Without a cure, vaccine, or proven long-term immunity against SARS-CoV-2, test-trace-and-isolate (TTI) strategies present a promising tool to contain its spread. For any TTI strategy, however, mitigation is challenged by pre- and asymptomatic transmission, TTI-avoiders, and undetected spreaders, which strongly contribute to ”hidden" infection chains. Here, we study a semi-analytical model and identify two tipping points between controlled and uncontrolled spread: (1) the behavior-driven reproduction number $${R}_{t}^{H}$$ R t H of the hidden chains becomes too large to be compensated by the TTI capabilities, and (2) the number of new infections exceeds the tracing capacity. Both trigger a self-accelerating spread. We investigate how these tipping points depend on challenges like limited cooperation, missing contacts, and imperfect isolation. Our results suggest that TTI alone is insufficient to contain an otherwise unhindered spread of SARS-CoV-2, implying that complementary measures like social distancing and improved hygiene remain necessary.
This paper presents the robust control of Three-Leg Split-Capacitor Shunt Active Power Filters (TLSC SAPFs) by means of structured H∞ controllers for reactive, unbalanced, and harmonic compensation and the DC-link bus voltage regulation. Robust controller synthesis is performed based on the TLSC SAPF dynamical model including power losses in passive elements. Before the control implementation, a systematic procedure for the nonlinear controllability verification of the converter and its quantification using the set-theoretic approach is presented. Controllability verification serves to accurately design the SAPF’s operation region. Thus, a Voltage Oriented Control (VOC) structure is implemented by using two different approaches to determine the PI controller parameters: (1) the traditional Pole-Placement method (PP-PI) and (2) the H∞-PI structured synthesis approach, which leads to PI robust controllers. From the latter approach, two sets of parameters are obtained. The first set considers the nominal model (H∞-PI), and the second one explicitly accounts for the model parametric uncertainties (H∞-uPI). An optimization procedure is presented for obtaining the optimal H∞-PI and H∞-uPI controller parameters where four complementary constrains are defined to establish a trade-off between the controllers performance and robustness. The enforcement of constraints is later evaluated for each of three PI controllers obtained. This work aims to establish a common ground for the comparison of robust control strategies applied to TLSC APFs; therefore, the TLSC SAPF compensation performance is measured and compared with the performance indices: integral of the absolute error (IAE), integral of the time-weighted absolute error (ITAE), integral of the absolute control action (IUA), and maximum sensitivity (Ms).
In this chapter, it is demonstrated that when using advanced evolutionary algorithms, whatever the adopted system model (SOSPD, nonminimum phase, oscillatory or nonlinear), it is possible to find optimal parameters for PID controllers satisfying simultaneously the behavior of the system and a performance index such as absolute integral error (IAE). The Multidynamics Algorithm for Global Optimization (MAGO) is used to solve the control problem with PID controllers. MAGO is an evolutionary algorithm without parameters, with statistical operators, and for the optimization, it does not need the derivatives, what makes it very effective for complex engineering problems. A selection of some representative benchmark systems is carried out, and the respectively twodegree-of-freedom (2DoF) PID controllers are tuned. A power electronic converter is adopted as a case study and based on its nonlinear dynamical model, a PI controller is tuned. In all cases, the control problem is formulated as a constrained optimization problem and solved using MAGO. The results found are outstanding.
This chapter presents a procedure to design and control power electronic converters (PECs), which includes a zero-based analysis as a dynamical system response criterion for dimensioning converter passive elements. For this purpose, a nonideal boost DC-DC converter (converter considering its parasitic losses) is dynamically modeled and analyzed in steady state as an application example. The steady-state model is obtained from the average nonlinear model. The steady-state model allows deducing expressions for equilibrium conversion ratio MD ðÞ and efficiency η of the system. Conditions for the converter conduction modes are analyzed. Simulations are made to see how parasitic losses affect both MD ðÞ and η. Then, inductor current and capacitor voltage ripple analyses are carried out to find lower boundaries for inductor and capacitor values. The values of the boost DC-DC converter passive elements are selected taking into account both steady-state and zero-based analyses. A nonideal boost DC-DC converter and a PI-based current mode control (CMC) structure are designed to validate the proposed procedure. Finally, the boost DC-DC converter is implemented in PSIM and system operating requirements are satisfactorily verified.
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