Self-Optimizing Steady-State Back-Off Approach for Control Structure Selection

The selection of suitable control structures has an important influence on the economic performance of process systems in the presence of disturbances. Economics has been incorporated in the control structure selection problem using different formulations based on different criteria. The back-off approach is based on the idea of minimizing the economic loss that results from the need to back off from the active constraints to avoid violating them in the presence of disturbances. On the other hand, self-optimizing control schemes aim at selecting controlled variables and constant setpoint values, such that the economic loss with respect to optimal operation is minimized in the presence of disturbances. This paper presents a comprehensive study of different formulations of the back-off approach that pays attention to steady-state feasibility in the presence of disturbances. We argue that the back-off approach that selects controlled variables and optimal setpoint values by minimizing the average cost in the presence of disturbances is a global self-optimizing control approach. The performance of the different formulations is compared by means of three different case studies.Fil: Bottari, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Marchetti, Pablo Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Marchetti, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentin

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Real-time optimization modifier adaptation approach using quadratic approximation of the plant-model mismatch function

The present work proposes a real-time optimization modifier adaptation scheme (RTO MA) in which the modifiers are obtained through a quadratic approximation of the plant-model mismatch function. The work also highlights the links between the model used in the trust-region framework, the model used in bias, gradient, and Hessian-based RTO MA schemes, and the model used in function-based RTO MA. In line with this, general conditions are established for the adapted nominal model for use on the basic trust-region algorithm. The proposed modifiers are then incorporated into an iterative algorithm of the real-time modifier adaptation scheme complemented with a trust-region framework. The effectiveness of the approach is demonstrated in simulation for the optimization of a continuous stirred tank reactor.Fil: Bottari, Agustin. Pontificia Universidad Católica Argentina "Santa María de los Buenos Aires"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Optimal Control Structure Selection Based on Economics for Continuous Cross-Flow Grain Dryer

In this work, we present the control structure selection problem based on steady-state economics applied to a continuous cross-flow grain dryer model. The optimal selection of the controlled and manipulated variables and their set-points can be obtained for various external disturbance scenarios if an appropriate mathematical programming problem is formulated. Simulation results show that the economics performance of classical open loop and closed loop structure used for dryer control can be improved by the use of linear combination of controlled variables and also by the use of a hierarchical control structure. In addition, we study several alternatives (sub-optimal) control structures that show an acceptable economic performance.Fil: Bottari, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Pontificia Universidad Católica Argentina "Santa María de los Buenos Aires"; ArgentinaFil: Braccia, Lautaro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentin

Economic Control Structure Selection for Two-Layered Real-Time Optimization Systems

In industrial chemical plants, the selection of controlled variables, manipulated variables, and setpoint values directly impacts the economics of plant operation. The economic operation of a controlled plant can be improved using measurements to optimize the setpoint values and/or change the control structure online. These corrective actions are typically implemented by a supervisory setpoint control layer, such as a real-time optimization system. In a recent work, the authors studied the steady-state back-off approach for control structure selection that selects the optimal control structure and setpoint values by minimizing the average economic cost while guaranteeing feasibility in the presence of disturbances. In the present paper, we extend the aforementioned back-off approach by considering the presence of an upper real-time optimization layer. We present formulations for control structure selection that consider changes in the setpoint values as a function of measured (or estimated) disturbances and changes to the control structure when the set of active constraints changes. The usefulness of the proposed formulations is demonstrated in simulation on a linear example, an evaporator process, and a reaction-distillation plant with recycle.Fil: Bottari, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Zumoffen, David Alejandro Ramon. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: Marchetti, Alejandro Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; Argentin