, this work examines modeling the perception of objects as well as their physical properties and the ability to simulate interactive events with such objects. To create soundscapes to re-sonify geographic environments, a method of automated soundscape design is presented. Using recorded sounds that are classified based on acoustic, social, semantic, and geographic information, this method produces stochastically generated soundscapes to re-sonify selected geographic areas. Drawing on prior knowledge, local sounds and those deemed similar comprise a locale's soundscape. In the context of re-sonifying events, this work examines processes for modeling and estimating the excitations of sounding objects. These include plucking, striking, rubbing, and any interaction that imparts energy into a system, affecting the resultant sound. A method of estimating a linear system's input, constrained to a signal-subspace, is presented and applied toward improving the estimation of percussive excitations for re-sonification. To work toward robust recording-based modeling and re-sonification of objects, new implementations of banded waveguide (BWG) models are proposed for object modeling and sound synthesis. Previous implementations of BWGs use arbitrary model parameters and may produce a range of simulations that do not match digital waveguide or modal models of the same design. Subject to linear excitations, some models proposed here behave identically to other equivalently designed physical models. Under nonlinear interactions, such as bowing, many of the proposed implementations exhibit improvements in the attack characteristics of synthesized sounds.Dissertation/ThesisPh.D. Electrical Engineering 201

Self-Learning Longitudinal Control for On-Road Vehicles

Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world experiments

Robust nonlinear control of vectored thrust aircraft

An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations

Discrete-time optimal preview control

There are many situations in which one can preview future reference signals, or future disturbances. Optimal Preview Control is concerned with designing controllers which use this preview to improve closed-loop performance. In this thesis a general preview control problem is presented which includes previewable disturbances, dynamic weighting functions, output feedback and nonpreviewable disturbances. It is then shown how a variety of problems may be cast as special cases of this general problem; of particular interest is the robust preview tracking problem and the problem of disturbance rejection with uncertainty in the previewed signal. . (', The general preview problem is solved in both the Fh and Beo settings. The H2 solution is a relatively straightforward extension ofpreviously known results, however, our contribution is to provide a single framework that may be used as a reference work when tackling a variety of preview problems. We also provide some new analysis concerning the maximum possible reduction in closed-loop H2 norm which accrues from the addition of preview action. / Name of candidate: Title of thesis: I DESCRIPTION OF THESIS Andrew Hazell Discrete-Time Optimal Preview Control The solution to the Hoo problem involves a completely new approach to Hoo preview control, in which the structure of the associated Riccati equation is exploited in order to find an efficient algorithm for computing the optimal controller. The problem tackled here is also more generic than those previously appearing in the literature. The above theory finds obvious applications in the design of controllers for autonomous vehicles, however, a particular class of nonlinearities found in typical vehicle models presents additional problems. The final chapters are concerned with a generic framework for implementing vehicle preview controllers, and also a'case study on preview control of a bicycle.Imperial Users onl