Bidirectional interactions between neuronal and hemodynamic responses to transcranial direct current stimulation (tDCS): challenges for brain-state dependent tDCS

Transcranial direct current stimulation (tDCS) has been shown to modulate cortical neural activity. During neural activity, the electric currents from excitable membranes of brain tissue superimpose in the extracellular medium and generate a potential at scalp, which is referred as the electroencephalogram (EEG). Respective neural activity (energy demand) has been shown to be closely related, spatially and temporally, to cerebral blood flow (CBF) that supplies glucose (energy supply) via neurovascular coupling. The hemodynamic response can be captured by near-infrared spectroscopy (NIRS), which enables continuous monitoring of cerebral oxygenation and blood volume. This neurovascular coupling phenomenon led to the concept of neurovascular unit (NVU) that consists of the endothelium, glia, neurons, pericytes, and the basal lamina. Here, recent works suggest NVU as an integrated system working in concert using feedback mechanisms to enable proper brain homeostasis and function where the challenge remains in capturing these mostly nonlinear spatiotemporal interactions within NVU during tDCS. Therefore, we propose EEG-NIRS-based whole-head monitoring of tDCS-induced neuronal and hemodynamic alterations for brain-state dependent tDCS

Notions of Input to Output Stability

This paper deals with several related notions of output stability with respect to inputs. The inputs may be thought of as disturbances; when there are no inputs, one obtains generalizations of the classical concepts of partial stability. The main notion studied is called input to output stability (IOS), and it reduces to input to state stability (ISS) when the output equals the complete state. Several variants, which formalize in different manners the transient behavior, are introduced. The main results provide a comparison among these notions. A companion paper establishes necessary and sufficient Lyapunov-theoretic characterizations.Comment: 16 pages See http://www.math.rutgers.edu/~sontag/ for many related paper

Robustness results in LQG based multivariable control designs

The robustness of control systems with respect to model uncertainty is considered using simple frequency domain criteria. Results are derived under a common framework in which the minimum singular value of the return difference transfer matrix is the key quantity. In particular, the LQ and LQG robustness results are discussed

