Computational analysis of real-time convex optimization for control systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2000.Includes bibliographical references (p. 177-189).Computational analysis is fundamental for certification of all real-time control software. Nevertheless, analysis of on-line optimization for control has received little attention to date. On-line software must pass rigorous standards in reliability, requiring that any embedded optimization algorithm possess predictable behavior and bounded run-time guarantees. This thesis examines the problem of certifying control systems which utilize real-time optimization. A general convex programming framework is used, to which primal-dual path-following algorithms are applied. The set of all optimization problem instances which may arise in an on-line procedure is characterized as a compact parametric set of convex programming problems. A method is given for checking the feasibility and well-posedness of this compact set of problems, providing certification that every problem instance has a solution and can be solved in finite time. The thesis then proposes several algorithm initialization methods, considering the fixed and time-varying constraint cases separately. Computational bounds are provided for both cases. In the event that the computational requirements cannot be met, several alternatives to on-line optimization are suggested. Of course, these alternatives must provide feasible solutions with minimal real-time computational overhead. Beyond this requirement, these methods approximate the optimal solution as well as possible. The methods explored include robust table look-up, functional approximation of the solution set, and ellipsoidal approximation of the constraint set. The final part of this thesis examines the coupled behavior of a receding horizon control scheme for constrained linear systems and real-time optimization. The driving requirement is to maintain closed-loop stability, feasibility and well-posedness of the optimal control problem, and bounded iterations for the optimization algorithm. A detailed analysis provides sufficient conditions for meeting these requirements. A realistic example of a small autonomous air vehicle is furnished, showing how a receding horizon control law using real-time optimization can be certified.by Lawrence Kent McGovern.Ph.D

A constrained optimization approach to control with application to flexible structures

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1996.Includes bibliographical references (leaves 101-102).by Lawrence Kent McGovern.M.S

Mission, Organization, and Future Direction of the Serological Sciences Network for COVID-19 (SeroNet) Epidemiologic Cohort Studies.

BackgroundGlobal efforts are needed to elucidate the epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the underlying cause of coronavirus disease 2019 (COVID-19), including seroprevalence, risk factors, and long-term sequelae, as well as immune responses after vaccination across populations and the social dimensions of prevention and treatment strategies.MethodsIn the United States, the National Cancer Institute in partnership with the National Institute of Allergy and Infectious Diseases, established the SARS-CoV-2 Serological Sciences Network (SeroNet) as the nation's largest coordinated effort to study coronavirus disease 2019. The network comprises multidisciplinary researchers bridging gaps and fostering collaborations among immunologists, epidemiologists, virologists, clinicians and clinical laboratories, social and behavioral scientists, policymakers, data scientists, and community members. In total, 49 institutions form the SeroNet consortium to study individuals with cancer, autoimmune disease, inflammatory bowel diseases, cardiovascular diseases, human immunodeficiency virus, transplant recipients, as well as otherwise healthy pregnant women, children, college students, and high-risk occupational workers (including healthcare workers and first responders).ResultsSeveral studies focus on underrepresented populations, including ethnic minorities and rural communities. To support integrative data analyses across SeroNet studies, efforts are underway to define common data elements for standardized serology measurements, cellular and molecular assays, self-reported data, treatment, and clinical outcomes.ConclusionsIn this paper, we discuss the overarching framework for SeroNet epidemiology studies, critical research questions under investigation, and data accessibility for the worldwide scientific community. Lessons learned will help inform preparedness and responsiveness to future emerging diseases

Postoperative continuous positive airway pressure to prevent pneumonia, re-intubation, and death after major abdominal surgery (PRISM): a multicentre, open-label, randomised, phase 3 trial

Background: Respiratory complications are an important cause of postoperative morbidity. We aimed to investigate whether continuous positive airway pressure (CPAP) administered immediately after major abdominal surgery could prevent postoperative morbidity. Methods: PRISM was an open-label, randomised, phase 3 trial done at 70 hospitals across six countries. Patients aged 50 years or older who were undergoing elective major open abdominal surgery were randomly assigned (1:1) to receive CPAP within 4 h of the end of surgery or usual postoperative care. Patients were randomly assigned using a computer-generated minimisation algorithm with inbuilt concealment. The primary outcome was a composite of pneumonia, endotracheal re-intubation, or death within 30 days after randomisation, assessed in the intention-to-treat population. Safety was assessed in all patients who received CPAP. The trial is registered with the ISRCTN registry, ISRCTN56012545. Findings: Between Feb 8, 2016, and Nov 11, 2019, 4806 patients were randomly assigned (2405 to the CPAP group and 2401 to the usual care group), of whom 4793 were included in the primary analysis (2396 in the CPAP group and 2397 in the usual care group). 195 (8\ub71%) of 2396 patients in the CPAP group and 197 (8\ub72%) of 2397 patients in the usual care group met the composite primary outcome (adjusted odds ratio 1\ub701 [95% CI 0\ub781-1\ub724]; p=0\ub795). 200 (8\ub79%) of 2241 patients in the CPAP group had adverse events. The most common adverse events were claustrophobia (78 [3\ub75%] of 2241 patients), oronasal dryness (43 [1\ub79%]), excessive air leak (36 [1\ub76%]), vomiting (26 [1\ub72%]), and pain (24 [1\ub71%]). There were two serious adverse events: one patient had significant hearing loss and one patient had obstruction of their venous catheter caused by a CPAP hood, which resulted in transient haemodynamic instability. Interpretation: In this large clinical effectiveness trial, CPAP did not reduce the incidence of pneumonia, endotracheal re-intubation, or death after major abdominal surgery. Although CPAP has an important role in the treatment of respiratory failure after surgery, routine use of prophylactic post-operative CPAP is not recommended