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  • CYBERNETICS  (3)
  • 2000-2004
  • 1990-1994  (3)
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  • 1992  (3)
  • 1
    Publikationsdatum: 2019-06-28
    Beschreibung: The problem of rigid object handling by multiple robot arms is investigated. The primary goal is to make the object exhibit a prescribed behavior while in contact with a fully known environment. Point contacts are assumed between the object and the arms. The aspect of task definition to achieve decoupling and linearizing control laws is discussed. Control laws are first formulated at the object level to provide decoupled force and position servo loops. It is then used to form control laws for the individual arms. Redundancies exist at the object and arm levels. The object level redundancy is used to achieve secondary goals in object handling. The arm level redundancies are the zero dynamics and can be controlled by redundant inputs. Full use of the available inputs are used to control the system as a whole. Numerical simulations for a dual-arm situation illustrate the validity of the approach.
    Schlagwort(e): CYBERNETICS
    Materialart: In: 1992 IEEE International Conference on Robotics and Automation, 8th, Nice, France, May 12-14, 1992, Proceedings. Vol. 1 (A93-35501 13-63); p. 467-474.
    Format: text
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  • 2
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    Publikationsdatum: 2011-08-24
    Beschreibung: In this paper the quadratically optimal model reduction problem for single-input, single-output systems is considered. The reduced order model is determined by minimizing the integral of the magnitude-squared of the transfer function error. It is shown that the numerator coefficients of the optimal approximant satisfy a weighted least squares problem and, on this basis, a two-step iterative algorithm is developed combining a least squares solver with a gradient minimizer. Convergence of the proposed algorithm to stationary values of the quadratic cost function is proved. The formulation is extended to handle the frequency-weighted optimal model reduction problem. Three examples demonstrate the optimization algorithm.
    Schlagwort(e): CYBERNETICS
    Materialart: Automatica (ISSN 0005-1098); 28; 5; p. 897-909.
    Format: text
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  • 3
    Publikationsdatum: 2019-08-28
    Beschreibung: A novel fast learning rule with fast weight identification is proposed for the two-time-scale neural controller, and a two-stage learning strategy is developed for the proposed neural controller. The results of the stability analysis show that both the tracking error and the fast weight error will be uniformly bounded and converge to a bounded region which depends only on the accuracy of the slow learning if the system is sufficiently excited. The efficiency of the two-stage learning is also demonstrated by a simulation of a two-link arm.
    Schlagwort(e): CYBERNETICS
    Materialart: In: IJCNN - International Joint Conference on Neural Networks, Baltimore, MD, June 7-11, 1992, Proceedings. Vol. 1 (A93-37001 14-63); p. I-707 to I-712.
    Format: text
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