Application of a method to diagnose the source of performance degradation in MPC systems

Model Predictive Control systems may suffer from performance degradation mainly for two reasons: (i) external unmeasured disturbances are not estimated correctly, (ii) the (linear) dynamic model used by the MPC does not match (any longer) the actual process response. In this work we present the application of a method to detect when performance is not optimal, to diagnose the source of performance degradation and to propose appropriate corrections. In the simplest situation (i), optimal performance can be restored by recomputing the estimator parameters; in the other case (ii), re-identification becomes necessary. The method is based on analysis of the prediction error, i.e. the difference between the actual measured output and the corresponding model prediction, and uses three main tools: a statistical (whiteness) test on the prediction error sequence, a subspace identification method to detect the order of the input-to-prediction error system, and a nonlinear optimization algorithm to recompute optimal estimator parameters. We illustrate the effectiveness of the method on a large-scale rigorously simulated industrial process. Copyright © 2013, AIDIC Servizi S.r.l

MPC performance monitoring of a rigorously simulated industrial process

We address in this paper the application of a recently proposed MPC performance monitoring method to a rigorously simulated industrial process. The methodology aims at detecting possible sources of suboptimal performance of linear offset-free MPC algorithms by analysis of the prediction error sequence, discriminating between the presence of plant/model mismatch and incorrect disturbance/state estimation, and proposing for each scenario an appropriate corrective action. We focus on the applicability of the method to large-scale industrial systems, which typically comprise a block structure, devising efficient and scalable diagnosis and correction procedures. We also discuss and support the application of this method when the controlled plant shows a mild nonlinear behavior mainly associated with operating point changes. A high-fidelity dynamic simulation model of a crude distillation unit was developed in UniSim® Design and used as representative test bench. Results show the efficacy of the method and indicate possible research directions for further improvements. © IFAC

Analogies between Internal Model Control and Predictive Control algorithms

Internal Model Control (IMC) is a well-known control strategy provided with simple tuning rules requiring a model in order to control a given single-input single-output plant; furthermore, it allows an easy and straightforward closed-loop analysis. However, it has some limitations. For instance, it cannot be applied to open-loop unstable plants, it does not cope easily with constraints, and disturbance rejection may be sluggish for disturbances other than output steps. On the other hand, Model Predictive Control (MPC), that still requires the definition of a model, has not limitation from the point of view of the nature of the plant, but it does not give allows simple CL analysis. IMC and MPC have many common features but, at the same time, they are also quite different control strategies: the goal we want to achieve in this work is to find a compromise between them that should have advantages of both control structures. In this work a Disturbance Observer Based Internal Model Control (DOB-IMC) is proposed: it works with an augmented model, classical IMC controller design is left unchanged, while the block standing for the model has been replaced by an observer block, where predicted states are ”filtered” through a Luenberger observer, known to deal better with dynamic disturbances rather than classic IMC deadbeat observer. Afterwards, this structure has been extended to open-loop unstable plants through application of the Q parametrization, and to integrating plants as well. The effectiveness of this control scheme has been validated through several simulations: first, different kind of Single-Input Single-Output linear systems have been tested; then, as a pratical application, the multivariable ”Shell oil fractionator” case study has been simulated with unmeasured disturbance and with saturated inputs

Disturbance models for offset-free nonlinear predictive control

Offset-free model predictive control refers to a class of control algorithms able to track asymptotically constant reference signals despite the presence of unmeasured, nonzero mean disturbances acting on the process and/or plant model mismatch. Generally, in these formulations the nominal model of the plant is augmented with integrating disturbances, i.e. with a properly designed disturbance model, and state and disturbance are estimated from output measurements. To date the vast majority of offset-free MPC applications are based on linear models, however, since process dynamics are generally inherently nonlinear, these may perform poorly or even fail in some situations. Better results can be achieved by making use of nonlinear formulations and hence of nonlinear model predictive control (NMPC) technology. However, the obstacles associated with implementing NMPC frameworks are nontrivial. In this work the offset-free tracking problem with nonlinear models is addressed. Firstly some basic concepts related to the observability of nonlinear systems and state estimation are reviewed, focusing on the digital filtering and putting a strong accent on the role of the disturbance model. Thus, a class of disturbance models in which the integrated term is added to model parameters is presented together with an efficient and practical strategy for its design and subsequent implementation in offset-free NMPC frameworks

Aeronautical engineering: A continuing bibliography with indexes (supplement 240)

This bibliography lists 629 reports, articles, and other documents introduced into the NASA scientific and technical information system in May, 1989. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Eco-efficiency Performance Comparison of Additive and Subtractive Manufactured Parts

This thesis aims to develop a decision support tool for the manufacturing industry, which has been achieved through the 'techno-eco-efficiency' framework. The framework provides a comprehensive assessment of additive and subtractive manufactured parts by integrating technical feasibility assessment, environmental life cycle assessment, life cycle costing, and eco-efficiency assessment. The framework has been implemented on virgin polymer composite and metal parts. Additionally, the social impacts and the eco-efficiency improvement strategy of material recycling has been explored

