Adaptive Variational Bayesian Extended Kalman Filtering for Nonlinear Systems

2013 ◽  
Author(s):  
Ding-Jie Xu ◽  
Chen Shen ◽  
Feng Shen
Keyword(s):  
Nonlinear Systems ◽  
Kalman Filtering ◽  
Extended Kalman Filtering ◽  
Variational Bayesian

scholarly journals Distributed Adaptive High-Gain Extended Kalman Filtering for Nonlinear systems

2015 ◽  
Vol 48 (8) ◽  
pp. 158-163 ◽  
Author(s):  
Mohammad Rashedi ◽  
Jinfeng Liu ◽  
Biao Huang
Keyword(s):  
Nonlinear Systems ◽  
Kalman Filtering ◽  
High Gain ◽  
Extended Kalman Filtering

scholarly journals Stochastic Optimal Control with Application in Visual Servoing

2021 ◽  
Author(s):  
Aidin Foroughi
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Kalman Filtering ◽  
Stochastic Optimal Control ◽  
Visual Servoing ◽  
Inverted Pendulum ◽  
Extended Kalman Filtering ◽  
Risk Seeking ◽  
Novel Method ◽  
Control Methodology

In this thesis, a new inference-based solution to stochastic optimal control (SOC) for general nonlinear systems is developed. This novel method applies to standard SOC problem, as well as robust and risk-seeking variations. The presented approach unifies many existing works, and makes possible, inference-based approximations to be applied to robust, risk-seeking, and standard SOC problems. Thus, an approximate method based on extended Kalman filtering is developed and tested on the inverted pendulum problem, and compared with existing methods. As an application, the developed algorithm was adapted to a practically important problem in visual control in robotics known as image-based visual servoing (IBVS). The proposed control methodology for visual servoing was implemented for real-time experiments, and was compared with the standard IBVS methodology. The experimental results show that the proposed method can improve the myopic behaviors of standard IBVS methodology.

scholarly journals An Enhanced UWB-Based Range/GPS Cooperative Positioning Approach Using Adaptive Variational Bayesian Cubature Kalman Filtering

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Feng Shen ◽  
Guanghui Xu
Keyword(s):  
Kalman Filtering ◽  
Intelligent Transportation Systems ◽  
Ad Hoc ◽  
Transportation Systems ◽  
Global Navigation Satellite Systems ◽  
Extended Kalman Filtering ◽  
Precise Position ◽  
Variational Bayesian ◽  
Satellite Systems ◽  
Cooperative Positioning

Precise position awareness is a fundamental requirement for advanced applications of emerging intelligent transportation systems, such as collision warning and speed advisory system. However, the achievable level of positioning accuracy using global navigation satellite systems does not meet the requirements of these applications. Fortunately, cooperative positioning (CP) techniques can improve the performance of positioning in a vehicular ad hoc network (VANET) through sharing the positions between vehicles. In this paper, a novel enhanced CP technique is presented by combining additional range-ultra-wide bandwidth- (UWB-) based measurements. Furthermore, an adaptive variational Bayesian cubature Kalman filtering (AVBCKF) algorithm is proposed and used in the enhanced CP method, which can add robustness to the time-variant measurement noise. Based on analytical and experimental results, the proposed AVBCKF-based CP method outperforms the cubature Kalman filtering- (CKF-) based CP method and extended Kalman filtering- (EKF-) based CP method.

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