적분 및 매개변수 기법 융합을 이용한 스마트폰 다중 동작에서 보행 항법

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 기계항공공학부, 2020. 8. 박찬국.In this dissertation, an IA-PA fusion-based PDR (Pedestrian Dead Reckoning) using low-cost inertial sensors is proposed to improve the indoor position estimation. Specifically, an IA (Integration Approach)-based PDR algorithm combined with measurements from PA (Parametric Approach) is constructed so that the algorithm is operated even in various poses that occur when a pedestrian moves with a smartphone indoors. In addition, I propose an algorithm that estimates the device attitude robustly in a disturbing situation by an ellipsoidal method. In addition, by using the machine learning-based pose recognition, it is possible to improve the position estimation performance by varying the measurement update according to the poses. First, I propose an adaptive attitude estimation based on ellipsoid technique to accurately estimate the direction of movement of a smartphone device. The AHRS (Attitude and Heading Reference System) uses an accelerometer and a magnetometer as measurements to calculate the attitude based on the gyro and to compensate for drift caused by gyro sensor errors. In general, the attitude estimation performance is poor in acceleration and geomagnetic disturbance situations, but in order to effectively improve the estimation performance, this dissertation proposes an ellipsoid-based adaptive attitude estimation technique. When a measurement disturbance comes in, it is possible to update the measurement more accurately than the adaptive estimation technique without considering the direction by adjusting the measurement covariance with the ellipsoid method considering the direction of the disturbance. In particular, when the disturbance only comes in one axis, the proposed algorithm can use the measurement partly by updating the other two axes considering the direction. The proposed algorithm shows its effectiveness in attitude estimation under disturbances through the rate table and motion capture equipment. Next, I propose a PDR algorithm that integrates IA and PA that can be operated in various poses. When moving indoors using a smartphone, there are many degrees of freedom, so various poses such as making a phone call, texting, and putting a pants pocket are possible. In the existing smartphone-based positioning algorithms, the position is estimated based on the PA, which can be used only when the pedestrian's walking direction and the device's direction coincide, and if it does not, the position error due to the mismatch in angle is large. In order to solve this problem, this dissertation proposes an algorithm that constructs state variables based on the IA and uses the position vector from the PA as a measurement. If the walking direction and the device heading do not match based on the pose recognized through machine learning technique, the position is updated in consideration of the direction calculated using PCA (Principal Component Analysis) and the step length obtained through the PA. It can be operated robustly even in various poses that occur. Through experiments considering various operating conditions and paths, it is confirmed that the proposed method stably estimates the position and improves performance even in various indoor environments.본 논문에서는 저가형 관성센서를 이용한 보행항법시스템 (PDR: Pedestrian Dead Reckoning)의 성능 향상 알고리즘을 제안한다. 구체적으로 보행자가 실내에서 스마트폰을 들고 이동할 때 발생하는 다양한 동작 상황에서도 운용될 수 있도록, 매개변수 기반 측정치를 사용하는 적분 기반의 보행자 항법 알고리즘을 구성한다. 또한 타원체 기반 자세 추정 알고리즘을 구성하여 외란 상황에서도 강인하게 자세를 추정하는 알고리즘을 제안한다. 추가적으로 기계학습 기반의 동작 인식 정보를 이용, 동작에 따른 측정치 업데이트를 달리함으로써 위치 추정 성능을 향상시킨다. 먼저 스마트폰 기기의 이동 방향을 정확하게 추정하기 위해 타원체 기법 기반 적응 자세 추정을 제안한다. 자세 추정 기법 (AHRS: Attitude and Heading Reference System)은 자이로를 기반으로 자세를 계산하고 자이로 센서오차에 의해 발생하는 드리프트를 보정하기 위해 측정치로 가속도계와 지자계를 사용한다. 일반적으로 가속 및 지자계 외란 상황에서는 자세 추정 성능이 떨어지는데, 추정 성능을 효과적으로 향상시키기 위해 본 논문에서는 타원체 기반 적응 자세 추정 기법을 제안한다. 측정치 외란이 들어오는 경우, 외란의 방향을 고려하여 타원체 기법으로 측정치 공분산을 조정해줌으로써 방향을 고려하지 않은 적응 추정 기법보다 정확하게 측정치 업데이트를 할 수 있다. 특히 외란이 한 축으로만 들어오는 경우, 제안한 알고리즘은 방향을 고려해 나머지 두 축에 대해서는 업데이트 해줌으로써 측정치를 부분적으로 사용할 수 있다. 레이트 테이블, 모션 캡쳐 장비를 통해 제안한 알고리즘의 자세 성능이 향상됨을 확인하였다. 다음으로 다양한 동작에서도 운용 가능한 적분 및 매개변수 기법을 융합하는 보행항법 알고리즘을 제안한다. 스마트폰을 이용해 실내를 이동할 때에는 자유도가 크기 때문에 전화 걸기, 문자, 바지 주머니 넣기 등 다양한 동작이 발생 가능하다. 기존의 스마트폰 기반 보행 항법에서는 매개변수 기법을 기반으로 위치를 추정하는데, 이는 보행자의 진행 방향과 기기의 방향이 일치하는 경우에만 사용 가능하며 일치하지 않는 경우 자세 오차로 인한 위치 오차가 크게 발생한다. 이러한 문제를 해결하기 위해 본 논문에서는 적분 기반 기법을 기반으로 상태변수를 구성하고 매개변수 기법을 통해 나오는 위치 벡터를 측정치로 사용하는 알고리즘을 제안한다. 만약 기계학습을 통해 인식한 동작을 바탕으로 진행 방향과 기기 방향이 일치하지 않는 경우, 주성분 분석을 통해 계산한 진행방향을 이용해 진행 방향을, 매개변수 기법을 통해 얻은 보폭으로 거리를 업데이트해 줌으로써 보행 중 발생하는 여러 동작에서도 강인하게 운용할 수 있다. 다양한 동작 상황 및 경로를 고려한 실험을 통해 위에서 제안한 방법이 다양한 실내 환경에서도 안정적으로 위치를 추정하고 성능이 향상됨을 확인하였다.Chapter 1 Introduction 1 1.1 Motivation and Background 1 1.2 Objectives and Contribution 5 1.3 Organization of the Dissertation 6 Chapter 2 Pedestrian Dead Reckoning System 8 2.1 Overview of Pedestrian Dead Reckoning 8 2.2 Parametric Approach 9 2.2.1 Step detection algorithm 11 2.2.2 Step length estimation algorithm 13 2.2.3 Heading estimation 14 2.3 Integration Approach 15 2.3.1 Extended Kalman filter 16 2.3.2 INS-EKF-ZUPT 19 2.4 Activity Recognition using Machine Learning 21 2.4.1 Challenges in HAR 21 2.4.2 Activity recognition chain 22 Chapter 3 Attitude Estimation in Smartphone 26 3.1 Adaptive Attitude Estimation in Smartphone 26 3.1.1 Indirect Kalman filter-based attitude estimation 26 3.1.2 Conventional attitude estimation algorithms 29 3.1.3 Adaptive attitude estimation using ellipsoidal methods 30 3.2 Experimental Results 36 3.2.1 Simulation 36 3.2.2 Rate table experiment 44 3.2.3 Handheld rotation experiment 46 3.2.4 Magnetic disturbance experiment 49 3.3 Summary 53 Chapter 4 Pedestrian Dead Reckoning in Multiple Poses of a Smartphone 54 4.1 System Overview 55 4.2 Machine Learning-based Pose Classification 56 4.2.1 Training dataset 57 4.2.2 Feature extraction and selection 58 4.2.3 Pose classification result using supervised learning in PDR 62 4.3 Fusion of the Integration and Parametric Approaches in PDR 65 4.3.1 System model 67 4.3.2 Measurement model 67 4.3.3 Mode selection 74 4.3.4 Observability analysis 76 4.4 Experimental Results 82 4.4.1 AHRS results 82 4.4.2 PCA results 84 4.4.3 IA-PA results 88 4.5 Summary 100 Chapter 5 Conclusions 103 5.1 Summary of the Contributions 103 5.2 Future Works 105 국문초록 125 Acknowledgements 127Docto

