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Application of ERA-Interim, empirical models, and an artificial intelligence-based model for estimating daily solar radiation

Solar radiation plays a pivotal role in the energy balance at the Earth's surface, evaporation, snow melting, water requirements of plants, and hydrological control of catchments. In this work, performance of ERA-Interim (a reanalysis dataset) was examined to estimate solar radiation at Ahvaz, BandarAbbas, and Kermanshah weather stations representing the even spatial distribution over Iran using e

Model optimization for autotuners in industrial control systems

Automatic tuning of PID controllers using relay feedback experiments has received attention on and off since it was first proposed and industrially implemented in a control system in the 1980s. While optimal experiment design and modern system identification easily outperform the original automatic tuner, they rely on computational resources that are not always available in industrial control syst

Towards a Holistic Controller: Reinforcement Learning for Data Center Control

The increased use of cloud and other large scale datacenter IT services and the associated power usage has put the spotlight on more energy-efficient datacenter management. In this paper, a simple model was developed to represent the heat rejection system and energy usage in a small DC setup. The model was then controlled by a reinforcement learning agent that handles both the load balancing of th

Next generation relay autotuners—analysis and implementation

In order to produce models for automatic controller tuning, this paper proposes a method that combines a short experiment with a novel scheme for approximating processes using low-order time-delayed models. The method produces models aimed to tune PI and PID controllers, but they could also be used for other model-dependent controllers like MPC. The proposed method has been evaluated in simulation

A Structured Optimal Controller With Feed-Forward for Transportation

We study an optimal control problem for a simple transportation model on a path graph. We give a closed form solution for the optimal controller, which can also account for planned disturbances using feed-forward. The optimal controller is highly structured, which allows the controller to be implemented using only local communication, conducted through two sweeps through the graph.

Identifiability issues in estimating the impact of interventions on Covid-19 spread

The Covid-19 pandemic has spawned numerous dynamic modeling attempts aimed at estimation, prediction, and ultimately control. The predictive power of these attempts has varied, and there remains a lack of consensus regarding the mechanisms of virus spread and the effectiveness of various non-pharmaceutical interventions that have been enforced regionally as well as nationally. Setting out in data

Improving streamflow simulation by combining hydrological process-driven and artificial intelligence-based models

Accurate and timely monitoring of streamflow and its variation is crucial for water resources management in watersheds. This study aimed at evaluating the performance of two process-driven conceptual rainfall-runoff models (HBV: Hydrologiska Byråns Vattenbalansavdelning, and NRECA: Non Recorded Catchment Areas) and seven hybrid models based on three artificial intelligence (AI) methods (adaptive n

Predictive Force-Centric Emergency Collision Avoidance

A controller for critical vehicle maneuvering is proposed that avoids obstacles and keeps the vehicle on the road while achieving heavy braking. It operates at the limit of friction and is structured in two main steps: a motion-planning step based on receding-horizon planning to obtain acceleration-vector references, and a low-level controller for following these acceleration references and transf

Dynamic Droop Control in Low-Inertia Power Systems

A widely embraced approach to mitigate the dynamic degradation in low-inertia power systems is to mimic generation response using grid-connected inverters to restore the stiffness of the grid. In this article, we seek to challenge this approach and advocate for a principled design based on a systematic analysis of the performance trade-offs of inverter-based frequency control. With this aim, we pe

A distributed time-lapse camera network to track vegetation phenology with high temporal detail and at varying scales

Near-surface remote sensing techniques are essential monitoring tools to provide spatial and temporal resolutions beyond the capabilities of orbital methods. This high level of detail is especially helpful to monitor specific plant communities and to accurately time the phenological stages of vegetation - which satellites can miss by days or weeks in frequently clouded areas such as the Arctic. In

Challenges of Adopting SAFe in the Banking Industry – A Study Two Years After Its Introduction

The Scaled Agile Framework (SAFe) is a framework for scaling agile methods in large organizations. We have found several experience reports and white papers describing SAFe adoptions in different banks, which indicates that SAFe is being used in the banking industry. However, there is a lack of academic publications on the topic, the banking industry is missing in the scientific reports analyzing

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

Tuning and Analysis of Geometric Tracking Controllers on SO(3)

This paper concerns the robustness of attitude controllers for dynamics configured on the SO(3) manifold and poses a set of bilinear matrix inequalities to find an optimal controller tuning with respect to (i) the ultimate bound of the error-state trajectories when perturbed by naturally arising disturbances, and (ii) the worst-case decay rate of the tracking errors. The presented optimization pro

Testing Self-Adaptive Software with Probabilistic Guarantees on Performance Metrics : Extended and Comparative Results

This paper discusses methods to test the performance of the adaptation layer in a self-adaptive system. The problem is notoriously hard, due to the high degree of uncertainty and variability inherent in an adaptive software application. In particular, providing any type of formal guarantee for this problem is extremely difficult. In this paper we propose the use of a rigorous probabilistic approac

Dynamic Management of Multiple Resources in Camera Surveillance Systems*

Distributed camera surveillance systems typically consist of multiple cameras that need to store some fraction of their video streams in a central storage node. The disk space of this node as well as the network between the cameras and this central node constitute shared resources. In the paper the disk space allocation as well as the network bandwidth reservation are solved using techniques norma

Real-Time EEG-Based Cognitive Workload Monitoring on Wearable Devices

Objective: Cognitive workload monitoring (CWM) can enhance human-machine interaction by supporting task execution assistance considering the operators cognitive state. Therefore, we propose a machine learning design methodology and a data processing strategy to enable CWM on resource-constrained wearable devices. Methods: Our CWM solution is built upon edge computing on a simple wearable system, w

Late Pleistocene and Holocene Afromontane vegetation and headwater wetland dynamics within the Eastern Mau Forest, Kenya

The Mau Forest Complex is Kenya's largest fragment of Afromontane forest, providing critical ecosystem services, and has been subject to intense land use changes since colonial times. It forms the upper catchment of rivers that drain into major drainage networks, thus supporting the livelihoods of millions of Kenyans and providing important wildlife areas. We present the results of a sedimentologi

Multiple-load wireless power transmission system through time-division multiplexed resonators

This paper presents a wireless power transmission system which is able to deliver power to multiple loads by making use of a time-division multiplexing technique. Similar loads are placed into the slots in a row, and two power transmitters, at the bottom and top, supply them with sufficient amount of power. This system operates in two phases; within one phase, the transmitters are in-phase, and th