TK420 : Design and implementation of robust state estimator baxsed on adaptive fuzzy approach
Thesis > Central Library of Shahrood University > Electrical Engineering > PhD > 2015
Authors:
Abstarct: This thesis is concerned with the design and implementation of H∞ state
estimator of a dynamical system baxsed on the adaptive fuzzy modeling. At first, a
universal linear model is considered with some unknown variables. Since the variables
are not time invariant in modeling of a real nonlinear system so they are modeled by
fuzzy approximates with some free parameters. The system states constitute input
variables of the fuzzy system. The novelty of this research is design of stable state and
parameter estimator baxsed on H∞ criterion in wich the system states and adaptive fuzzy
systems' parameters are determined simultaneously. It will be proved that the parameter
estimator is just modified normalized least mean squares (NLMS) algorithm which
follows H∞ optimality. In this way, it reduces required tuning parameters of the filter
and has lower computational complexity. The proposed model can be used in signal
processing such as time series and speech processing or in nonlinear circuit modeling.
Finally, suggested algorithm is implemented on a practical data gathered from battery
for state of charge estimation. The results show stability, good performance, fast
convergence time, and robustness to far initial conditions of the suggested estimator.
For comparison, the proposed method is compared with the one in which the identified
free parameters are not adjusting during estimation process.
Keywords:
#Dual H∞ filter #adaptive fuzzy modeling #normalized LMS #state estimation #parameter estimation #battery state ob charge Link
Keeping place: Central Library of Shahrood University
Visitor:
Keeping place: Central Library of Shahrood University
Visitor: