36 research outputs found

    A real-time iteration scheme for nonlinear optimization in optimal feedback control

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    An efficient Newton-type scheme for the approximate on-line solution of optimization problems as they occur in optimal feedback control is presented. The scheme allows a fast reaction to disturbances by delivering approximations of the exact optimal feedback control which are iteratively refined during the runtime of the controlled process. The contractivity of this real-time iteration scheme is proven, and a bound on the loss of optimality-compared with the theoretical optimal solution-is given. The robustness and excellent real-time performance of the method is demonstrated in a numerical experiment, the control of an unstable system, namely, an airborne kite that shall fly loops.status: publishe

    Unreliable Narration and Dual Perspective

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    In Unreliability and Point of View in Filmic Narration, Emar Maier makes a distinction between reliable and unreliable narrators. The latter, Maier claims, must be a first-person narrator, as an impersonal, third-person narrator lacks an individual perspective that can be unreliable (with some exceptions he sets aside). He concludes that most film adaptations of unreliably narrated novels are not themselves unreliably narrated, for they feature third person perspectives (not through the novel’s narrator’s eyes). I take Maier’s major claims to be (1) that there is a strict distinction between reliable and unreliable narration; and (2) that film shots displaying both a character and that character's hallucinations are not unreliable narration. I will challenge both.</jats:p

    Real-Time Iterations for Nonlinear Optimal Feedback Control

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    Emergent Behaviors of Cucker-Smale Flocks on Riemannian Manifolds

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    In this article, we present a new Cucker-Smale model on smooth Riemannian manifolds using the concepts of covariant derivative and parallel transport, and we also study its emergent dynamics under an a priori assumption on the energy functional. For Euclidean space, our proposed model coincides with the original Cucker-Smale model. As concrete examples, we consider three Riemannian manifolds: the unit 2-sphere, the unit circle, and the Poincare half-plane, and provide explicit reductions from the proposed general model to aforementioned manifolds via explicit formulas for the covariant derivative and parallel transport.N

    Emergent Behaviors of Cucker–Smale Flocks on Riemannian Manifolds

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    Human-like actuated walking that is asymptotically stable without feedback

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    Nominal stability of the real-time iteration scheme for nonlinear model predictive control

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    We present and investigate a Newton type method for online optimization in nonlinear model predictive control, the so called ``real-time iteration scheme''. In this scheme only one Newton type iteration is performed per sampling instant, and the control of the system and the solution of the optimal control problem are performed in parallel. In the resulting combined dynamics of system and optimizer, the actual feedback control in each step is based on the current solution estimate, and the solution estimates are at each sampling instant refined and transferred to the next optimization problem by a specially designed transition. This approach yields an efficient online optimization algorithm that has already been successfully tested in several applications. Due to the close dovetailing of system and optimizer dynamics, however, stability of the closed-loop system is not implied by standard nonlinear model predictive control results. In this paper, we give a proof of nominal stability of the scheme which builds on concepts from both, NMPC stability theory and convergence analysis of Newton type methods. The principal result is that -- under some reasonable assumptions -- the combined system-optimizer dynamics can be guaranteed to converge towards the origin from significantly disturbed system-optimizer states
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