Motion Planning of Uncertain Ordinary Differential Equation Systems

This work presents a novel motion planning framework, rooted in nonlinear programming theory, that treats uncertain fully and under-actuated dynamical systems described by ordinary differential equations. Uncertainty in multibody dynamical systems comes from various sources, such as: system parameters, initial conditions, sensor and actuator noise, and external forcing. Treatment of uncertainty in design is of paramount practical importance because all real-life systems are affected by it, and poor robustness and suboptimal performance result if it’s not accounted for in a given design. In this work uncertainties are modeled using Generalized Polynomial Chaos and are solved quantitatively using a least-square collocation method. The computational efficiency of this approach enables the inclusion of uncertainty statistics in the nonlinear programming optimization process. As such, the proposed framework allows the user to pose, and answer, new design questions related to uncertain dynamical systems. Specifically, the new framework is explained in the context of forward, inverse, and hybrid dynamics formulations. The forward dynamics formulation, applicable to both fully and under-actuated systems, prescribes deterministic actuator inputs which yield uncertain state trajectories. The inverse dynamics formulation is the dual to the forward dynamic, and is only applicable to fully-actuated systems; deterministic state trajectories are prescribed and yield uncertain actuator inputs. The inverse dynamics formulation is more computationally efficient as it requires only algebraic evaluations and completely avoids numerical integration. Finally, the hybrid dynamics formulation is applicable to under-actuated systems where it leverages the benefits of inverse dynamics for actuated joints and forward dynamics for unactuated joints; it prescribes actuated state and unactuated input trajectories which yield uncertain unactuated states and actuated inputs. The benefits of the ability to quantify uncertainty when planning the motion of multibody dynamic systems are illustrated through several case-studies. The resulting designs determine optimal motion plans—subject to deterministic and statistical constraints—for all possible systems within the probability space

KLM quantum computation as a measurement based computation

We show that the Knill Laflamme Milburn method of quantum computation with linear optics gates can be interpreted as a one-way, measurement based quantum computation of the type introduced by Briegel and Rausendorf. We also show that the permanent state of n n-dimensional systems is a universal state for quantum computation.Comment: 4 pages 3 figure

EURO - CHALLENGES AND PERSPECTIVES FOR ROMANIA

The process of preparation and adoption of the European single currency is one of the most important challenges that Romania has to face in the first decade as a full time member of the European Union. This process will test both the political and the administrative capacity, requiring very clear programs for the adaptation of European regulations and directives that will ensure real and nominal convergence. This process will surely prove to be a difficult one and it will bring a high degree of pressure upon the economic system in general. The worldwide financial crisis is making the process of single European currency adoption even more difficult for Romania. Although its effects are not directly felt in Romania, the disorder created within international markets can easily transform the management of economic and currency politics into an insecure and extremely difficult task.exchange rate, euro, Economic and Monetary Union, Euro Zone, convergence criteria, ERM II, NBR, ECB, financial crisis