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The IEEE Control Systems Society (CSS) Technical Committee on Networks and Communication Systems (TC-NCS) focuses on areas that involve the interplay among networks, communication, and systems control. The TC is organized into eight working groups, Control of Network Systems, Information Networks and Control, Networked Sensing and Sensor Networks, Optimization and Game Theoretic Methods in Network
The IEEE Control Systems Society (CSS) Technical Committee on Networks and Communication Systems (TC-NCS) focuses on areas that involve the interplay between networks, communication, and systems control. TCNCS currently has 47 members and is organized into eight working groups. These are Control of Network Systems, Networked Sensing and Sensor Networks, Optimization and Game-Theoretic Methods in N
A bond wire to microstrip line transition, featuring two impedance transformers, is presented for a mm-wave microstrip antenna and power amplifier (PA) integration using conventional bond wires. Simulated return loss bandwidth for the transition is 4 GHz with a minimum insertion loss of 1 dB. Measurement results for the designed active antenna are compared with measurements for a passive antenna a
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.
This thesis treats the intersection between two of the largest transformations we are seeing within our society today; the cloud and the Internet-of-Things (IoT). The aim of this thesis is to investigate different ways to model and control a network of cloud services so that timing-critical IoT applications can make use of them. Examples of such applications can be autonomous and mobile robots,
Modeling is fundamental to both feed-forward and feedback control. Within automated anesthesia the two paradigms are usually referred to as target-controlled infusion (TCI) and closed-loop drug delivery, respectively. In both cases, the objective is to control a system with anesthetic drug infusion rate as input, and (measured) clinical effect as output. The input is related to the output through
Self-adaptation provides a principled way to deal with software systems' uncertainty during operation. Examples of such uncertainties are disturbances in the environment, variations in sensor readings, and changes in user requirements. As more systems with strict goals require self-adaptation, the need for formal guarantees in self-adaptive systems is becoming a high-priority concern. Designing se
A neural-network-based adaptive control scheme is developed for bilateral teleoperation systems with single-master-multiple-slaves in the presence of dynamic uncertainties and communication constraint. Discrete-time data transmitting communication network with bandwidth limitation and time-varying communication delays is considered and the Round-Robin scheduling protocol is used to orchestrate the
It is proved that network realizability of controllers can be enforced without conservatism using convex constraints on the closed loop transfer function. Once a network realizable closed loop transfer matrix has been found, a corresponding controller can be implemented using a network structured version of Internal Model Control.
Atomic norms occur frequently in data science and engineering problems such as matrix completion, sparse linear regression, system identification and many more. These norms are often used to convexify non-convex optimization problems, which are convex apart from the solution lying in a non-convex set of so-called atoms. For the convex part being a linear constraint, the ability of several atomic n
We propose an efficient algorithm, that given a strictly proper, second-order system, finds a sparse input signal so that the system's output optimally approximates a given trajectory in least-squares sense. As an illustration, we apply the algorithm to an estimation problem from medicine.
A numerical method based on radial basis functions (RBF) has been developed to find the optimal event-based sampling policy in an LQG problem setting. The optimal sampling problem can be posed as a stationary partial differential equation with a free boundary, which is solved by reformulatingthe optimal RBF approximation as a linear complementarity problem (LCP). The LCP can be efficiently solved
We present a novel predictive control scheme for linear constrained systems that uses the alternating direction method of multipliers (ADMM) for online optimization. In contrast to existing works on ADMM-based model predictive control (MPC), we only consider a single ADMM-iteration in every time step. The resulting real-time ADMM scheme is tailored for embedded and fast MPC implementations. The ma
BACKGROUND: The gut microbiome is an important determinant of human health. Its composition has been shown to be influenced by multiple environmental factors and likely by host genetic variation. In the framework of the Milieu Intérieur Consortium, a total of 1000 healthy individuals of western European ancestry, with a 1:1 sex ratio and evenly stratified across five decades of life (age 20-69), w
Operation and maintenance (O&M) is highly important to fight unplanned downtime, which is a costly consequence of the increasing automation enabled by digitalization. We will discuss O&M to enable seamless exchange of information in a hierarchical multi-vendor system, while ensuring individual vendors controlling what know-how to share.
Providing information security is crucial for the Internet of Things (IoT) devices, platforms in which the available power budget is very limited. This paper tackles this challenge and presents a cryptographic processor compliant with the security algorithms specified by the 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) NarrowBand IoT (NB-IoT) standard. The proposed processor
High-energy linear particle accelerators enable exploration of the microscopic structure of pharmaceuticals, solar cells, fuel cells, high-temperature superconductors, and the universe itself. These accelerators accelerate charged particles using oscillating magnetic fields that are confined in metal cavities. The amplitudes and phases of the electromagnetic fields need to be accurately controlled
The proliferation of connected embedded devices, or the Internet of Things (IoT), together with recent advances in machine intelligence, will change the profile of future cloud services and introduce a variety of new research problems centered around empowering resource-limited edge devices to exhibit intelligent behavior, both in sensing and control. Cloud services will enable learning from data,
