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Machine Learning and System Identification for Estimation in Physical Systems

In this thesis, we draw inspiration from both classical system identification and modern machine learning in order to solve estimation problems for real-world, physical systems. The main approach to estimation and learning adopted is optimization based. Concepts such as regularization will be utilized for encoding of prior knowledge and basis-function expansions will be used to add nonlinear model

Robotic Seam Tracking for Friction Stir Welding under Large Contact Forces

Friction stir welding (FSW) is a solid-state welding process where metals are joined without melting. Heat is generated by friction between a rotating non-consumable tool and the work-piece material, and by mechanical deformation of the material. The process, invented in 1991, provides several benefits over arc welding and other fusion processes: No filler material has to be added, low energy cons

Self-aware computing systems : Open challenges and future research directions

In this chapter, we discuss the open challenges in building self-aware computing systems that are still being faced by the research and development community. The challenges can be theoretical, technical, computational, or even sociological. First, we highlight the challenges associated with each of the earlier parts of the book and summarize on respective future research directions. We then offer

A Radial Basis Function Method for Approximating the Optimal Event-Based Sampling Policy

In networked control systems it is desirable to have efficient wireless communication (saving energy and bandwidth) while still ensuring good control performance. By abandoning periodic sampling, communication can be made more efficient by sampling and updating the control signal only "when required" based on the system’s behaviour. This is the concept of event-based control. In this work we consi

Challenges in high performance big data frameworks

Nowadays, we live in a society with billions of devices that are interconnected and interact together to improve the quality of our lives. The management and processing of information and knowledge have by now become our main resources, and the fundamental factors of economic and social development, and it is achieved through Big Data Frameworks (BDFs). The amount of such data is becoming larger e

Finite-size scaling analysis of protein droplet formation

The formation of biomolecular condensates inside cells often involve intrinsically disordered proteins (IDPs), and several of these IDPs are also capable of forming dropletlike dense assemblies on their own, through liquid-liquid phase separation. When modeling thermodynamic phase changes, it is well known that finite-size scaling analysis can be a valuable tool. However, to our knowledge, this ap

Investigating the role of the tibetan plateau in ENSO variability

The role of the Tibetan Plateau (TP) in El Niño-Southern Oscillation (ENSO) variability is investigated using coupled model experiments with different topography setups. Removing the TP results in weakened trade winds in the tropical Pacific, an eastward shift of atmospheric convection center, a shallower mixed layer in the equatorial Pacific, and a flattened equatorial thermocline, which leads to

EpilepsyGAN : Synthetic Epileptic Brain Activities with Privacy Preservation

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-threatening. Modern systems monitoring elec-troencephalography (EEG) signals are being currently developed with the view to detect epileptic seizur

A Micro-Simulation Study of the Generalized Proportional Allocation Traffic Signal Control

We study the problem of controlling phase activations for signalized junctions in an urban transportation network using local feedback information consisting of measures of the queue-lengths at the incoming lanes of each junction. Our focus is on the validation and performance evaluation through micro-simulations of the recently proposed Generalized Proportional Allocation (GPA) controller. Previo

Response of heterogeneous rainfall variability in East Asia to Hadley circulation reorganization during the late Quaternary

The Quaternary East Asian summer rainfall evolution reconstructed with the Chinese speleothem δ18O records shows the consistency throughout the region of East Asia, and has long been considered equivalent to the monsoon intensity. Its variation and teleconnection with global climate were usually interpreted by the meridional shift of the intertropical convergence zone (ITCZ). However, many other p

Numerical Pitfalls in Q-Design

Q-design is a powerful method for designing approximately optimal LTI controllers and assessing the achievable control performance. Unfortunately, numerical issues are often encountered in Q-design which limits its applicability. This paper warns about two numerical pitfalls in Q-design when using H 2 costs and Laguerre-type basis functions.

A Contoured-Beam Reflector Satellite Antenna Using Two Doubly Curved Circular Polarization Selective Surfaces

We present a reflector antenna system using a circular polarization selective surface (CPSS) to realize a circular polarization (CP) equivalent to the widely used linear polarization (LP) gridded or dual-gridded reflector (DGR). The CPSS is realized by a multilayer stack of non-resonant anisotropic meander line surfaces, achieving a very wide bandwidth. The CPSS reflection and transmission dyadics

Analysis and Design of a 17-GHz All-npn Push-Pull Class-C VCO

A push-pull oscillator topology that uses only one type of active device is proposed in this article. A magnetic transformer is leveraged to set positive feedback around a common-collector differential npn transistor pair, implementing the push-pull operation. This results in half the bias current for a given amplitude of oscillation, compared to more standard oscillator topologies. A thorough pha

Dual Control of Linear Discrete-Time Systems with Time-Varying Parameters

We describe how the optimal dual controller for a discrete-time linear system can be found by approximately solving the corresponding Bellman equation using a neural network to represent the value function. We illustrate the method on an example with time-varying dynamics, where the new method is shown to give improved performance.

Attitude Control on SU(2): Stability, Robustness, and Similarities

This paper concerns trajectory tracking control of attitude dynamics configured on SU(2). Inspired by a popular geometric tracking controller on SO(3), differential geometric tools are used to derive both continuous and discontinuous attitude controllers on the SU(2) manifold, relating these to preexisting controllers operating with imaginary quaternion errors. Additionally, a robustness result is

Exploiting linear substructure in linear regression Kalman filters

We exploit knowledge of linear substructure in the linear-regression Kalman filters (LRKFs) to simplify the problem of moment matching. The theoretical results yield quantifiable and significant computational speedups at no cost of estimation accuracy, assuming partially linear estimation models. The results apply to any symmetrical LRKF, and reductions in computational complexity are stated as a

Filtered output feedback tracking control of a quadrotor UAV

We present a tracking controller for quadrotor UAVs which uses partial state information and filters measurement noise. We show uniform almost global and locally exponential asymptotic stability of the resulting closed-loop system, which implies robustness against bounded disturbances. We illustrate the performance of the controller by means of several numerical examples, including a complex loopi

Coordination Control of Double-Integrator Systems with Time-Varying Weighted Inputs

This paper considers coordination control of double-integrator systems and proposes general control laws involving time-varying inputs. The nominal control input is weighted by time-varying (time-dependent or state-dependent) positive definite matrices, providing more freedoms in defining the control tasks. We present sufficient conditions to ensure the asymptotic convergence of double-integrator

Improving Performance of Feedback-Based Real-Time Networks using Model Checking and Reinforcement Learning

Traditionally, automatic control techniques arose due to need for automation in mechanical systems. These techniques rely on robust mathematical modelling of physical systems with the goal to drive their behaviour to desired set-points. Decades of research have successfully automated, optimized, and ensured safety of a wide variety of mechanical systems. Recent advancement in digital technology ha