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Item type:Publication, Access status: without files , Real-time optimization of load sharing for gas compressors in the presence of uncertainty(Elsevier, 2020-08-15); ; Mercangöz, MehmetThis paper investigates the problem of load-sharing optimization of gas compressors in the presence of uncertainty. The objective is to operate a set of compressor units in an energy-efficient way, while at the same time meeting a varying load demand. The main challenge is the fact that the available models, and in particular the compressor efficiency maps, carry a significant amount of uncertainty. For this task, real-time optimization (RTO) techniques that rely on plant measurements and correct the model are available in the literature. This paper is tailored to the application of RTO to the compressor load-sharing optimization problem. An adaptive optimization approach that guarantees optimal plant operation upon convergence is used. To this end, we use appropriate measurements to estimate plant gradients and correct the model in such a way that it exhibits the same optimality conditions as the plant. This way, the challenge is shifted from having an accurate model to being able to estimate experimental gradients accurately. We show how the specific problem structure can be exploited for the purpose of efficient estimation of plant gradients. We consider both parallel and serial compressor configurations as well as operation close to surge constraints. The simulation of an industrial case study demonstrates the efficiency of the proposed approach.Publicationtype: Journal Article13 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optimal load sharing for serial compressors via modifier adaptation(IEEE, 2018-11-27); Mercangöz, MehmetThis paper investigates the optimal load-sharing problem of serial gas compressors in the presence of plant- model mismatch. The problem is formulated as a static real- time optimization task that is solved via modifier adaptation for interconnected systems. The proposed approach guarantees optimal operation of the plant upon convergence. Furthermore, it is shown how the specific problem structure can be exploited during process operation for the efficient estimation of plant gradients with respect to local inputs. A simulated case study demonstrates the effectiveness of the proposed real-time optimization approach.Publicationtype: Conference Paper9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A distributed feasible-side convergent modifier-adaptation scheme for interconnected systems, with application to gas-compressor stations(Elsevier, 2018-07-12); Recently, a feasible-side globally convergent modifier-adaptation scheme has been proposed for the real-time optimization of uncertain systems. We show that this scheme is related to proximal-gradient algorithms in numerical optimization and we exploit this relationship to analyze its convergence in the case of inexact gradient information. We also make use of this relationship to propose a novel distributed modifier-adaptation algorithm for interconnected systems that uses a coordinator and knowledge of the interconnection topology. We then prove its feasible-side convergence to plant optimality. In addition, our distributed algorithm ensures confidentiality of local models and data. We finally demonstrate the applicability and effectiveness of this algorithm on a load-sharing optimization case study for serially connected gas compressors.Publicationtype: Journal Article8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Distributed modifier adaptation using a coordinator and measured interconnection variablesWe propose a distributed real-time optimization scheme for structurally uncertain systems consisting of multiple interconnected subsystems. In particular, we investigate a novel distributed variant of modifier adaptation that exploits a coordinator and knowledge of interconnection model. This way, each subsystem can compute its optimal inputs using only local information in terms of model, gradients and measurements. A coordinator ensures that the local optimal inputs computed by each subsystem are consistent with the interconnection model. In addition to ensuring confidentiality of local data, the scheme also guarantees plant optimality upon convergence. The analysis is illustrated via a simulation example.Publicationtype: Conference Paper4 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optimal load sharing of parallel compressors via modifier adaptation(IEEE, 2016); ; Mercangöz, MehmetWe discuss optimal load sharing of parallel gas compressors in the presence of plant-model mismatch. We formulate this problem as a static real-time optimization task and propose to tackle it by means of modifier adaptation. Under mild assumptions, the chosen approach guarantees optimal operating conditions upon convergence. Furthermore, we discuss how the specific problem structure can be exploited to estimate the plant gradients efficiently during process operation. Finally, we draw upon simulated case studies for two and six compressors to demonstrate the applicability and effectiveness of the proposed real-time optimization approach.Publicationtype: Conference Paper9 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Time-optimal path-following operation in the presence of uncertaintyPath-following tasks, which refer to dynamic motion planning along pre-specified geometric references, are frequently encountered in applications such as milling, robot-supported measurements, and trajectory planning for autonomous vehicles. Different convex and non-convex optimal control formulations have been proposed to tackle these problems for the case of perfect models. This paper analyzes path-following problems in the presence of plant-model mismatch. The proposed adaptation strategies rely on concepts that are well known in the field of real-time optimization. We present conditions guaranteeing that, upon convergence, a minimumtime solution is attained despite the presence of plant-model mismatch. We draw upon a simulated robotic example to illustrate our results.Publicationtype: Conference Paper6