Interval model predictive control

6TH INTERNATIONAL WORKSHOP ON ALGORITHMS AND ARCHITECTURES FOR REAL TIME CONTROL (6) (6.2000.PALMA DE MALLORCA. ESPAÑA)Model Predictive Control is one of the most popular control strategy in the process industry. One of the reason for this success can be attributed to the fact that constraints and uncertainties can be handled. There are many techniques based on interval mathematics that are used in a wide range of applications. These interval techniques can mean an important contribution to Model Predictive Control giving algorithms to achieve global optimization and constraint satisfaction

Welfare assessment: correlations and integration between a Qualitative Behavioural Assessment and a clinical/health protocol applied in veal calves farms

This study is aimed at finding correlations and possible integration among Qualitative Behavioural Assessment (QBA) and a specific protocol of clinical/health evaluation. Both welfare assessment methods were based on direct animal observation and were applied in 24 Italian veal calves farms at 3 weeks (wks) of rearing. Principal component analysis (PCA) summarized 20 QBA descriptors on two main components (PC1 and PC2) with eigenvalues above 4 and explaining 29.6 and 20.3% of the variation respectively. PCA on residuals obtained after correcting for housing condition yielded highly similar results, indicating that the rearing environment of the calves was not an important determinant of the observer reliability of QBA. A relationship was found between QBA PC2 and the presence of signs of cross-sucking recorded during the clinical visit (presence PC2=1.11 vs. absence PC2=-1.55,

The extraction of nuclear sea quark distribution and energy loss effect in Drell-Yan experiment

The next-to-leading order and leading order analysis are performed on the differential cross section ratio from Drell-Yan process. It is found that the effect of next-to-leading order corrections can be negligible on the differential cross section ratios as a function of the quark momentum fraction in the beam proton and the target nuclei for the current Fermilab and future lower beam proton energy. The nuclear Drell-Yan reaction is an ideal tool to study the energy loss of the fast quark moving through cold nuclei. In the leading order analysis, the theoretical results with quark energy loss are in good agreement with the Fermilab E866 experimental data on the Drell-Yan differential cross section ratios as a function of the momentum fraction of the target parton. It is shown that the quark energy loss effect has significant impact on the Drell-Yan differential cross section ratios. The nuclear Drell-Yan experiment at current Fermilab and future lower energy proton beam can not provide us with more information on the nuclear sea quark distribution.Comment: 17 pages, 4 figure

The role of the agent's outside options in principal-agent relationships

We consider a principal-agent model of adverse selection where, in order to trade with the principal, the agent must undertake a relationship-specific investment which affects his outside option to trade, i.e. the payoff that he can obtain by trading with an alternative principal. This creates a distinction between the agent’s ex ante (before investment) and ex post (after investment) outside options to trade. We investigate the consequences of this distinction, and show that whenever an agent’s ex ante and ex post outside options differ, this may equip the principal with an additional tool for screening among different agent types, by randomizing over the probability with which trade occurs once the agent has undertaken the investment. In turn, this may enhance the efficiency of the optimal second-best contract

Modeling and control strategies for a variable reluctance direct-drive motor

A high-performance ripple-free dynamic torque controller for a variable-reluctance (VR) motor intended for trajectory tracking in robotic applications is designed. A modeling approach that simplifies the design of the controller is investigated. Model structure and parameter estimation techniques are presented. Different approaches to the overall torque controller design problem are discussed, and the solution adopted is illustrated. A cascade controller structure consisting of a feedforward nonlinear torque compensator, cascaded to a nonlinear flux or current closed-loop controller is considered, and optimization techniques are used for its design. Although developed for a specific commercial motor, the proposed modeling and optimization strategies can be used for other VR motors with magnetically decoupled phases, both rotating and linear. Laboratory experiments for model validation and preliminary simulation results of the overall torque control system are presente

Application of Raman Microspectroscopic and Raman imaging techniques for cell biological studies

Raman spectroscopy is being used to study biological molecules for some three decades now. Thanks to continuing advances in instrumentation more and more applications have become feasible in which molecules are studied in situ, and this has enabled Raman spectroscopy to enter the realms of biomedicine and cell biology [1-5].\ud Here we will describe some of the recent work carried out in our laboratory, concerning studies of human white blood cells and further instrumentational developments

A prototype controller for variable reluctance motors

A three-level cascade structure is proposed for the control of a variable reluctance (VR) motor. In order to deal with the highly nonlinear behavior of VR motors, the controlling system includes two variable-structure controllers for current and velocity loops as well as an intermediate torque-sharing compensator. The intermediate compensator has been designed by means of nonlinear optimization techniques in order to reduce the torque ripple and to get the maximum motor velocity. The proposed controller has been validated through extensive simulation experiments. The architecture of a prototype controller is presented and the actual performance measured on a VR motor is discussed in comparison with simulations. The results show practical feasibility and good performance of the proposed controller, which is also suitable for a very simple and quite inexpensive fully hardware implementatio

Diagnosability of Fuzzy Discrete Event Systems

In order to more effectively cope with the real-world problems of vagueness, {\it fuzzy discrete event systems} (FDESs) were proposed recently, and the supervisory control theory of FDESs was developed. In view of the importance of failure diagnosis, in this paper, we present an approach of the failure diagnosis in the framework of FDESs. More specifically: (1) We formalize the definition of diagnosability for FDESs, in which the observable set and failure set of events are {\it fuzzy}, that is, each event has certain degree to be observable and unobservable, and, also, each event may possess different possibility of failure occurring. (2) Through the construction of observability-based diagnosers of FDESs, we investigate its some basic properties. In particular, we present a necessary and sufficient condition for diagnosability of FDESs. (3) Some examples serving to illuminate the applications of the diagnosability of FDESs are described. To conclude, some related issues are raised for further consideration.Comment: 14 pages; revisions have been mad