Search results for "model predictive control"

showing 10 items of 35 documents

An Adaptive Robust Predictive Current Control for Three-Phase Grid-Connected Inverters

2011

This paper presents an adaptive robust predictive current control (RPCC) for grid-connected three-phase inverters that exhibit zero steady-state current error. The error correction is achieved by means of an adaptive strategy that works in parallel with the deadbeat algorithm, therefore preserving the typical fast response of the predictive law. The resulting control adapts to any particular L or LCL filter by estimation of the resistive part of the filter. As a variety of the RPCC class of control, it offers the best tradeoff between robustness and speed. © 2009 IEEE.

EngineeringAdaptive controlThree-phase inverterGrid connected invertersElectric current controlElectric invertersTECNOLOGIA ELECTRONICAControl theoryRobustness (computer science)Active power filteringCurrent-controlled voltage source invertersFast responseElectrical and Electronic EngineeringActive filterAdaptive strategyActive filtersActive power filtering (APF)Power convertersbusiness.industryGrid-connectedPredictive current controlGridSteady-state currentsDeadbeat algorithmModel predictive controlCurrent-controlled voltage source inverter (VSI)Robust predictive current control (RPCC)Three-phaseControl and Systems EngineeringRobust controlLCL filtersError detection and correctionbusinessIEEE Transactions on Industrial Electronics
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Model predictive control for drum water level of boiler systems

2014

EngineeringDrum Water LevelInformation Systems and Managementbusiness.industryBoiler (power generation)DrumLinear-quadratic-Gaussian controlWater levelNonlinear systemModel predictive controlControl theoryControl and Systems EngineeringbusinessNon-linear SystemsDrum Water Level; Model Predictive Control; Non-linear Systems; Information Systems and Management; Control and Systems EngineeringModel Predictive Control
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Robust Predictive Control of a variable speed wind turbine using the LMI formalism

2014

This paper proposes a Robust Fuzzy Multivariable Model Predictive Controller (RFMMPC) using Linear Matrix Inequalities (LMIs) formulation. The main idea is to solve at each time instant, an LMI optimization problem that incorporates input, output and Constrained Receding Horizon Predictive Control (CRHPC) constraints, and plant uncertainties, and guarantees certain robustness properties. The RFMMPC is easily designed by solving a convex optimization problem subject to LMI conditions. Then, the derived RFMMPC applied to a variable wind turbine with blade pitch and generator torque as two control inputs. The effectiveness of the proposed design is shown by simulation results.

EngineeringMathematical optimizationOptimization problembusiness.industryBlade pitchLMIs formalism; predictive control; quadratic program; T-S fuzzy model; Control and Systems EngineeringFuzzy logicVariable speed wind turbineModel predictive controlLMIs formalismControl and Systems EngineeringComputer Science::Systems and ControlControl theoryRobustness (computer science)Convex optimizationQuadratic programmingquadratic programT-S fuzzy modelbusinesspredictive control2014 European Control Conference (ECC)
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Fuzzy predictive controller design using ant colony optimization algorithm

2014

In this paper, an approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the Ant Colony Optimization (ACO) is studied. On-line adaptive fuzzy identification is used to identify the system parameters. These parameters are used to calculate the objective function based on predictive approach and structure of RST control. The optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to calculate a sequence of future RST control actions. The obtained simulation results show that proposed approach provides better results compared with Proportional Integral-Ant Colony Optimization (PI-ACO) controller and adaptive fuzzy model pr…

EngineeringMeta-optimizationOptimization problemLinear programmingbusiness.industryAnt colony optimization algorithmsComputer Science Applications1707 Computer Vision and Pattern RecognitionComputingMethodologies_ARTIFICIALINTELLIGENCEFuzzy logicModel predictive controlControl theoryControl and Systems EngineeringModeling and SimulationModeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Control and Systems Engineering; Electrical and Electronic EngineeringElectrical and Electronic EngineeringbusinessAlgorithmMetaheuristic
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Performances Comparison for a Rotating Shaft Suspended by 4-Axis Radial Active Magnetic Bearings via 𝜇 -Synthesis, Loop-Shaping Design, and Sub ( 𝐻…

2011

The control systems applied on active magnetic bearing are several. A perfect levitation is characterized by maintaining the operating point condition that is characterized by the center of stator coincident with the geometric center of shaft. The first controller implemented for this purpose is PID controller that is characterized by an algorithm that leads the amplifier to produce control current until the operating point condition is not reached, this is obtained by an integration operator. The effect of an integrator is essential but not necessary for a centered levitation for example in the robust control characterized by a dynamic model depended on plant of system so that it depends o…

