Distributed LQR design for identical dynamically coupled systems: Application to load frequency control of multi-area power grid

The paper proposes a distributed LQR method for the solution to regulator problems of networks composed of dynamically dependent agents. It is assumed that these dynamical couplings among agents can be expressed in a state-space form of a certain structure. Following a top-down approach we approximate a centralized LQR optimal controller by a distributed scheme the stability of which is guaranteed via a stability test applied to convex combination of Hurwitz matrices. The method is applied to N-identical-area power grid where a distributed state-feedback Load Frequency Controller (LFC) is proposed to achieve frequency regulation under power demand variations. An illustrative numerical example demonstrates the applicability of the method

Distributed Model Predictive Load Frequency Control of multi-area Power Grid: A Decoupling Approach

A model-predictive scheme for load frequency control of a multi-area power system is proposed. The method depends on a decoupling technique which allows for a control design with a distributed architecture. Treating the total power inflows of each area as input variables, a decoupled linearized model for each area is derived. This allows for the formulation and solution of a model predictive control problem with a quadratic performance index and input saturating constraints on the individual tie-line power flows, along with an overall equality constraint to address the energy balance of the network. It is assumed that the interconnection topology (tie-lines) coincides with the communication topology of the network. The only information which needs to be shared between interconnected areas is the local frequency variables. The effectiveness of the method is illustrated via a simulation study of a three-area network. Future work will attempt to establish formally the stability of the control scheme and to enhance the versatility of the method by including constraints on the state variables

Strong stability of discrete-time systems

The paper introduces a new notion of stability for internal (state-space) autonomous system descriptions in discrete-time, referred to as strong stability which extends a parallel notion introduced in the continuous-time case. This is a stronger notion of stability compared to alternative definitions (asymptotic, Lyapunov), which prohibits systems described by natural coordinates to have overshooting responses for arbitrary initial conditions in state-space. Three finer notions of strong stability are introduced and necessary and sufficient conditions are established for each one of them. The class of discrete-time systems for which strong and asymptotic stability coincide is characterized and links between the skewness of the eigen-frame and the violation of strong stability property are obtained. Connections between the notions of strong stability in the continuous and discrete-domains are briefly discussed. Finally strong stabilization problems under state and output feedback are studied. The results of the paper are illustrated with a numerical example

Correction to: Two years later: Is the SARS-CoV-2 pandemic still having an impact on emergency surgery? An international cross-sectional survey among WSES members

Background: The SARS-CoV-2 pandemic is still ongoing and a major challenge for health care services worldwide. In the first WSES COVID-19 emergency surgery survey, a strong negative impact on emergency surgery (ES) had been described already early in the pandemic situation. However, the knowledge is limited about current effects of the pandemic on patient flow through emergency rooms, daily routine and decision making in ES as well as their changes over time during the last two pandemic years. This second WSES COVID-19 emergency surgery survey investigates the impact of the SARS-CoV-2 pandemic on ES during the course of the pandemic. Methods: A web survey had been distributed to medical specialists in ES during a four-week period from January 2022, investigating the impact of the pandemic on patients and septic diseases both requiring ES, structural problems due to the pandemic and time-to-intervention in ES routine. Results: 367 collaborators from 59 countries responded to the survey. The majority indicated that the pandemic still significantly impacts on treatment and outcome of surgical emergency patients (83.1% and 78.5%, respectively). As reasons, the collaborators reported decreased case load in ES (44.7%), but patients presenting with more prolonged and severe diseases, especially concerning perforated appendicitis (62.1%) and diverticulitis (57.5%). Otherwise, approximately 50% of the participants still observe a delay in time-to-intervention in ES compared with the situation before the pandemic. Relevant causes leading to enlarged time-to-intervention in ES during the pandemic are persistent problems with in-hospital logistics, lacks in medical staff as well as operating room and intensive care capacities during the pandemic. This leads not only to the need for triage or transferring of ES patients to other hospitals, reported by 64.0% and 48.8% of the collaborators, respectively, but also to paradigm shifts in treatment modalities to non-operative approaches reported by 67.3% of the participants, especially in uncomplicated appendicitis, cholecystitis and multiple-recurrent diverticulitis. Conclusions: The SARS-CoV-2 pandemic still significantly impacts on care and outcome of patients in ES. Well-known problems with in-hospital logistics are not sufficiently resolved by now; however, medical staff shortages and reduced capacities have been dramatically aggravated over last two pandemic years

A polyhedral approach to the stability analysis and feedback stabilization of networked control systems

In this note, the stability analysis and control design of Networked Control Systems (NCS) with bounded transmission delays, constant and unknown or time varying, is investigated using polyhedral Lyapunov functions. First, conditions guaranteeing stability are formulated for the equivalent augmented discrete-time system with structured uncertainties. Then, algebraic conditions leading to the computation of a linear state feedback controller for a NCS with bounded time varying delays are established. Both the stability analysis and synthesis problem are reduced to linear programming methods, a welcome consequence stemming from the choice of polyhedral Lyapunov functions

Computational Methods on Tall Buildings - the Bishopsgate Tower

This paper summarizes the ongoing research done on The Bishopsgate Tower in the City of London using parametric design methodologies. The process is indicative of how computational methods will develop in the future and help designers find solutions for increasingly complex spaces