نتایج جستجو برای: exact linearization el

تعداد نتایج: 409975  

2013
Hany Osman M. F. Baki

We address the balancing problem of transfer lines in this paper to find the optimal line balancing that minimizes the nonproductive time. We focus on the tool change time and face orientation change time both of which influence the makespane. We consider machine capacity limitations and technological constraints associated with the manufacturing process of auto cylinder heads. The problem is r...

Journal: :Kybernetika 1994
Hans Hahn X. Zhang K.-D. Leimbach Hanns-Jakob Sommer

This paper presents a nonlinear control concept of a planar multi-axis servohydraulic test facility. Based on nonlinear model equations including servohydraulic actuator dynamics and test table and payload mechanics a global nonlinear diffeomorphism is derived which maps the model equations into nonlinear canonical form. A nonlinear control law is derived using exact linearization techniques. T...

2011
Vijay Gupta Ignacio E. Grossmann

The optimal development planning of offshore oil and gas fields has received significant attention in recent years. In this paper, we present an efficient investment and operational planning model for this problem which is fairly generic, and is extended to include fiscal considerations. With the objective of maximizing total NPV for long-term planning horizon, the proposed non-convex multiperi...

Journal: :Kybernetika 1995
Sergej Celikovský

The general, differential-equation-independent definition of a continuous-time controlled dynamical system as well as of the state space transformation and static state feedback are introduced. This approach makes it possible to consider transformations that are not smooth and introduce the so-called topological equivalence of controlled dynamical sys­ tems. It is shown that this approach gener...

2011
Jorge Cortés

In this lecture, we investigate the problem of exact linearization by feedback for multiple input multiple output systems. We will see that, when a “vector” relative degree exists, things go as smoothly as for SISO systems. To deal with the case when no relative degree exists, we will discuss the dynamic extension algorithm. This algorithm will help us choose a dynamic state feedback to make th...

2008
Wei Lin Jinfeng Wei Feng Wan

Abstract—Necessary and sufficient conditions are presented under which a discrete-time autonomous system with outputs is locally diffeomorphic to an output-scaled linear observable system or an output-scaled nonlinear system in the observer form. As a consequence of such characterizations, the nonlinear observer design problem is studied by a time-scaling approach combined with the exact linear...

2008
Zhongsheng Hou Shangtai Jin

The NARMA model is an exact representation of the input-output behavior of finitedimensional nonlinear discrete-time dynamical systems in the neighborhood of the equilibrium state. However, it is inconvenient for purposes of adaptive control due to its nonlinear dependence on the control input, even by using the neural network method. In this paper, we introduce a so called model-free adaptive ...

2005
Alexander Kipp Peter Krauthausen Frank Dellaert

We present an extension of a smoothing approach to Simultaneous Localization and Mapping (SLAM). We have previously introduced Square-Root SAM, a Smoothing and Mapping approach to SLAM based on Levenberg-Marquardt (LM) optimization. It iteratively finds the optimal nonlinear least squares solution (ML), where one iteration comprises of a linearization step, a matrix factorization, and a backsub...

2004
Bojan GrCar Peter Cafuta Mitja ZnidariC Felix Gausch

The complete control design for a permanent magnet synchronous (PMAC) motor, derived from the input-output linearization, is presented in the paper. The motor model, written in the rotor’s d-q coordinates, is nonlinear with respect to the state variables and linear in the control. The input-output linearization makes it possible to write the motor’s model in Brunovski decoupled canonical form w...

2010
Trond Ingebrigtsen

where λ is the Lagrange multiplier and ψ = 0 the holonomic constraint. The first practical algorithm for constrained dynamics was called SHAKE [3]. In this algorithm the Lagrange multiplier was calculated from the viewpoint, that no exact discrete solution could be obtained. Thus the constraints were satisfied by inserting the discrete propagator into the holonomic constraint, ψ(t+ h) = 0. This...

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