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This article addresses the distributed cooperative control design for a class of sampled-data teleoperation systems with multiple slave mobile manipulators grasping an object in the presence of communication bandwidth limitation and time delays. Discrete-time information transmission with time-varying delays is assumed, and the Round-Robin (RR) scheduling protocol is used to regulate the data tran

Numerous modelling efforts have attempted to characterize the effects of different non-pharmaceutical interventions (NPIs) on the Covid-19 spread. Arguably the most famous is one published in Nature by an Imperial College group. A slight variation of it was later published in Science by a group of Oxford researchers. Both publications are based on hierarchical Bayesian modelling that aims to expla

A major challenge for a person with diabetes is to adapt insulin dosage regimens and food intake to keep blood glucose within tolerable limits during daily life activities. The accurate prediction of blood glucose levels in response to inputs would support the patients with invaluable information for appropriate on-the-spot decision making concerning the management of the disease. Against this bac

A 32 Kb dual-port low-voltage SRAM in 28 nm FD-SOI, featuring foundry supplied high-density 6T bitcells, is presented. Dual-port configurability is realized by a unique dual-rail architecture, utilizing boost techniques that guarantee reliable operation in low-voltage. The area cost of the array is 62% lower, compared to widely used 8T two-port or dual-port SRAM arrays. The SRAM reliably operates

ControlSystems.jl enables the powerful features of the Julia language to be leveraged for control design and analysis.The toolbox provides types for state-space, transfer-function, and time-delay models, together with algorithms for design and analysis.Julia's mathematically-oriented syntax is convenient for implementing control algorithms, and its just-in-time compilation gives performance on par

– Complexity of large-scale Airborne LIDAR data: its processing, and interpretation emerges the necessity of automated analysis with novel techniques.– Detection and documentation of archaeological ruins, hidden in the forests of the Swedish landscape.

In this paper we consider distributed adaptive stabilization for uncertain multivariable linear systems with a time-varying diagonal matrix gain. We show that uncertain multivariable linear systems are stabilizable by diagonal matrix high gains if the system matrix is an H-matrix with positive diagonal entries. Based on matrix measure and stability theory for diagonally dominant systems, we consid

Hydrological processes in a watershed consist of multiple sub-processes (such as plant growth, evapotranspiration, water yield, and soil–water balance) that have complex interactions. The common practice of calibrating hydrological models against only a single variable (e.g., streamflow) can lead to parameter uncertainty (also known as equifinality), resulting in significant uncertainties in the r

Recurrent neural networks (RNNs) are efficient for classification of sequential data such as speech and audio due to their high precision on tasks. However, power efficiency, the required memory capacity and bandwidth requirements make them less suitable for battery powered devices. In this work, we introduce FLoPAD-GRU: a system on a chip (SoC) for efficient processing of gated recurrent unit (GR

There is a large variability between individuals in the response to anesthetic drugs, that seriously limits the achievable performance of closed-loop controlled drug dosing. Full individualization of patient models based on early clinical response data has been suggested as a means to improve performance with maintained robustness (safety). We use estimation theoretic analysis and realization theo

This thesis deals with the general problem of controlling rigid-body systems through space, with a special focus on unmanned aerial vehicles (UAVs). Several promising UAV control algorithms have been developed over the past decades, enabling truly astounding feats of agility when combined with modern sensing technologies. However, these control algorithms typically come without global stability gu

Electromagnetic fields exist all around us. Through evolution, nature has developed tools to interact and use these fields, where our eyes are a spectacular example. Humans have a long history of developing structures and objects of their own to alter and interact with these fields. Today they are important cornerstones in society, with radiating devices such as cell phones, Wi-Fi routers, or car

We show that algebraic proofs are hard to find: Given an unsatisfiable CNF formula F, it is NP-hard to find a refutation of F in the Nullstellensatz, Polynomial Calculus, or Sherali-Adams proof systems in time polynomial in the size of the shortest such refutation. Our work extends, and gives a simplified proof of, the recent breakthrough of Atserias and Müller (JACM 2020) that established an anal

A novel multi-source data fusion method based on Bayesian inference (BIF) was proposed in this study to blend the advantages of in-situ observations and remote sensing estimations for obtaining accurate chlorophyll-a (Chla) concentration in Lake Taihu (China). Two error models (additive and multiplicative) were adopted to construct the likelihood function in BIF; the BIF method was also compared w

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

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

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

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

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.