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Unfair work distribution is common in project-based learning with teams of students. One contributing factor is that students are differently skilled developers. To mitigate the differences in a course with group work, we introduced mandatory programming lab sessions. The intervention did not affect the work distribution, showing that more is needed to balance the workload. Contrary to our goal, t
We characterize a class of systems for which the H-infinity optimal control problem can be simplified in a way that enables sparse solutions and efficient computation. For a subclass of the systems, an optimal controller can be explicitly expressed in terms of the matrices of the system's state-space representation. In many applications, the controller given by this formula, which is st
A novel method using the cloud to implement a variable horizon model predictive controller is presented. In case of sudden long delays and downtime, a graceful degradation is used. Robust, best effort strategies allow industrial grade use of the powerful, efficient, and quickly improving cloud ecosystems. The variable horizon strategy finds use in, for example, non-linear control problems, and the
A two-tier architecture for cloud-based MPC is presented consisting of a high rate MPC in the cloud and a low rate MPC on the local device. The system use the cloud MPC as the nominal controller but switches to local MPC in case of connectivity loss. The two MPCs are designed to be as similar to each other as possible except for the sampling rate. Different alternatives for when to execute the loc
In this contribution, a recently conducted measurement campaign for indoor millimeter-wave (mm-wave) propagation channels is introduced. A vector network analyzer (VNA)-based channel sounder was exploited to record the channel characteristics at the frequency band from 28-30 GHz. A virtual uniform circular array (UCA) with a radius of 0.25 m was formed using a rotator with 360 steps. Moreover, by
Software design in e-commerce can be improved with user data through controlled experiments (i.e. A/B tests) to better meet user needs. Machine learning-based algorithmic optimization techniques extends the approach to large number of variables to personalize software to different user needs. So far the optimization techniques has only been applied to optimize software of low complexity, such as c
Massive multiple-input multiple-out (MIMO) is vital in millimeter-wave (mmWave) bands to obtain large array gains. However, there are practical challenges, such as high hardware cost and power consumption in such systems. A promising solution to these problems is to adopt a hybrid beamforming architecture. This architecture has a much lower number of transceiver (TRx) chains than the total antenna
Context:: Software-intensive organizations’ rationale for sharing Open Source Software (OSS) may be driven by both idealistic, strategic and commercial objectives, and include both monetary as well as non-monetary benefits. To gain the potential benefits, an organization may need to consider what they share and how, while taking into account risks, costs and other complexities. Objective:: This st
In this paper, an adaptive design methodology for synthesizing a harmonic free N-path filter with reduced frequency folding is presented. System level analysis of proposed architecture shows that by adding a few extra paths with proper weights to a conventional N-path filter, several characteristics such as harmonic rejection, power reduction, foldback elimination and spectrum shaping can be achie
A multi-variable PI (proportional integrating) controller is proved to be optimal for an important class of control problems where performance is specified in terms of frequency weighted H-infinity norms. The problem class includes networked systems with a subsystem in each node and control action along each edge. For such systems, the optimal PI controller is decentralized in the sense that contr
This paper develops a novel framework for power system stability analysis, that allows for the decentralised design of inverter based controllers. The method requires that each individual inverter satisfies a standard H∞ design requirement. Critically each requirement depends only on the dynamics of the components and inverters at each individual bus, and the aggregate susceptance of the transmiss
Modeling of robot motion as dynamical movement primitives (DMPs) has becomean important framework within robot learning and control. The ability of DMPs to adapt online with respect to the surroundings, e.g., to moving targets, has been used and developed by several researchers. In this work, a method for handling perturbations during execution of DMPs on robots was developed. Two-degree-of-freedo
We show how to minimize the energy required to build up the electromagnetic field in radio-frequency cavities, which will allow power savings for pulsed particle accelerators. By formulating an optimal control problem for a first-order system we obtain a solution on state-feedback form. We numerically compare the optimal solution to previous approaches.
This paper presents an algorithm for Model Predictive Control of SISO systems. Based on a quadratic objective in addition to (hard) input constraints it features soft upper as well as lower constraints on the output and an input rate-of-change penalty term. It keeps the deterministic and stochastic model parts separate. The controller is designed based on the deterministic model, while the Kalman
The fast-increasing demand and relatively slow growth of infrastructure capacity are providing a strong motivation for research in real-time urban traffic controls that make the best use of novel sensing in order to increase efficiency and resilience of the transportation system. In our contribution, we focus on a class of dynamic feedback traffic signal control policies that are based on a genera
Relay autotuning has proven very successful for single-input single-output systems. This paper proposes an identification method for relay autotuning of systems with two inputs and two outputs (TITO systems). The combination of asymmetric relay feedback and output error identification admits short tuning time, without the need for limit cycle convergence. The method is successfully demonstrated on
Control and scheduling co-design becomes an issue when several controller tasks share the same execution platform and disrupt the ideal sampling and actuation patterns. In co-design the objective is to optimize the combined performance of all the controllers on the platform, subject to schedulability constraints. In the paper four LQG-based co-design methods are reviewed and evaluated: delay-aware
The paper presents conditions for the stability of a dynamical network described by a directed graph, whose nodes represent dynamical systems characterised by the same transfer function F(s) and whose edges account for the interactions between pairs of nodes. In turn, these interactions depend via a transference G(s) on the outputs of the subsystems associated with the connected nodes. The stabili
An adaptive uplink detection scheme for a Massive MIMO (MaMi) base station serving up to 16 users is presented. Considering user distribution in a cell, selective matched filtering (MF) is proposed for non-interference limited users and a Cholesky decomposition (CD) based zero-forcing (ZF) detector is implemented for the remaining users. Channel conditions such as coherence bandwidth are exploited
