期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
Recursive Fuzzy Predictions of Future Patient Paths to Support Clinical Decision Making in ICU
1
作者 A. Zeghbib M. Mahfouf +4 位作者 J. J. Ross G. H. Mills G. G. Panoutsos M. Denai S. Suzani 《Engineering(科研)》 2013年第10期584-589,共6页
In this paper, we propose a new architecture that combines prediction and decision-making in the form of a hybrid framework aimed at providing clinicians with transparent and accurate maps, or charts, to guide and to ... In this paper, we propose a new architecture that combines prediction and decision-making in the form of a hybrid framework aimed at providing clinicians with transparent and accurate maps, or charts, to guide and to support treatment decisions, and to interrogate the clinical patients’ course as it develops. These maps should be patient-specific, with options displayed of possible treatment pathways. They would suggest the optimal care pathways, and the shortest routes to the most efficient care, by predicting clinical progress, testing the ensuing suggestions against the developing clinical state and patient condition, and suggesting new options as necessary. These maps should also mine an extensive database of accumulated patient data, modelled diseases, and modelled patient-responses based on expert-derived rules. These individualized hierarchical targets, which are implemented in order to prevent life-threatening illnesses, will also have to “adapt” to the patient’s altering clinical condition. Therapies that support one system can destabilize others and selecting which specific support to prioritize is an uncertain process, the prioritization of which can vary between clinical experts. Whilst clinical therapeutic decisions can be made with some degree of anticipation of the “likely” outcome (based on the experts’ opinion and judgment), treatment is essentially rooted in the present, and is dependent on analyzing the current clinical condition and available data. The recursive learning approach presented in this paper, allows decision rules to predict the possible future course, and reflects back derived information from such projections to the present time and thus support proactive clinical care rather than reactive clinical care. The proposed framework for such a patient map supports and enables an optimized choice from available options and also ensures that decisions are based on both the available evidence and a database of best clinical practice. Preliminary results are encouraging and it is hoped to validate the approach clinically in the near future. 展开更多
关键词 PROACTIVE Treatment Clinical Decision Intensive-Care Patient-Paths PHYSIOLOGICAL Map
下载PDF
Nonlinear optimal control of rotating flexible shaft in active magnetic bearings 被引量:6
2
作者 G. S. TOMBUL S. P. BANKS 《Science China(Technological Sciences)》 SCIE EI CAS 2011年第5期1084-1094,共11页
The optimal control of nonlinear systems has been studied for years by many researchers. However, the application of optimal control problem to nonlinear non-affine systems needs more attention. In this paper we propo... The optimal control of nonlinear systems has been studied for years by many researchers. However, the application of optimal control problem to nonlinear non-affine systems needs more attention. In this paper we propose an optimal control design technique for a class of nonlinear and control non-affine equations. The dynamic equations of a flexible shaft supported by a pair of active magnetic bearings (AMBs) are used as the nonlinear control non-affine equations. Mathematical model for the flexible beam is chosen to be the well known Timoshenko beam model, which takes rotary inertia and shear deformations into account, and it is assumed that the shaft is supported by two frictionless bearings at the ends. The effective control of such systems is extremely important for very high angular velocity shafts which are a feature of many modern machines. The control must be able to cope with unbalanced masses and hence be very robust. We shall approach the problem by discretising the Timoshenko beam model and using standard difference formulae to develop a finite-dimensional model of the system. Then we use a recently developed technique for controlling nonlinear systems by reducing the problem to a sequence of linear time-varying (LTV) systems. An optimal control designed for each approximating linear, time-varying system and recent results show that this method will converge uniformly on compact time intervals to the optimal solution. 展开更多
关键词 approximation technique nonlinear optimal control timoshenko beam active magnetic bearings
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部