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    Tytuł:
    Stiffness control of robot manipulators in the operational space using fuzzy mapping of dynamic functions
    Autorzy:
    Bertol, D. W.
    Barasuol, V.
    Martins, N. A.
    De Pieri, E. R.
    Powiązania:
    https://bibliotekanauki.pl/articles/971046.pdf
    Data publikacji:
    2013
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    stiffness control
    fuzzy mapping
    robot manipulators
    operational space
    trajectory tracking
    Opis:
    In this paper a stiffness control strategy based on the fuzzy mapped nonlinear terms of the robot manipulator dynamic model is proposed. The proposed stiffness controller is evaluated on a research robot manipulator performing a task in the operational space. Tests attempted to achieve fast motion with reasonable accuracy associated with lower computational load compared to the non-fuzzy approach. The stability analysis is presented to conclude about the mapping error influence and to obtain precondition criteria for the gains adjustment to face the trajectory tracking problem. Simulation results that supported the implementation are presented, followed by experiments and results obtained. These tests are conducted on a robot manipulator with SCARA configuration to illustrate the feasibility of this strategy.
    Źródło:
    Control and Cybernetics; 2013, 42, 3; 639-661
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Trajectory tracking of a wheeled mobile robot with uncertainties and disturbances: proposed adaptive neural control
    Autorzy:
    Martins, N. A.
    Alencar, M.
    Lombardi, W. C.
    Bertol, D. W.
    Pieri, E. R.
    Filho, H. F.
    Powiązania:
    https://bibliotekanauki.pl/articles/971045.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Instytut Badań Systemowych PAN
    Tematy:
    wheeled mobile robot
    trajectory tracking
    kinematic control
    variable structure control
    dynamic control
    sliding mode theory
    neural networks
    Lyapunov theory
    Opis:
    This paper analyses a trajectory tracking control problem for a wheeled mobile robot, Rusing integration of a kinematic neural controller (KNC) and a torque neural controller (TNC), in which both the kinematic and dynamic models contain uncertainties and disturbances. The proposed adaptive neural controller (PANC) is composed of the KNC and the TNC and is designed with use of a modeling technique of Gaussian radial basis function neural networks (RBFNNs). The KNC is a variable structure controller, based on the sliding mode theory and is applied to compensate for the disturbances of the wheeled mobile robot kinematics. The TNC is an inertia-based controller composed of a dynamic neural controller (DNC) and a robust neural compensator (RNC) applied to compensate for the wheeled mobile robot dynamics, bounded unknown disturbances, and neural network modeling errors. To minimize the problems found in practical implementations of the classical variable structure controllers (VSC) and sliding mode controllers (SMC), and to eliminate the chattering phenomenon, the nonlinear and continuous KNC and RNC of the TNC are applied in lieu of the discontinuous components of the control signals that are present in classical forms. Additionally, the PANC neither requires the knowledge of the wheeled mobile robot kinematics and dynamics nor the timeconsuming training process. Stability analysis, convergence of the tracking errors to zero, and the learning algorithms for the weights are guaranteed based on the Lyapunov method. Simulation results are provided to demonstrate the effectiveness of the proposed approach.
    Źródło:
    Control and Cybernetics; 2015, 44, 1; 47-98
    0324-8569
    Pojawia się w:
    Control and Cybernetics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
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