scholarly journals An Adaptive Derivative Estimator for Fault-Detection Using a Dynamic System with a Suboptimal Parameter

Algorithms ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 101
Author(s):  
Manuel Schimmack ◽  
Paolo Mercorelli
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Dynamic System ◽  
Adaptive Algorithm ◽  
Adaptive Kalman Filter ◽  
Infinite Time ◽  
Lyapunov Approach ◽  
First Order ◽  
First Derivative ◽  
Proven Theorem

This paper deals with an approximation of a first derivative of a signal using a dynamic system of the first order. After formulating the problem, a proposition and a theorem are proven for a possible approximation structure, which consists of a dynamic system. In particular, a proposition based on a Lyapunov approach is proven to show the convergence of the approximation. The proven theorem is a constructive one and shows directly the suboptimality condition in the presence of noise. Based on these two results, an adaptive algorithm is conceived to calculate the derivative of a signal with convergence in infinite time. Results are compared with an approximation of the derivative using an adaptive Kalman filter (KF).

A New Improved Adaptive Algorithm in Gravity Anomaly Processing

2012 ◽  
Vol 466-467 ◽  
pp. 556-560
Author(s):  
Cheng Luo ◽  
Hong Sheng Li ◽  
Li Ye Zhao
Keyword(s):  
Kalman Filter ◽  
Gravity Anomaly ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Gravity Data ◽  
Adaptive Kalman Filter ◽  
Current Time ◽  
System Parameters ◽  
System Noise ◽  
Gravity System

In order to effectively eliminate the measurement and system noise and improve the accuracy of the gravity anomaly, based on the sage-husa filter, a modified adaptive Kalman filter is proposed. The sum of the weighted innovation sequence is used as the innovation at current time, and then system parameters Q and R can be estimated by the innovation. The adaptive algorithm is conducted theoretically and based on the real gravity data, the de-noising experiment has been emulated. The simulations indicate that both filters can effectively inhibit the noise of inertial/gravity system, but the proposed filter has a better performance than sage-husa adaptive filter.

Fuzzy adaptive Kalman filter for the drive system with an elastic coupling

2013 ◽  
Vol 62 (2) ◽  
pp. 251-265 ◽  
Author(s):  
Piotr J. Serkies ◽  
Krzysztof Szabat
Keyword(s):  
Kalman Filter ◽  
Control Structure ◽  
Experimental Tests ◽  
Drive System ◽  
Adaptive Kalman Filter ◽  
State Matrix ◽  
State Controller ◽  
Kalman Gain ◽  
Robust Adaptive ◽  
Fuzzy Adaptive

Abstract In the paper issues related to the design of a robust adaptive fuzzy estimator for a drive system with a flexible joint is presented. The proposed estimator ensures variable Kalman gain (based on the Mahalanobis distance) as well as the estimation of the system parameters (based on the fuzzy system). The obtained value of the time constant of the load machine is used to change the values in the system state matrix and to retune the parameters of the state controller. The proposed control structure (fuzzy Kalman filter and adaptive state controller) is investigated in simulation and experimental tests.

scholarly journals A new adaptive Kalman filter for navigation systems of carrier-based aircraft

2021 ◽  
Author(s):  
Lifei Zhang ◽  
Shaoping Wang ◽  
Maria Sergeevna Selezneva ◽  
Konstantin Avenirovich Neysipin
Keyword(s):  
Kalman Filter ◽  
Navigation Systems ◽  
Adaptive Kalman Filter
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