Search results for "state estimation"

showing 3 items of 13 documents

Descriptor-type Kalman Filter and TLS EXIN Speed Estimate for Sensorless Control of a Linear Induction Motor.

2014

This paper proposes a speed observer for linear induction motors (LIMs), which is composed of two parts: 1) a linear Kalman filter (KF) for the online estimation of the inductor currents and induced part flux linkage components; and 2) a speed estimator based on the total least squares (TLS) EXIN neuron. The TLS estimator receives as inputs the state variables, estimated by the KF, and provides as output the LIM linear speed, which is fed back to the KF and the control system. The KF is based on the classic space-vector model of the rotating induction machine. The end effects of the LIMs have been considered an uncertainty treated by the KF. The TLS EXIN neuron has been used to compute, in …

State variableEngineeringObserver (quantum physics)neural networks (NNs)linear induction motor controlLinear Induction Motor (LIM) Kalman Filter Total Least-Squares Neural Networks.Industrial and Manufacturing EngineeringSettore ING-INF/04 - AutomaticaKalman filter (KF)Control theorylinear induction motor (LIM)state estimationElectrical and Electronic EngineeringTotal least squaresAlpha beta filterArtificial neural networkbusiness.industryEstimatorKalman filterLinear motorFlux linkagetotal least squares (TLS)Control and Systems EngineeringLinear induction motorbusinessInduction motor
researchProduct

Extended Kalman Filter for sensorless control of induction motors

2010

This paper deals with speed and rotor flux estimation of induction motors via Extended Kalman Filter (EKF). The filter is designed starting from a discrete time model obtained by means of a first order discretization of the original nonlinear model of the induction motor (IM). In order to obtain accurate estimation of the above mentioned variables, the load torque is included into the state variables and then estimated, thus constructing a sixth order EKF. Experimental results are shown with reference to a closed loop sensorless control system, consisting of a 750 W induction motor supplied by a voltage source inverter, a cascade controller consisting of four PI control loops and the design…

State variableEngineeringbusiness.industryControl engineeringKalman filterInvariant extended Kalman filterExtended Kalman filterSettore ING-INF/04 - AutomaticaComputer Science::Systems and ControlControl theoryFilter (video)Control systemFull state estimation sensorless control experimental validation.TorquebusinessInduction motor2010 First Symposium on Sensorless Control for Electrical Drives
researchProduct

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
researchProduct