The state estimation of a quantized system (Q.S.) is a challenging problem for designing feedback control and model-based fault diagnosis algorithms. The core of a Q.S. is a continuous variable system whose inputs and outputs are represented by their corresponding quantized values. This paper concerns with state estimation of a Q.S. by a qualitative observer. The presented observer in this pape...

The purpose of this paper is to present a new approach based on the Least Squares Error method for estimating the unknown parameters of the nonlinear 3rd order synchronous generator model. The proposed method uses the mathematical relationships between the machine parameters and on-line input/output measurements to estimate the parameters of the nonlinear state space model. The field voltage is...

In this paper the problems of state estimation, tracking control and shape control in a micro-cantilever beam with nonlinear electrostatic actuation are investigated. The system’s partial differential equation of motion is converted into a set of ordinary differential equations by projection method. Observabillity of the system is proven and a state estimation system is designed using extended ...

This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...

In most chemical processes only some measurements are available online while other measurements are available infrequently and often with long delays. Multirate state estimation can optimally combine these different classes of measurements to improve the estimation quality compared to the fast measurements alone. The nature of measurements at different sampling intervals which are subject to de...

The knowledge about its operation environment is a fundamental requirements for intelligents agents acting in a dynamic world. Knowledge gathering is thus a critical functionality for any agents and it involves several problems: perception, object detection, environment structure reconstruction and so on. The state estimation problem is a general definition to describe many applications: object...

This paper proposes the stochastic tabu search (STS) for improving the measurement scheme for power system state estimation. If the original measured scheme is not observable, the additional measurements with minimum number of measurements are added into the system by STS so that there is no critical measurement pair. The random bit flipping and bit exchanging perturbations are used for generat...

In this paper we introduce a state-estimation method that uses a short-term memory to calculate the current state. A common way to solve state estimation problems is to use implementations of the Bayesian algorithm like Kalman filters or particle filters. When implementing a Bayesian filter several problems can arise. One difficulty is to obtain error models for the sensors and for the state tr...