6,934 research outputs found

    Circle grid fractal plate as a turbulent generator for premixed flame: an overview

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    This review paper focuses to ascertain a new approach in turbulence generation on the structure of premixed flames and external combustion using a fractal grid pattern. This review paper discusses the relationship between fractal pattern and turbulence flow. Many researchers have explored the fractal pattern as a new concept of turbulence generators, but researchers rarely study fractal turbulence generators on the structure premixed flame. The turbulent flow field characteristics have been studied tand investigated in a premixed combustion application. In terms of turbulence intensity, most researchers used fractal grid that can be tailored so that they can design the characteristic needed in premixed flame. This approach makes it extremely difficult to determine the exact turbulent burning velocity on the velocity fluctuation of the flow. The decision to carry out additional research on the effect circle grid fractal plate as a turbulent generator for premixed flame should depends on the blockage ratio and fractal pattern of the grid. 1

    Fuzzy robust nonlinear control approach for electro-hydraulic flight motion simulator

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    AbstractA fuzzy robust nonlinear controller for hydraulic rotary actuators in flight motion simulators is proposed. Compared with other three-order models of hydraulic rotary actuators, the proposed controller based on first-order nonlinear model is more easily applied in practice, whose control law is relatively simple. It not only does not need high-order derivative of desired command, but also does not require the feedback signals of velocity, acceleration and jerk of hydraulic rotary actuators. Another advantage is that it does not rely on any information of friction, inertia force and external disturbing force/torque, which are always difficult to resolve in flight motion simulators. Due to the special composite vane seals of rectangular cross-section and goalpost shape used in hydraulic rotary actuators, the leakage model is more complicated than that of traditional linear hydraulic cylinders. Adaptive multi-input single-output (MISO) fuzzy compensators are introduced to estimate nonlinear uncertain functions about leakage and bulk modulus. Meanwhile, the decomposition of the uncertainties is used to reduce the total number of fuzzy rules. Different from other adaptive fuzzy compensators, a discontinuous projection mapping is employed to guarantee the estimation process to be bounded. Furthermore, with a sufficient number of fuzzy rules, the controller theoretically can guarantee asymptotic tracking performance in the presence of the above uncertainties, which is very important for high-accuracy tracking control of flight motion simulators. Comparative experimental results demonstrate the effectiveness of the proposed algorithm, which can guarantee transient performance and better final accurate tracking in the presence of uncertain nonlinearities and parametric uncertainties

    A distributed networked approach for fault detection of large-scale systems

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    Networked systems present some key new challenges in the development of fault diagnosis architectures. This paper proposes a novel distributed networked fault detection methodology for large-scale interconnected systems. The proposed formulation incorporates a synchronization methodology with a filtering approach in order to reduce the effect of measurement noise and time delays on the fault detection performance. The proposed approach allows the monitoring of multi-rate systems, where asynchronous and delayed measurements are available. This is achieved through the development of a virtual sensor scheme with a model-based re-synchronization algorithm and a delay compensation strategy for distributed fault diagnostic units. The monitoring architecture exploits an adaptive approximator with learning capabilities for handling uncertainties in the interconnection dynamics. A consensus-based estimator with timevarying weights is introduced, for improving fault detectability in the case of variables shared among more than one subsystem. Furthermore, time-varying threshold functions are designed to prevent false-positive alarms. Analytical fault detectability sufficient conditions are derived and extensive simulation results are presented to illustrate the effectiveness of the distributed fault detection technique

    A practical implementation of Robust Evolving Cloud-based Controller with normalized data space for heat-exchanger plant