Probabilistic control for uncertain systems

In this paper a new framework has been applied to the design of controllers which encompasses nonlinearity, hysteresis and arbitrary density functions of forward models and inverse controllers. Using mixture density networks, the probabilistic models of both the forward and inverse dynamics are estimated such that they are dependent on the state and the control input. The optimal control strategy is then derived which minimizes uncertainty of the closed loop system. In the absence of reliable plant models, the proposed control algorithm incorporates uncertainties in model parameters, observations, and latent processes. The local stability of the closed loop system has been established. The efficacy of the control algorithm is demonstrated on two nonlinear stochastic control examples with additive and multiplicative noise

A distributed optimization framework for localization and formation control: applications to vision-based measurements

Multiagent systems have been a major area of research for the last 15 years. This interest has been motivated by tasks that can be executed more rapidly in a collaborative manner or that are nearly impossible to carry out otherwise. To be effective, the agents need to have the notion of a common goal shared by the entire network (for instance, a desired formation) and individual control laws to realize the goal. The common goal is typically centralized, in the sense that it involves the state of all the agents at the same time. On the other hand, it is often desirable to have individual control laws that are distributed, in the sense that the desired action of an agent depends only on the measurements and states available at the node and at a small number of neighbors. This is an attractive quality because it implies an overall system that is modular and intrinsically more robust to communication delays and node failures

