Privacy Analysis of Decentralized Federated Learning

Privacy concerns in federated learning have attracted considerable attention recently. In centralized networks, it has been observed that even without directly exchanging raw training data, the exchange of other so-called intermediate parameters such as weights/gradients can still potentially reveal private information. However, there has been...

Distributed Particle Filtering

The recent advances in wireless communication, micro-fabrication, and integration have led to the rise of multi-agent networks such as wireless sensor networks, drone swarms, and satellite arrays. These multi-agent networks comprise multiple agents, which cooperate to solve a problem collectively, beyond the individual knowledge of a single...

Distributed Optimisation Using Stochastic PDMM: Convergence, transmission losses and privacy

In recent years, the large increase in connected devices and the data that is collected by these devices has caused a heightened interest in distributed processing. Many practical distributed networks are of heterogeneous nature. Because of this, algorithms operating within these networks need to be simple, robust against network dynamics and...

Nesterov Accelerated ADMM for Distributed Pose Graph Optimization in SLAM problems

A common problem in robotics is the simultaneous localization and mapping (SLAM) problem. Here, a robot needs to create a map of its surroundings while simultaneously localizing itself in this map. An unknown environment is assumed. Traditionally, it has been approached through filtering solutions. This paradigm has shifted to pose graph...

Distributed Coordination for Multi-fleet Truck Platooning

Truck platooning refers to coordinating a group of heavy-duty vehicles at a close inter-vehicle distance to reduce overall fuel consumption. This coordination between trucks is traditionally achieved by adjusting the schedule, velocity, and routines to increase the platooning chances, and thus improve the overall fuel efficiency. However, the...

Computational Strategies for Model Predictive Control on Switching Max-plus Linear Systems

A switching max-plus linear model is a framework to describe the discrete dynamics of the timing of events. To influence these systems one can choose the routes of jobs and the orderings of operations as input for the system. In this thesis the techniques of model predictive control are used to find good input values. The problem of finding the...

Distributed Collision Free Trajectory Optimization for the Reconfiguration of a Spacecraft Formation

In recent years there has been an increasing interest in formation flying with many lightweight spacecraft, as satellite missions can potentially become cheaper and more flexible. An example of such mission is the Silicon Wafer Integrated Femtosatellites mission, consisting of 100 to 1000 spacecraft with a mass of 0.1 kg. Due to modest control...

Inexact distributed optimization schemes: A convergence analysis using monotone operator theory

Distributed optimization has been an <br/>extensively studied field for years. Recent developments in the area of sensors makes it possible to create networks consisting of a large number of nodes. The focus of this thesis will be optimizing distributed problems over a decentralized network. These distributed optimization schemes operate in an...

Towards Decentralized Grids: EnergyBazaar: decentralized free-market energy-trade within an isolated community micro-grid

<br/>We witness the rise of prosumers: consumers that produce a surplus of energy that can be sup- plied back into the grid. However, for energy-trade between prosumers and consumers, a cen- tralized and undesirable middle-man is still necessary. We developed a method to decentralize essential aspects of energy distribution between households....

Distributed Approach for Aerodynamic Model Identification of the ICE Aircraft

High performance control allocation methods for the Innovative Control Effectors (ICE) aircraft require accurate onboard aerodynamic models, with preferably first order continuity. Simplotope B-Splines, an extension on Simplex B-Splines, have a high approximation power by using local basis functions. However, enforcing global continuity produces...

Distributed Optimization for Railway Track Maintenance Operations Planning

An essential component of railway infrastructures is track ballast. As railway track is used frequently by passing rolling stocks, its performance degrades over time. At certain degradation levels, maintenance interventions must be carried out to improve the track performance so to meet technical and safety regulations. In this way, the risk of...

Distributed optimal power flow in a dc distribution system: Step towards smarter energy management

Rise in distributed energy resources has prompted a shift in the way electricity market operators function. Traditionally, centralized optimization techniques are used by such operators to plan for economic dispatches of power tominimize the overall operational costs and increase system social welfare. Due to the dispersed nature of renewable...

Model Predictive Control Architecture Comparison for a Power Scheduling Electric Vehicle Aggregator

Energy flexibility is the ability to change power production or consumption over time. It is required for a power system to function properly, to balance supply and demand. Currently, the largest providers of energy flexibility in the Netherlands can be found on the supply side and consist mainly out of fossil fueled power plants. As these are...

Application of Finite Volume and Finite Element methods to distributed optimal control of semi-linear elliptic equations

In this paper we are concerned with distributed optimal control problems governed by a second-order linear and semi-linear elliptic partial differential equations (PDE), where the control is distributed on the domain ?. The semi-linear elliptic boundary value problem is analysed by proving the existence of a unique solution and optimal control...

Distributed Wavefront Reconstruction for Adaptive Optics Systems

We are currently facing an increasing amount of challenges in the area of photonics as more and more applications in need for active “photon control” sprout in different fields of science. Adaptive Optics (AO) is the subject which deals with measuring, reconstructing, and reshaping the phase of a photon wavefront in real-time and can, thus,...