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    The RECCo control algorithm, presented in this article, is based on the fuzzy rule-based (FRB) system named ANYA which has non-parametric antecedent part. It starts with zero fuzzy rules (clouds) in the rule base and evolves its structure while performing the control of the plant. For the consequent part of RECCo PID-type controller is used and the parameters are adapted in an online manner. The RECCo does not require any off-line training or any type of model of the controlled process (e.g. differential equations). Moreover, in this article we propose a normalization of the cloud (data) space and an improved adaptation law of the controller. Due to the normalization some of the evolving parameters can be fixed while the new adaptation law improves the performance of the controller in the starting phase of the process control. To assess the performance of the RECCo algorithm, firstly a comparison study with classical PID controller was performed on a model of a plate heat-exchanger (PHE). Tuning the PID parameters was done using three different techniques (Ziegler–Nichols, Cohen–Coon and pole placement). Furthermore, a practical implementation of the RECCo controller for a real PHE plant is presented. The PHE system has nonlinear static characteristic and a time delay. Additionally, the real sensor's and actuator's limitations represent a serious problem from the control point of view. Besides this, the RECCo control algorithm autonomously learns and evolves the structure and adapts its parameters in an online unsupervised manner

    Analysis of adaptation law of the robust evolving cloud-based controller

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    In this paper we propose a performance analysis of the robust evolving cloud-based controller (RECCo) according to the different initial scenarios. RECCo is a controller based on fuzzy rule-based (FRB) systems with non-parametric antecedent part and PID type consequent part. Moreover, the controller structure (the fuzzy rules and the membership function) is created in online manner from the data stream. The advantage of the RECCo controller is that do not require any a priory knowledge of the controlled system. The algorithm starts with zero fuzzy rules (zero data clouds) and evolves/learns during the process control. Also the PID parameters of the controller are initialed with zeros and are adapted in online manner. According to the zero initialization of the parameters the new adaptation law is proposed in this article to solve the problems in the starting phase of the process control. Several initial scenarios were theoretically propagated and experimentally tested on the model of a heat-exchanger plant. These experiments prove that the proposed adaptation law improve the performance of the RECCo control algorithm in the starting phase

    The strengthening of Islamic values on students through the metaphor of accepting death: an Indonesian perception

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    Death is a sure entity for every human that cannot be avoided in human life. The purpose of this research was to reveal that the usage of metaphor technique called, “The Acceptance of Death” in group counselling can improve Islamic values on Muslim students. This study employed an action research using The Kemmis Model with the stages of planning, action, observation, and reflection. This research implemented group counselling with metaphor technique of accepting death by students. The research subjects were 20 female students of State Islamic University of Sultan Syarif Kasim Riau who lived in the campus dormitory. The selection of the research subjects was done randomly by choosing the female students who were willing to join the group counselling activity. The research results showed that the practice of metaphor technique of “The Acceptance of Death” in the group counselling can strengthen the Islamic values and their characteristics as Muslims. They understand their previous mistakes and are willing to be better for the sake of their life. They have the commitment to become the best students and the best Muslims

    Integral MRAC with Minimal Controller Synthesis and bounded adaptive gains: The continuous-time case

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    Model reference adaptive controllers designed via the Minimal Control Synthesis (MCS) approach are a viable solution to control plants affected by parameter uncertainty, unmodelled dynamics, and disturbances. Despite its effectiveness to impose the required reference dynamics, an apparent drift of the adaptive gains, which can eventually lead to closed-loop instability or alter tracking performance, may occasionally be induced by external disturbances. This problem has been recently addressed for this class of adaptive algorithms in the discrete-time case and for square-integrable perturbations by using a parameter projection strategy [1]. In this paper we tackle systematically this issue for MCS continuous-time adaptive systems with integral action by enhancing the adaptive mechanism not only with a parameter projection method, but also embedding a s-modification strategy. The former is used to preserve convergence to zero of the tracking error when the disturbance is bounded and L2, while the latter guarantees global uniform ultimate boundedness under continuous L8 disturbances. In both cases, the proposed control schemes ensure boundedness of all the closed-loop signals. The strategies are numerically validated by considering systems subject to different kinds of disturbances. In addition, an electrical power circuit is used to show the applicability of the algorithms to engineering problems requiring a precise tracking of a reference profile over a long time range despite disturbances, unmodelled dynamics, and parameter uncertainty.Postprint (author's final draft
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