A Model-Based Framework for the Smart Manufacturing of Polymers

It is hard to point a daily activity in which polymeric materials or plastics are not involved. The synthesis of polymers occurs by reacting small molecules together to form, under certain conditions, long molecules. In polymer synthesis, it is mandatory to assure uniformity between batches, high-quality of end-products, efficiency, minimum environmental impact, and safety. It remains as a major challenge the establishment of operational conditions capable of achieving all objectives together. In this dissertation, different model-centric strategies are combined, assessed, and tested for two polymerization systems. The first system is the synthesis of polyacrylamide in aqueous solution using potassium persulfate as initiator in a semi-batch reactor. In this system, the proposed framework integrates nonlinear modelling, dynamic optimization, advanced control, and nonlinear state estimation. The objectives include the achievement of desired polymer characteristics through feedback control and a complete motoring during the reaction. The estimated properties are close to experimental values, and there is a visible noise reduction. A 42% improvement of set point accomplishment in average is observed when comparing feedback control combined with a hybrid discrete-time extended Kalman filter (h-DEKF) and feedback control only. The 4-state geometric observer (GO) with passive structure, another state estimation strategy, shows the best performance. Besides achieving smooth signal processing, the observer improves 52% the estimation of the final molecular weight distribution when compared with the h-DEKF. The second system corresponds to the copolymerization of ethylene with 1,9-decadiene using a metallocene catalyst in a semi-batch reactor. The evaluated operating conditions consider different diene concentrations and reaction temperatures. Initially, the nonlinear model is validated followed by a global sensitivity analysis, which permits the selection of the important parameters. Afterwards, the most important kinetic parameters are estimated online using an extended Kalman filter (EKF), a variation of the GO that uses a preconditioner, and a data-driven strategy referred as the retrospective cost model refinement (RCMR) algorithm. The first two strategies improve the measured signal, but fail to predict other properties. The RCMR algorithm demonstrates an adequate estimation of the unknown parameters, and the estimates converge close to theoretical values without requiring prior knowledge

Shape, motion, and inertial parameter estimation of space objects using teams of cooperative vision sensors

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005."February 2005."Includes bibliographical references (leaves 133-140).Future space missions are expected to use autonomous robotic systems to carry out a growing number of tasks. These tasks may include the assembly, inspection, and maintenance of large space structures; the capture and servicing of satellites; and the redirection of space debris that threatens valuable spacecraft. Autonomous robotic systems will require substantial information about the targets with which they interact, including their motions, dynamic model parameters, and shape. However, this information is often not available a priori, and therefore must be estimated in orbit. This thesis develops a method for simultaneously estimating dynamic state, model parameters, and geometric shape of arbitrary space targets, using information gathered from range imaging sensors. The method exploits two key features of this application: (1) the dynamics of targets in space are highly deterministic and can be accurately modeled; and (2) several sensors will be available to provide information from multiple viewpoints. These features enable an estimator design that is not reliant on feature detection, model matching, optical flow, or other computation-intensive pixel-level calculations. It is therefore robust to the harsh lighting and sensing conditions found in space. Further, these features enable an estimator design that can be implemented in real- time on space-qualified hardware. The general solution approach consists of three parts that effectively decouple spatial- and time-domain estimations. The first part, referred to as kinematic data fusion, condenses detailed range images into coarse estimates of the target's high-level kinematics (position, attitude, etc.).(cont.) A Kalman filter uses the high-fidelity dynamic model to refine these estimates and extract the full dynamic state and model parameters of the target. With an accurate understanding of target motions, shape estimation reduces to the stochastic mapping of a static scene. This thesis develops the estimation architecture in the context of both rigid and flexible space targets. Simulations and experiments demonstrate the potential of the approach and its feasibility in practical systems.by Matthew D. Lichter.Ph.D

