Enhanced fuzzy state estimation of discrete‐time nonlinear systems via a multi‐instant united switch‐type observer

2021 ◽  
Author(s):  
Hongyu Lu ◽  
Xiangpeng Xie ◽  
Wei Liu
Keyword(s):  
Nonlinear Systems ◽  
State Estimation ◽  
Discrete Time ◽  
Switch Type ◽  
Fuzzy State

scholarly journals Ellipsoidal and Gaussian Kalman Filter Model for Discrete-Time Nonlinear Systems

Mathematics ◽  
2019 ◽  
Vol 7 (12) ◽  
pp. 1168 ◽  
Author(s):  
Ligang Sun ◽  
Hamza Alkhatib ◽  
Boris Kargoll ◽  
Vladik Kreinovich ◽  
Ingo Neumann
Keyword(s):  
Kalman Filter ◽  
Nonlinear Systems ◽  
State Estimation ◽  
Discrete Time ◽  
Probability Distributions ◽  
Nonlinear Problems ◽  
The State ◽  
Filter Model ◽  
Highly Nonlinear ◽  
Correction Step

In this paper, we propose a new technique—called Ellipsoidal and Gaussian Kalman filter—for state estimation of discrete-time nonlinear systems in situations when for some parts of uncertainty, we know the probability distributions, while for other parts of uncertainty, we only know the bounds (but we do not know the corresponding probabilities). Similarly to the usual Kalman filter, our algorithm is iterative: on each iteration, we first predict the state at the next moment of time, and then we use measurement results to correct the corresponding estimates. On each correction step, we solve a convex optimization problem to find the optimal estimate for the system’s state (and the optimal ellipsoid for describing the systems’s uncertainty). Testing our algorithm on several highly nonlinear problems has shown that the new algorithm performs the extended Kalman filter technique better—the state estimation technique usually applied to such nonlinear problems.

Modeling and Fuzzy Control for Complex Flexible Nonlinear Systems with Time-Delay

2014 ◽  
Vol 602-605 ◽  
pp. 920-923
Author(s):  
Ji Xiang Chen
Keyword(s):  
Time Delay ◽  
Feedback Control ◽  
Nonlinear Systems ◽  
Discrete Time ◽  
State Feedback ◽  
Sufficient Conditions ◽  
State Feedback Control ◽  
Linear Matrix ◽  
Control Approach ◽  
Fuzzy State

A time-delay discrete-time fuzzy singularly perturbed modeling and fuzzy state feedback control approach are presented for a class of complex flexible nonlinear systems with time-delay. The considered flexible nonlinear system is firstly described by a time-delay standard discrete-time fuzzy singular perturbation model. A fuzzy state feedback control law is secondly design. By using a matrix spectral norm and linear matrix inequalities approach, the sufficient conditions of the controller existence are divided. The provided controller not only can stabilize the resulting closed-loop system but also overcome the effects caused by both time-delay and external disturbances. A simulation example is given to illustrate the effectiveness of the developed result.

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