Structured Singular Valued based robust nonlinear model predictive controller using Volterra series models

A methodology is proposed for designing a robust nonlinear model predictive controller based on a Volterra series model with uncertain coefficients. A key benefit of using the Volterra series model is that it can be split into a nominal and an uncertainty model thus permitting the application of robust analysis tools. The controller is based on the on-line solution of a robust performance test based on a Structured Singular Value norm. The cost function of the controller can be formulated to account for manipulated variable movement weighting, manipulated variable constraints and a terminal condition. Finally, the proposed methodology is applied to a single-input–single-output continuous stirred tank reactor problem and to a multiple-input–multiple-output pH neutralization process.     

Modeling Massive RFID Data Sets: A Gateway-Based Movement Graph Approach

Massive Radio Frequency Identification (RFID) data sets are expected to become commonplace in supply chain management systems. Warehousing and mining this data is an essential problem with great potential benefits for inventory management, object tracking, and product procurement processes. Since RFID tags can be used to identify each individual item, enormous amounts of location-tracking data are generated. With such data, object movements can be modeled by movement graphs, where nodes correspond to locations and edges record the history of item transitions between locations. In this study, we develop a movement graph model as a compact representation of RFID data sets. Since spatiotemporal as well as item information can be associated with the objects in such a model, the movement graph can be huge, complex, and multidimensional in nature. We show that such a graph can be better organized around gateway nodes, which serve as bridges connecting different regions of the movement graph. A graph-based object movement cube can be constructed by merging and collapsing nodes and edges according to an application-oriented topological structure. Moreover, we propose an efficient cubing algorithm that performs simultaneous aggregation of both spatiotemporal and item dimensions on a partitioned movement graph, guided by such a topological structure.     

On some properties of quasi-MV algebras and \sqrt{^{\prime}} quasi-MV algebras. Part II

The present paper is a sequel to Paoli F, Ledda A, Giuntini R, Freytes H (On some properties of QMV algebras and QMV algebras, submitted). We provide two representation results for quasi-MV algebras in terms of MV algebras enriched with additional structure; we investigate the lattices of subvarieties and subquasivarieties of quasi-MV algebras; we show that quasi-MV algebras, as well as cartesian and flat quasi-MV algebras, have the amalgamation property.     

Goal Change in the Situation Calculus

Although there has been much discussion of belief change (e.g.[4, 21]), goal change has not received much attention. In thispaper, we propose a method for goal change in the frameworkof Reiter's; [12] theory of action in the situation calculus[8, 10], and investigate its properties. We extend the frameworkdeveloped by Shapiro et al. [17] and Shapiro and Lespérance[16], where goals and goal expansion were modelled, but goalcontraction was not.     

Existence and uniqueness of minimal realizations of nonlinear systems

In the theory of finite dimensional linear systems, it is well known that every input-output map that can be realized by one such system can also be realized by a system which is minimal, i.e. both controllable and observable. Moreover, the minimal realization of a given map is unique up to isomorphism. It is shown here that similar results hold for the class of all systems whose state space is a real analytic manifold, whose dynamics is given by a family of complete real analytic vector fields, and whose output is an arbitrary real analytic function on the state space.Research partially supported by NSF Grant GP-37488.     

Structural optimization of non-linear systems under stochastic excitation

This work concentrates on the structural optimization of a class of non-linear systems with deterministic structural parameters subject to stochastic excitation. The optimization problem is formulated as the minimization of an objective function subject to constraints on the response level. The stochastic response is characterized by its first two statistical moments, which are computed by a statistical equivalent linearization technique. The implicit structural optimization problem is replaced by a sequence of explicit sub-optimization problems. The sub-problems are constructed by using a conservative first-order approximation of the objective and constraint functions. The applicability of the proposed design process is demonstrated in three numerical examples where the methodology is applied to systems with nonlinearity of hardening and hysteretic type. The effects of the nonlinearity on the general performance of the final designs are discussed. At the same time, some engineering implications of the results obtained in this work are addressed.     

Effect of cellulosic sugar degradation products (furfural and hydroxymethyl furfural) on acetone–butanol–ethanol (ABE) fermentation using Clostridium beijerinckii P260

Studies were performed to identify chemical compounds present in wheat straw hydrolysate (WSH) that enhance acetone butanol ethanol (ABE) productivity. These compounds were identified as furfural and hydroxymethyl furfural (HMF). Control experiment resulted in the production of 21.38 g L^?1 ABE with a productivity of 0.30 g L^?1 h^?1. WSH contained 0.04–0.34 g L^?1 furfural and 0.12–0.88 g L^?1 HMF. Addition of furfural to the fermentation medium at a concentration of 0.50 g L^?1 resulted in a productivity of 0.88 g L^?1 h^?1 which is 293% of the productivity obtained in control experiments. Supplementation with 1.00 g L^?1 HMF into the fermentation medium produced 25.27 g L^?1 ABE with a productivity of 0.68 g L^?1 h^?1. A combination of furfural (0.50 g L^?1) and HMF (0.50 g L^?1) also enhanced ABE production and productivity when added to the fermentation medium. Both furfural and HMF enhanced specific productivity (233–308%) of ABE. In brief, WSH contained an adequate concentration of furfural and HMF that enhanced ABE productivity, specific productivity, and product concentration.     

A socio-technical approach to post-occupancy evaluation: interactive adaptability in domestic retrofit

Understanding the process of domestic retrofit is important for learning and innovation. This is particularly the case for low carbon retrofits such as those undertaken under the UK's Retrofit for the Future (RftF) programme, with its aim to achieve an overall 80% carbon reduction by 2050. Current post-occupancy evaluation (POE) research has both theoretical and methodological limitations with implications for technical and behavioural research in the built environment. Drawing on relevant ideas and concepts from social practice theory and science and technology studies, principally prefiguration (constraints/enablement), black-boxing, heating and cooling practices, this paper demonstrates how the relationship between buildings and people could be reconceptualized as mutually constitutive and co-evolving through a process of ‘interactive adaptation’. The concept of ‘interactive adaptation’ is explored through a novel approach to integrating physical and social data collected from a sample of dwellings selected from the RftF programme. Analysis yields insights into the influences and pathways of interactive adaptation resulting from retrofit technology and practices. The implications of these insights for policy-makers, the research community and practitioners are discussed: end-use energy demand policy needs to be informed by a socio-technical approach.     

Comparison of the performance of a reduced-order dynamic PLS soft sensor with different updating schemes for digester control

In this work, the previously developed reduced-order dynamic PLS (RO-DPLS) soft sensor is extended to its adaptive version to address frequent process changes in a pulp digester. The properties of four model update schemes and the corresponding data scaling methods are investigated through one simulated case study and two industrial case studies of Kamyr digesters. Our findings obtained through extensive experiments are presented, which are expected to provide useful information and some guidance to practitioners. Finally, the effectiveness of the recursive RO-DPLS soft sensor is demonstrated through a digester closed-loop control case study, which shows that the closed-loop control performance can be significantly improved if the soft sensor prediction is fed back to a PID controller.