In vitro pro-apoptotic and anti-migratory effects of Marantodes pumilum (Blume) Kuntze and Ficus deltoidea L. extracts on prostate cancer cell lines

This thesis evaluates the in vitro pro-apoptotic and anti-migratory effects of Marantodes pumilum Blume Kuntze and Ficus deltoidea L. plants on prostate cancer cells, characterising both their mechanism of actions on some of the main Hallmarks of Cancer, and their chemistry with a view to contribute to future chemopreventive strategies. Plant materials of M. pumilum (MP) F. deltoidea var. angustifolia (FD1) and F. deltoidea var. deltoidea (FD2) were obtained from dedicated farms in Southern Malaysia. The crude methanolic extract was partitioned into n-hexane (MPh, FD1h, FD2h) chloroform (MPc, FD1c, FD2c) and aqueous extracts (MPa, FD1a, FD2a). Active fractions (GI50<30 μg/mL) based on prostate cancer cell line, PC3, Sulforhodamine B staining were further fractionated. Active compound/s were identified using spectroscopic methods. In vitro mechanistic studies on PC3 cells were conducted to investigate the mode of death of PC3 cells and effects of the active extracts on PC3 cells migration and invasion. MPc, FD1c and FD2c extracts induced cell death via apoptosis as evidenced by nuclear DNA fragmentation, accompanied by a significant increase in MMP depolarization (P<0.05), activation of caspases 3 and 7 (MPc P<0.01; FD1c and FD2c P<0.05) in both PC3 and LNCaP cell lines. All active plant extracts up-regulated Bax and Smac/DIABLO and down-regulated Bcl-2 (P<0.05). Only MPc inhibited the expression of ALOX-5 mRNA gene expression (P<0.001). None resulted cytotoxic against normal human fibroblast cells (HDFa) at the tested concentrations. All active plant extracts inhibited both migration and invasion of PC3 cells (MPc; P<0.01, FD1c and FD2c; P<0.05), achieved by down-regulation of both VEGF and CXCL-12 gene expressions (P<0.001). A monounsaturated 5-alkyl resorcinol was isolated as the active compound present in the MPc extract. LC-MS dereplication identified isovitexin in FD1c; and oleanolic acid, moretenol, betulin, lupenone and lupeol in FD2c. In conclusion, evidence gathered in this study suggests a role for interaction of MPc, FD1c and FD2c in three of the Hallmarks of Cancer in PC3 cells: (1) apoptosis by activating of the intrinsic pathway, (2) inhibition of both migration and invasion by modulating the CXCL12-CXCR4 axis, and (3) inhibiting angiogenesis by modulating VEGF-A expression. The compounds identified and dereplicated in this study will be further characterized and used for the standardization of the active extracts in the future

MEGAPORT COMPETITIVENESS AND SUSTAINABILITY PRACTICE IN CONTAINER SHIPPING LOGISTICS IN NORTHEAST ASIA

Amidst intense port competition in Northeast Asia, competitiveness in port operations is a critical issue in adopting and implementing sustainability practice that incorporate economic, environmental, social and operational perspectives. Notwithstanding the importance of sustainability practice for sustainable port operations, very few studies have investigated its links with operational sustainability and competitiveness. For this reason, in order to encourage the proactive adoption and implementation of sustainability practice in port operations, this study aims to analyse the role of sustainability practice in managing competitiveness and continuous improvements in operational performance, based on mega container ports operations. To address this issue, this study adopted a two-phase research design which incorporates a preliminary field study and empirical research. At first, to understand the specific and general features of sustainability practice in commercial port operations, preliminary field work through semi-structured face-to-face interviews were undertaken. Interviews validated the attributes of sustainability practice in the container port operational context, investigating the relevant issues. Thereafter, based on data collected from 203 organisations engaged in container port operations in Northeast Asia, the feasible relationships among sustainability practice, competitiveness and performance were analysed using hierarchical moderator regression analysis in SPSS 21. Finally, the results revealed that sustainability practice has a significant contribution as a moderator to the relationship between competitiveness, particularly in operational efficiency and service quality, and operational performance. The two-phase research design made it possible to define and validate the role of sustainability practice in managing the relationship between competitiveness and performance. With regard to theory, this study has placed the case of Northeast Asia in a global context. Secondly, the direct relationships between determinants of megaport competitiveness and performance in the context of container port operations were verified. Thirdly, the specific routes, what is achievable and how sustainability practice contributes to enhancing the relationships between determinants of megaport competitiveness and operational performance, were revealed in a container port operational context. For the ports industries, this study has provided useful insights to establish strategies for sustainable port operations and a strategic agenda to assist ports to incorporate sustainability practice, providing evidence that this will contribute to enhancing their overall competitiveness. The findings are expected to be utilised further in future studies on sustainable port development and operations, as well as to provide guidance for port operators in its future improvement strategy