Search for dissertations about: "Disturbance estimation"

Showing result 1 - 5 of 44 swedish dissertations containing the words Disturbance estimation.

  1. 1. Automation of front-end loaders : electronic self leveling and payload estimation

    Author : I Yung; Leonid Freidovich; Sven Rönnbäck; Carlos Vázquez; Tomas Nygren; Heikki Handroos; Umeå universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Front-End Loaders; Electronic Self Leveling; Modeling; Control; Disturbance estimation; Payload estimation; Equations of motion; Pressure-based friction;

    Abstract : A growing population is driving automatization in agricultural industry to strive for more productive arable land. Being part of this process, this work is aimed to investigate the possibility to implement sensor-based automation in a particular system called Front End Loader, which is a lifting arms that is commonly mounted on the front of a tractor. READ MORE

  2. 2. Estimation and Detection with Applications to Navigation

    Author : David Törnqvist; Fredrik Gustafsson; Hugh Durrant-Whyte; Linköpings universitet; []
    Keywords : Navigation; SLAM; Particle Filter; Estimation; TECHNOLOGY; TEKNIKVETENSKAP;

    Abstract : The ability to navigate in an unknown environment is an enabler for truly utonomous systems. Such a system must be aware of its relative position to the surroundings using sensor measurements. It is instrumental that these measurements are monitored for disturbances and faults. READ MORE

  3. 3. Identification of Stochastic Nonlinear Dynamical Models Using Estimating Functions

    Author : Mohamed Abdalmoaty; Håkan Hjalmarsson; Adrian Wills; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Prediction Error Method; Maximum Likelihood; Data-driven; Learning; Stochastic; Nonlinear; Dynamical Models; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Estimation; Process Disturbance; Electrical Engineering; Elektro- och systemteknik;

    Abstract : Data-driven modeling of stochastic nonlinear systems is recognized as a very challenging problem, even when reduced to a parameter estimation problem. A main difficulty is the intractability of the likelihood function, which renders favored estimation methods, such as the maximum likelihood method, analytically intractable. READ MORE

  4. 4. Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors

    Author : Mohamed Abdalmoaty; Håkan Hjalmarsson; Jimmy Olsson; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Stochastic Nonlinear Systems; Nonlinear System Identification; Learning Dynamical Models; Maximum Likelihood; Estimation; Process Disturbance; Prediction Error Method; Non-stationary Linear Predictors; Intractable Likelihood; Latent Variable Models; Electrical Engineering; Elektro- och systemteknik;

    Abstract : The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. READ MORE

  5. 5. Parameter estimation and model based control design of drive train systems

    Author : Mats Tallfors; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Signalbehandling; control; drive train; estimation; identification; mechanical; Signalbehandling; Signal processing; Signalbehandling;

    Abstract : The main control task in many speed-controlled drives is to eliminate or reduce the load speed error caused by the load torque disturbance and reduce oscillations as quickly as possible. This thesis addresses different aspects of identification and control of such resonant elastic systems. READ MORE