Movements in a linear system like this are best controlled by a state-space controller. Problems begin at state reconstruction: usually only the piston's position is measured; velocity and acceleration have to be either computed by differentiation of position or estimated by an observer algorithm. ...
State Space Adaptive Control for Nonlinear SystemsIn education of modern control theory it is very substantial to present students technical problems where the application of modern methods is necessary and justified by their complexity and present this in a control lab. An example of a control ...
We build the nonlinear state space model for analyzing the highly nonlinear system and then develop a Hammerstein-Wiener (H-W) model which consists of a static input nonlinear block with two-segment polynomial nonlinearities, a linear time-invariant dynamic block, and a static output nonlinear ...
A state-space approach to the Youla parameterization of stabilizing controllers for linear and nonlinear systems is suggested. The stabilizing controllers (or a class of stabilizing controllers for nonlinear systems) are characterized as fractional transformations of stable parameters. The main idea behind...
J., `Nonlinear state space H, control theory', in Essays on Control: Perspectives in the Theory and its Applications, H. L. Trentelman and J. C. Willems (Eds), Birkhauser, Boston, MA, 1993, pp. 153-190.van der Schaft, A. J., "Nonlinear State Space H, Control Theory", ...
In this paper, we propose a parameter estimation method for nonlinear state-space models based on the variational Bayes. It is proved that the variational posterior distribution of the hidden states is equivalent to a posterior distribution of the states of an augmented nonlinear state-space model....
This paper shows how to check rank criteria for a local identification of nonlinear DSGE models, given higher-order approximations and pruning. This approa... W Mutschler - 《Journal of Economic Dynamics & Control》 被引量: 11发表: 2015年 Frontiers | Jesús Fernández The Pruned State-Space ...
Introduction In this paper, we study SMC methods for smoothing in nonlinear state space models. We consider a bivariate process (X, Y ), where X {X k ; k ≥ 0} is a homogeneous discrete- time Markov chain taking values in some state space (X, X). We let (Q θ , θ∈Θ⊆R ...
This idea needs to be completed for the robust design: it is necessary to construct a Lyapunov function for an uncertain nonlinear system and to obtain the robust controller once the Lyapunov function is known. The book is organized around solving these problems. After an introduction and a ...
The models are widely used in modern control applications for designing controllers and analyzing system performance in the time domain and frequency domain. The models can be applied to nonlinear systems or systems with non-zero initial conditions. They also provide a convenient way to represent, ...