EngineeringOperating pointArticle Subjectbusiness.industryGeneral EngineeringMagnetic bearingPID controllerAngular velocitylcsh:QA75.5-76.95Computer Science ApplicationsModel predictive controlRotating shaft Active Megnetic Bearing μ-Synthesis Loop-Shaping Design Sub(H)∞Settore ING-IND/14 - Progettazione Meccanica E Costruzione Di MacchineControl theoryModeling and SimulationIntegratorlcsh:Electronic computers. Computer scienceRobust controlbusinessModelling and Simulation in Engineering
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A New Generalized Robust Predictive Current Control for Grid-Connected Inverters Compensates Anti-Aliasing Filters Delay

2016

In this paper, a new predictive control for grid-connected inverters is presented, which provides the best performance in terms of transient response and stability margins when analog filters in current sensing circuits are used. These filters are necessary to avoid aliasing in the A/D conversion process, which causes an important ripple on injected current into the grid and increases the total harmonic distortion. However, predictive controls are very sensitive to delays on the acquisitions, so when such anti-aliasing filters are used a reduction of stability margins is produced and the transient response is affected. The proposed predictive control allows to compensate the effect of the f…

EngineeringTotal harmonic distortionbusiness.industry020209 energy020208 electrical & electronic engineeringRipple02 engineering and technologyFilter (signal processing)Anti-aliasingAnalogue filterModel predictive controlControl and Systems EngineeringAliasingControl theory0202 electrical engineering electronic engineering information engineeringElectronic engineeringTransient responseElectrical and Electronic EngineeringbusinessIEEE Transactions on Industrial Electronics
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PEM Fuel Cell System Model Predictive Control and real-time operation on a power emulator

2010

Fuel Cell Systems (FCS) seem to be among the most reliable devices to produce clean energy, although they still suffer for many problems, mostly related to the fragility of the Polymer Electrolyte Membrane (PEM). Particularly, this paper focuses on the oxygen starvation, that leads both a decrease of the FCS performance and a shortening in the FCS lifetime. The purpose is to use the Model Predictive Control (MPC) and its capacity of accounting for linear constraints for managing the air system without risking to damage the fuel cell. Two control inputs and no static feed-forward actions have been used. Results show that the MPC is able to avoid the oxygen starvation, even with a sudden incr…

Engineeringair managementmodel predictive controlbusiness.industryProton exchange membrane fuel cellConvertersfuel cell systemsSystem modelPower (physics)Model predictive controlFragilityControl theoryFuel cellslipids (amino acids peptides and proteins)businessOxygen starvation2010 IEEE Energy Conversion Congress and Exposition
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LPV Predictive Control of the Stall and Surge for Jet Engine 1

2001

Abstract Predictive control of constrained LPV systems is applied to the model of the stall and surge control for jet engine compressors. The objective of the used technique is to optimize nominal performance while guaranteeing robust stability and constraint satisfaction. This is achieved by exploiting invariant sets and a receding horizon optimization procedure which provides on-line a non-linear correction to a gain-scheduled linear feedback designed off-line. A comparison with a contractive gain-scheduling control technique is also shown.

Engineeringbusiness.industryControl engineeringConstraint satisfactionJet enginelaw.inventionModel predictive controlGain schedulinglawControl theoryRobust controlbusinessGas compressorSurge controlStall (engine)IFAC Proceedings Volumes
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A Robust Predictive Current Control for Three-Phase Grid-Connected Inverters

2009

This paper presents a new predictive control algorithm for grid-connected current-controlled inverters. The control combines a two-sample deadbeat control law with a Luenberger observer to estimate the future value of the grid currents. The resulting control offers robustness against the computational delay inherent in the digital implementation and considerably enhances the gain and phase margins of the previous predictive controls while maintaining the high-speed response typical of the deadbeat controllers.

Engineeringbusiness.industryControl engineeringGridInductanceModel predictive controlThree-phaseControl and Systems EngineeringControl theoryRobustness (computer science)State observerElectrical and Electronic EngineeringRobust controlbusinessVoltageIEEE Transactions on Industrial Electronics
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An ant colony optimization-based fuzzy predictive control approach for nonlinear processes

2015

In this paper, a new approach for designing an adaptive fuzzy model predictive control (AFMPC) based on the ant colony optimization (ACO) is proposed. On-line adaptive fuzzy identification is introduced to identify the system parameters. These parameters are used to calculate the objective function based on a predictive approach and structure of RST control. Then the optimization problem is solved based on an ACO algorithm, used at the optimization process in AFMPC to determine optimal controller parameters of RST control. The utility of the proposed controller is demonstrated by applying it to two nonlinear processes, where the proposed approach provides better performances compared with p…

Information Systems and ManagementMeta-optimizationOptimization problemComputer scienceAnt colony optimization algorithmsComputer Science::Neural and Evolutionary ComputationProcess (computing)Computer Science ApplicationsTheoretical Computer ScienceNonlinear systemModel predictive controlArtificial IntelligenceControl and Systems EngineeringControl theoryMetaheuristicSoftwareInformation Sciences
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