미지의 정현파 외부 입력을 갖는 선형시스템을 위한 적응 출력 제어

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 2. 심형보.This dissertation investigates the output regulation problem (which is equivalent to the problem of asymptotic tracking and disturbance rejection when the reference inputs and the disturbances are generated by an autonomous differential equation, the so-called exosystem) for linear systems driven by unknown sinusoidal exosystems. Unlike previous researches, our ultimate goal is to achieve asymptotic regulation of the plant output to the origin for the sinusoidal exogenous signals (representing the reference inputs and disturbances) generated by the exosystems whose magnitudes, phases, bias, frequencies, and even the number of frequencies are all unknown. Here, the plant is linear time-invariant (LTI) single-input-single-output (SISO) systems (including non-minimum phase systems) without uncertainty. Before achieving the final control goal, we first start by considering an output regulation problem under the assumption that the number of frequencies contained in the exogenous inputs is known but magnitudes, phases, bias, and frequencies are unknown. To solve this problem, an add-on type output regulator with an adaptive observer is presented. The adaptive observer, based on the persistently exciting (PE) property, is used to estimate the frequencies of sinusoidal exogenous inputs as well as the states of plant and exosystem. Also, by add-on controller we mean an additional controller which runs harmonically with a preinstalled controller that has been in operation for the plant. When the desired performance of the preinstalled controller is not satisfactory, the add-on controller can be used. Some advantages of the proposed add-on controller include that it can be designed without much information about the preinstalled controller and it can be plugged in the feedback loop any time in operation without causing unnecessary transient response. Both simulation and experimental results of the track-following control for commercial optical disc drive (ODD) systems confirm the effectiveness of the proposed method. As the next step, we deal with the case where, as well as magnitudes, phases, bias, and frequencies, the number of frequencies contained in the exogenous inputs is unknown. To this end, a closed-form solution is given under the assumptions that the plant has hyperbolic zero dynamics (i.e., there is no zero on the imaginary axis of the complex plane), and that the number of unknown frequencies has known upper bound. In particular, the PE property is not necessary for the estimation of the unknown frequencies. For this, an adaptive observer is proposed to estimate the frequencies and the number of frequencies, simultaneously. This is important contribution, because, sufficient persistency of excitation is usually required since the unknown parameters are estimated by the adaptive control. Moreover, we propose a suitable dead-zone function with a computable dead-band only using the plant parameters to avoid the singularity problem in the transient-state and, at the same time, to achieve output regulation in the steady-state.Chapter 1 Introduction 1 1.1 Research Background 1 1.2 Contributions and Outline of the Dissertation 5 Chapter 2 Reviews of Related Prior Studies 9 2.1 Control Methods for Rejecting of Sinusoidal Disturbance 9 2.1.1 Adaptive Feedforward Cancellation (AFC) 9 2.1.2 Repetitive Control 12 2.1.3 Disturbance Observer (DOB) with Internal Model 15 2.2 Frequency Estimation Algorithms for Indirect Approach 19 2.2.1 Adaptive Notch Filtering 19 2.2.2 Phase-Locked Loops 20 2.2.3 Extended Kalman Filtering 21 2.2.4 Marinos Frequency Estimator 23 Chapter 3 Highlights of Output Regulation for Linear Systems 27 3.1 Problem Formulation 27 3.2 Output Regulation via Full Information 29 3.3 Output Regulation via Error Feedback 31 Chapter 4 Adaptive Add-on Output Regulator for Unknown Sinusoidal Exogenous Inputs 37 4.1 Add-on Output Regulator 39 4.1.1 Problem Formulation 39 4.1.2 Controller Design and Stability Analysis 41 4.2 Adaptive Add-on Output Regulator 44 4.2.1 Problem Formulation 44 4.2.2 Controller Design and Analysis 46 4.3 Industrial Application: Optical Disc Drive (ODD) Systems 54 4.3.1 Introduction of ODD Systems 54 4.3.2 Simulation Results 58 4.3.3 Experimental Results 63 Chapter 5 Adaptive Output Regulator for Unknown Number of Unknown Sinusoidal Exogenous Inputs 69 5.1 Problem Formulation 71 5.2 Adaptive Output Regulator 72 5.3 Constructive Proof of Theorem 5.2.1 75 5.4 Numerical Examples 88 Chapter 6 Conclusions and Further Issues 93 6.1 Conclusions 93 6.2 Further Issues 94 APPENDIX 97 A.1 Stabilizability and Detectability of the Plant in Chapter 4 97 A.2 Nonsingularity of the Matrix T(θ) in Chapter 4 99 A.3 Pseudo Code Implemented on the DSP Board in Chapter 4 99 A.4 Observability Property of the Pair (S, γ) in Chapter 5 101 A.5 Structure of the Matrix Tc(θ) in Chapter 5 102 A.6 Convergence Property of det2(i(t)) in Lemma 5.3.2 104 BIBLIOGRAPHY 109 국문초록 121Docto