The application of advanced control techniques to drug-induced unconsciousness and muscle relaxation in operating theaters is described. A brief survey of other simple control applications to anesthesia is given, and ...
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The application of advanced control techniques to drug-induced unconsciousness and muscle relaxation in operating theaters is described. A brief survey of other simple control applications to anesthesia is given, and the use of generalized predictive control and fuzzy logic control for muscle relaxation are discussed. Various attempts have been made to control unconsciousness automatically, but an expert system advisory approach based on data fusion for clinical signs and online monitoring is emphasized. Extensions of both adaptive and intelligent control techniques for multivariable anesthesia are described.< >
An extension to the Morison equation including Duffing oscillator-type force terms is postulated through knowledge of the flow mechanisms. This is used to curve-fit measured force time-histories from velocity time-his...
An extension to the Morison equation including Duffing oscillator-type force terms is postulated through knowledge of the flow mechanisms. This is used to curve-fit measured force time-histories from velocity time-histories, generated experimentally from various sources: regular oscillatory flow in a U-tube, cylinder oscillation in still water and in a current, random waves in the large De Voorst wave flume and a directional sea state at the Christchurch Bay Tower. The curve fits from the Morison equation are sometimes poor, while the curve fits from the extended equation are always excellent, although the corresponding 'predictions' give little or no improvement on the Morison equation. The curve fits obtained by simply adding a term proportional to F\F\, where F is force, are also significant improvements over the Morison fits enabling an improved classification of force in terms of drag, inertia and history (for each flow situation). In unidirectional flows the association of a significant history term with vortex shedding is confirmed by the occurrence of a prominent transverse or lift force. In directional seas, lift (due to vortex shedding) cannot be isolated and it is suggested that the data analysis described here will indicate the significance of vortex shedding through the relative magnitude of the history term.
The accurate modelling of robot dynamics is essential for the design of model-based robot controllers. However, dynamic models have very complicated features which can be attributed to several reasons. For example, th...
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The accurate modelling of robot dynamics is essential for the design of model-based robot controllers. However, dynamic models have very complicated features which can be attributed to several reasons. For example, the continuously-varying arm configuration, uncertain effects of load handling on the dynamic stability of the arm, and the high degree of non-linearity and coupling exhibited between the different links. Hence, the accurate modelling of these effects will play an important role in the design of robust controllers. Towards this end, an efficient and fast method for the on-line tuning of robot dynamic parameters must be devised. This work proposes to solve this problem as follows. First, a simplified dynamic model of the robot is developed. The model allows for direct and straightforward extraction and regrouping of dynamic parameters. The resulting dynamic parameters are formulated as a regression equation which is linear in the dynamic parameters. Finally, the algorithm is executed using a Transputer development system to speed up the computation and meet real-time constraints. The efficiency of the approach is demonstrated by a case study.
A new approach for identifying continuous time models from discrete time sampled-data records is presented. The proposed method involves estimating and validating a discrete time model, linear or non-linear, based on ...
A new approach for identifying continuous time models from discrete time sampled-data records is presented. The proposed method involves estimating and validating a discrete time model, linear or non-linear, based on sampled data records, evaluating the discrete time linear and non-linear frequency response functions and then curve fitting to the frequency response data to yield a continuous time model. No numerical differentiation and integration is involved and hence higher derivatives of input and output data records are avoided. Errors which would be introduced by the numerical approximation of differentiation and integration are therefore eliminated. The orthogonal estimator which is introduced to curve fit to the complex frequency response functions provides information on the model structure and the unknown parameter values for linear and non-linear continuous time models. The advantage of this approach is that non-linear differential equation models which can be related to the physical behaviour of the system can be readily computed from discrete time data.
Viewing the given rule-base as defining a global linguistic association constrained by fuzzy sets, approximate reasoning is implemented here by a Backpropagation Neural Network (BNN) with the aid of the fuzzy ste theo...
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This paper proposes an algorithm for Self-Organising Fuzzy Modelling(SOFM) which models the system by learning rules from input and output data, even although the rule set is empty at the beginning. The concept of tun...
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An intelligent robot has the ability to accomplish its specific task in the presence of uncertainty and variability in its environment and to adjust its actions based on what it has sensed. An artificial neural networ...
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This paper describes how fuzzy patterns captured by tactile sensing of hardness features of a coal seam can be processed and used for the steering of rockcutting mining machines in geological environments. A method of...
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Supervisory control has been applied to many cases in control industry. It consists of monitoring the process and the controller for maintaining the system in the best operating conditions. In this paper a knowledge-b...
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Supervisory control has been applied to many cases in control industry. It consists of monitoring the process and the controller for maintaining the system in the best operating conditions. In this paper a knowledge-based supervisory control system is built as a multi-level structure which is used for controlling and monitoring industrial processes. The system is applied to a real-time liquid level rig which highlights the system specifications as a supervisory controller.
Supervisory control has been applied to many cases in control industry. It consists of monitoring the process and the controller for maintaining the system in the best operating conditions. In this paper a knowledge-b...
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Supervisory control has been applied to many cases in control industry. It consists of monitoring the process and the controller for maintaining the system in the best operating conditions. In this paper a knowledge-based supervisory control system is built as a multi-level structure which is used for controlling and monitoring industrial processes. The system is applied to a real-time liquid level rig which highlights the system specifications as a supervisory controller.
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