808 resultados para Modal Logics. Paranormal Logics. Fuzzy Logics


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This report presents a new way of control engineering. Dc motor speed controlled by three controllers PID, pole placement and Fuzzy controller and discusses the advantages and disadvantages of each controller for different conditions under loaded and unloaded scenarios using software Matlab. The brushless series wound Dc motor is very popular in industrial application and control systems because of the high torque density, high efficiency and small size. First suitable equations are developed for DC motor. PID controller is developed and tuned in order to get faster step response. The simulation results of PID controller provide very good results and the controller is further tuned in order to decrease its overshoot error which is common in PID controllers. Further it is purposed that in industrial environment these controllers are better than others controllers as PID controllers are easy to tuned and cheap. Pole placement controller is the best example of control engineering. An addition of integrator reduced the noise disturbances in pole placement controller and this makes it a good choice for industrial applications. The fuzzy controller is introduce with a DC chopper to make the DC motor speed control smooth and almost no steady state error is observed. Another advantage is achieved in fuzzy controller that the simulations of three different controllers are compared and concluded from the results that Fuzzy controller outperforms to PID controller in terms of steady state error and smooth step response. While Pole placement controller have no comparison in terms of controls because designer can change the step response according to nature of control systems, so this controller provide wide range of control over a system. Poles location change the step response in a sense that if poles are near to origin then step response of motor is fast. Finally a GUI of these three controllers are developed which allow the user to select any controller and change its parameters according to the situation.

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A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

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This paper is a preliminary investigation into the application of the formal-logical theory of normative positions to the characterisation of normative-informational positions, pertaining to rules that are meant to regulate the supply of information. First, we present the proposed framework. Next, we identify the kinds of nuances and distinctions that can be articulated in such a logical framework. Finally, we show how such nuances can arise in specific regulations. Reference is made to Data Protection Law and Contract Law, among others. The proposed approach is articulated around two essential steps. The first involves identifying the set of possible interpretations that can be given to a particular norm. This is done by using formal methods. The second involves picking out one of these interpretations as the most likely one. This second step can be resolved only by using further information (e.g., the context or other parts of the regulation).

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