Dynamics of Hydrostatic Transmission

Model description: 

The hydrostatic transmission dynamics is represented by a nonlinear fourth order state-space model

$$\begin{align*} \dot{q}_{1}(t) &= -a_{11}q_{1}(t)+b_{11}u_{1}(t) \\ \dot{q}_{2}(t) &= -a_{22}q_{2}(t)+b_{22}u_{2}(t) \\ \dot{q}_{3}(t) &= a_{31}q_{1}(t)p(t)-a_{33}q_{3}(t)-a_{34}q_{2}(t)q_{4}(t) \\ \dot{q}_{4}(t) &=a_{43}q_{2}(t)q_{3}(t)-a_{44}q_{4}(t), \end{align*}$$

where $q_1(t)$ is the normalized hydraulic pump angle, $q_2(t)$ is the normalized hydraulic motor angle, $q_3(t)$ is the pressure difference [bar], $q_4(t)$ is the hydraulic motor speed [rad/s], $p(t)$ is the speed of hydraulic pump [rad/s], $u_1(t)$ is the normalized control signal of the hydraulic pump, and $u_2(t)$ is the normalized control signal of the hydraulic motor. It is supposed that the external variable $p(t)$ , as well as the second state variable $q_2(t)$ are measurable. In given working point the model parameters are

$\eqalignno{& a_{11}=7.6923 \qquad a_{22}=4.5455 \quad a_{33}=7.6054.10^{-4} \cr &a_{31}=0.7877 \qquad a_{34}=0.9235\quad\ b_{11}=1.8590.10^{3} \cr &a_{43}=12.1967 \quad\ \ a_{44}=0.4143\quad b_{22}= 1.2879.10{}^{{3}}}$

Type: 

Form: 

Model order: 

4

Time domain: 

Linearity: 

Publication details: 

TitleDesign of Stable Fuzzy-Observer-Based Residual Generators for a Class of Nonlinear Systems
Publication TypeConference Paper
Year of Publication2011
AuthorsKrokavec, D., Filasova A., and Hladky V.
Conference Name15th IEEE International Conference on Intelligent Engineering Systems (INES), 2011
Date Published06/2011
PublisherIEEE
Conference LocationPoprad
ISBN Number978-1-4244-8954-1
Accession Number12118815
Keywordscontinuous time systems, fault diagnosis, fuzzy systems, linear matrix inequalities, MIMO systems, nonlinear control systems, observers, stability
AbstractOne principle for designing fuzzy-observer-based fault residual generators for one class of continuous-time nonlinear MIMO system is treated in this paper. The problem addressed can be indicated as an approach given sufficient conditions for residual generator design based on fuzzy system state observers. The conditions are outlined in the terms of linear matrix inequalities to possess a stable structure closest to optimal asymptotic properties. Simulation results illustrate the design procedures and demonstrate the performance of the proposed residual generator.
DOI10.1109/INES.2011.5954768