Search results for "Proportional control"

showing 4 items of 4 documents

An intelligent Proportional controller of a Seeded Batch Crystallizer

2020

Crystallization process is used in a very wide range of industrial applications. However, highly nonlinear comportment of such process and the difficulties of characterizing several phenomenological effects makes difficult to find suitable operational procedures for producing required products. In this article, we use a model-free control (MFC) for controlling the mean size of crystals produced by seeded batch cooling crystallization. The MFC method is distinguished notably in terms of the modeling strategy. Rather than developing a crystallization model within the classic population balance equation (PBE) together with the mass balance and the energy balance, as is usually done, we use a l…

0209 industrial biotechnologyNoise measurementEnergy balanceProcess (computing)Population balance equationProportional control02 engineering and technologylaw.inventionNonlinear system020901 industrial engineering & automation020401 chemical engineeringControl theorylaw0204 chemical engineeringCrystallization2020 17th International Multi-Conference on Systems, Signals & Devices (SSD)
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Linearized Piecewise Affine in Control and States Hydraulic System: Modeling and Identification

2018

In this paper, the modeling and identification of a nonlinear actuated hydraulic system is addressed. The full-order model is first reduced in relation to the load pressure and flow dynamics and, based thereupon, linearized over the entire operational state-space. The dynamics of the proportional control valve is identified, analyzed, and intentionally excluded from the reduced model, due to a unity gain behavior in the frequency range of interest. The input saturation and dead-zone nonlinearities are considered while the latter is identified to be close to 10% of the valve opening. The mechanical part includes the Stribeck friction detected and estimated from the experiments. The lineariza…

0209 industrial biotechnologySeries (mathematics)020208 electrical & electronic engineeringProportional control02 engineering and technologyServomotorNonlinear system020901 industrial engineering & automationFlow (mathematics)Control theoryLinearization0202 electrical engineering electronic engineering information engineeringRange (statistics)Hydraulic machineryMathematicsIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
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Robust model-following control of parallel UPS single-phase inverters

2008

This paper presents a robust control technique applied to modular uninterruptible power-supply (UPS) inverters operating in parallel. When compared to conventional proportional-integral (PI) control, the proposed technique improves the response of the output voltage to load steps and to high distorted output currents, reducing the distortion of the output voltage. Furthermore, an excellent distribution of currents between modules is achieved, resulting in fine power equalization between the inverters on stream. The crossover frequency of the different loop gains involved is moderate, so that robustness to variations of the operation point and to modeling uncertainties is achieved. A compara…

Crossover frequencyEngineeringbusiness.industryInverter controlParallel invertersProportional controlModular designOperation pointUninterruptible power supply (UPS)TECNOLOGIA ELECTRONICAControl and Systems EngineeringControl theoryRobustness (computer science)Electronic engineeringElectrical and Electronic EngineeringRobust controlSingle phasebusinessVoltage
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Optimization of Delayed-State Kalman-Filter-based Algorithm via Differential Evolution for Sensorless Control of Induction Motors

2010

This paper proposes the employment of the differential evolution (DE) to offline optimize the covariance matrices of a new reduced delayed-state Kalman-filter (DSKF)-based algorithm which estimates the stator-flux linkage components, in the stationary reference frame, to realize sensorless control of induction motors (IMs). The DSKF-based algorithm uses the derivatives of the stator-flux components as mathematical model and the stator-voltage equations as observation model so that only a vector of four variables has to be offline optimized. Numerical results, carried out using a low-speed training test, show that the proposed DE-based approach is very promising and clearly outperforms a cla…

evolutionary algorithms (EAs)induction-motor (IM) drivesvelocity controlspeed sensorlessProportional controlcovariance matricesKalman filteralgorithmsSliding mode controlControl and Systems EngineeringRobustness (computer science)Control theoryAC motor drivesDifferential evolutionoptimization methodsstate estimationElectrical and Electronic EngineeringRobust controlparameter estimationAlgorithmStationary Reference FrameKalman filteringInduction motorMathematics
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