Digitální knihovnaUPCE
 

Fakulta elektrotechniky a informatiky / Faculty of Electrical Engineering and Informatics

Stálý URI pro tuto komunituhttps://hdl.handle.net/10195/3847

Práce obhájené před rokem 2008 jsou uloženy pouze v kolekci Vysokoškolské kvalifikační práce

Procházet

Filtry

2016 - 20172

Nastavení

Autor: search.filters.author.Honc, DanielPředmět: search.filters.subject.prediktivní řízeníPředmět: search.filters.subject.mobilní robot

Search Results

Nyní se zobrazuje 1 - 2 z 2
  • Náhled
    Konferenční objektpeer-reviewedpostprintOtevřený přístup
    Comparitive study of predictive controllers for trajectory tracking of non-holonomic mobile robot
    (IEEE (Institute of Electrical and Electronics Engineers), 2017) Kizhakke Illom, Rahul Sharma; Dušek, František; Honc, Daniel
    The paper deals with predictive control of non-holonomic mobile robot. The basic nonlinear kinematic equation is linearized into two different linear time varying models based on frame of reference-world coordinates and local coordinate of mobile robot. The non-linear model predictive control is applied to the trajectory tracking problem of a non-holonomic mobile robot with these models. The control law is derived from a cost function which penalizes the state tracking error, control effort and terminal state deviation error. Various simulation experiments are conducted and a comparative analysis has been made with respect to state-of-the-art approaches.
  • Náhled
    Konferenční objektpeer-reviewedpostprintOmezený přístup
    PREDICTIVE CONTROL OF DIFFERENTIAL DRIVE MOBILE ROBOT CONSIDERING DYNAMICS AND KINEMATICS
    (EUROPEAN COUNCIL MODELLING & SIMULATION, 2016) Sharma K., Rahul; Honc, Daniel; Dušek, František
    The paper deals with trajectory tracking of the differential drive robot with a mathematical model governing dynamics and kinematics. Motor dynamics and chassis dynamics are considered for deriving a linear state-space dynamic model. Basic nonlinear kinematic equations are linearized into a successively linearized state-space model. The dynamic and kinematic models are augmented to derive a single state-space linear model. The deviation variables are reference variables which are variables of an ideal robot following a reference trajectory which can be pre-calculated. Reference tracking is achieved by model predictive control of supply voltage of both the drive motors by considering constraints on controlled variables and manipulated variables. Simulation results are provided to demonstrate the performance of proposed control strategy in the MATLAB simulation environment.