The free surface movement of liquids during transportation stages is a critical hindrance faced across numerous precision industrial process engineering sectors. Uncontrolled liquid oscillations lead to equipment inst...
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The free surface movement of liquids during transportation stages is a critical hindrance faced across numerous precision industrial process engineering sectors. Uncontrolled liquid oscillations lead to equipment instability, spillage losses, and complications in meeting stringent quality control demands. This research presents the design, modeling, and experimental validation of a fuzzylogiccontrol-based sloshing suppression system for precision fluid transport mechanisms. The developed platform uses a belt drive system actuated by a PMDC motor to transport a container filled with liquid over a 1-m linear path. A fuzzycontroller in a closed feedback loop is implemented for system stabilization. The liquid is represented by an equivalent mechanical pendulum model. Comparative Simulink simulations against conventional PID control demonstrate the superiority of the fuzzy technique for reducing destabilizing slosh by up to 20%. Experimental testing utilizes high-speed flow visualization to analyze liquid dynamics under real-time motion profiles. Results exhibit robust sloshing mitigation for the fuzzy system across disturbance scenarios and varieties of liquids. This investigation successfully proves the concept of a fuzzy slosh controller for industrial liquid transport tasks requiring precision motion quality. The system provides critical industrial value by enhancing operation stability, improving spillage losses, and meeting stringent production demands reliant on smooth fluid conveyance.
This paper proposes a fuzzy logic control algorithm (FLCA) to stabilize the Rossler chaotic dynamical system. The fuzzylogiccontrol system is based on a Takagi-Sugeno-Kang inference engine and the stability analysis...
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This paper proposes a fuzzy logic control algorithm (FLCA) to stabilize the Rossler chaotic dynamical system. The fuzzylogiccontrol system is based on a Takagi-Sugeno-Kang inference engine and the stability analysis in the sense of Lyapunov is carried out using Lyapunov's direct method. The new FLCA is formulated to offer sufficient inequality stability conditions. The asymptotic complexity of our algorithm is analyzed and proved to be lower in comparison with that of linear matrix inequality-based FLCAs. A set of simulation results illustrates the effectiveness of the proposed FLCA.
The design analysis of a multi-input converter using an intelligent controller based on fuzzy logic control algorithm is encompassed. The use of dedicated dc-dc converters is going through a transitory phase in smart-...
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The design analysis of a multi-input converter using an intelligent controller based on fuzzy logic control algorithm is encompassed. The use of dedicated dc-dc converters is going through a transitory phase in smart-grid applications. Different characteristics of inputs can be combined to give desired output operation by using a multi-input converter which is more or less the combination of individual converters sharing a common load thus simultaneously transferring power to the load. The converter with the help of an intelligent algorithm will ensure the buffering time for each input thus multiplexing between various inputs according to the set demand and fluctuating conditions on the input side. Such a converter will behave as a power electronic interface between the utility, user and the renewable energy sources. A three-input cuk converter has been designed for interfacing wind energy sources with the dc load bus and the main grid. Sending power to the main grid incorporates the power quality enhancement features which will be accommodated using the bi-directional inverter connected with the grid to perform the active filtration. Moreover, three fuzzylogiccontrollers will set the output currents corresponding to each input current by changing their reference voltages according to the power demand.
This study presents an adaptive perturb and observe (P&O)-fuzzycontrol maximum power point tracking (MPPT) for photovoltaic (PV) boost dc-dc converter. P&O is known as a very simple MPPT algorithm and used wi...
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This study presents an adaptive perturb and observe (P&O)-fuzzycontrol maximum power point tracking (MPPT) for photovoltaic (PV) boost dc-dc converter. P&O is known as a very simple MPPT algorithm and used widely. fuzzylogic is also simple to be developed and provides fast response. The proposed technique combines both of their advantages. It should improve MPPT performance especially with existing of noise. For evaluation and comparison analysis, conventional P&O and fuzzy logic control algorithms have been developed too. All the algorithms were simulated in MATLAB-Simulink, respectively, together with PV module of Kyocera KD210GH-2PU connected to PV boost dc-dc converter. For hardware implementation, the proposed adaptive P&O-fuzzycontrol MPPT was programmed in TMS320F28335 digital signal processing board. The other two conventional MPPT methods were also programmed for comparison purpose. Performance assessment covers overshoot, time response, maximum power ratio, oscillation and stability as described further in this study. From the results and analysis, the adaptive P&O-fuzzycontrol MPPT shows the best performance with fast time response, less overshoot and more stable operation. It has high maximum power ratio as compared to the other two conventional MPPT algorithms especially with existing of noise in the system at low irradiance.
This paper presents a fuzzylogiccontrol design for a two tanks hydraulic system model. The fuzzy logic control algorithm performance was tested for different references as well as perturbation scenarios. The fuzzy l...
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ISBN:
(纸本)9780769545639
This paper presents a fuzzylogiccontrol design for a two tanks hydraulic system model. The fuzzy logic control algorithm performance was tested for different references as well as perturbation scenarios. The fuzzylogiccontrol design proves its superiority when compared to classical controlalgorithms because of its inherent characteristics to deal with non-lineal systems. It bases its functioning in the principle of heuristics so design is natural and easy to achieve. Only a basic knowledge of the system dynamics is needed for a successful design, and no mathematical model is needed for the design process. Obtained results demonstrate the effectiveness of the proposed method, achieving a swift response and smoothness characteristics near an error tolerance.
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