One of the most important problems when designing controller is how to deal with all kinds of uncertainties, which, along with the high nonlinearities of most real systems, makes it difficult to guarantee the desired closed loop performance. Recently, nonlinear Kalman-class filter has been extensively researched and several well-known algorithms, including Extended Kalman Filter (EKF), Unscente...

Several groups have proposed the state-space approach to tracking time-varying frequencies of multiharmonic quasiperiodic signals. The extended Kalman filter/smoother (EKF/EKS) is one of the common frequency tracking approaches seen in the literature. We introduce a multiharmonic frequency tracker based on the forward-backward statistical linearized Sigma-Point Kalman smoother (FBSL-SPKS) and c...

To ensure safe operation of unmanned aerial vehicles (UAVs), component hazards need to be dealt with robustly through effective fault diagnosis. The extended Kalman filter (EKF) has proven popular in this realm, though it is known to suffer from linearisation errors that can degrade performance. This paper presents results from initial simulation trials that address sensor fault detection and i...

This paper presents a Discrete-Time Variable-Structure Control (DTVSC) for the dynamic positioning system of a marine supply vessel. The DTVSC guarantees robustness with respect to disturbances and parametric variations. Two wave-filtering approaches are employed: the Extended Kalman filter (EKF) and the multi-rate Kalman filter (MREKF) . The proposed solution is compared with a PID-based contr...

With the recent advance of deep learning based object recognition and estimation, it is possible to consider level SLAM where pose each estimated in process. In this letter, on a novel Lie group structure, right invariant extended Kalman filter (RI-EKF) for proposed. The observability analysis shows that proposed algorithm automatically maintains correct unobservable subspace, while standard EK...

When Extended Kalman Filter is used to solve the SLAM problem of a nonlinear system, the linearization error will lead to severe estimation error or even make the method to be divergent. After analyzing the linearization principle of Kalman filters family, two improved methods are suggested to decrease the linearization error. These two methods improve posterior estimation accuracy by revising ...

This paper presents the Optimized Kalman Particle Swarm (OKPS) filter. This filter results from two years of research and improves the Swarm Particle Filter (SPF). The OKPS has been designed to be both cooperative and reactive. It combines the advantages of the Particle Filter (PF) and the metaheuristic Particle Swarm Optimization (PSO) for ego-vehicles localization applications. In addition to...

A convergence analysis of the modified unscented Kalman filter (UKF), used as an observer for a class nonlinear deterministic continuous time systems, is presented. Under certain conditions, extended (EKF) exponential non-linear i.e., dynamics estimation error exponentially stable. It shown that unlike EKF, UKF not converging observer. modification – proposed, which better candidate This paper ...

In this paper, a new robust extended Kalman filtering algorithm based on singular value decomposition (SVD) of covariance / information matrix is presented with application in the flight state and parameter estimation of aircraft. The presented algorithm not only has a good numerical stability but also can handle correlated measurement noise without any additional transformation. The algorithm ...

In this paper, a new sensorless Interior Permanent Magnet Synchronous Motor (IPMSM) drives method with Extended Kalman Filter (EKF) for speed, rotor position and load torque estimation is proposed. The Direct Torque Control (DTC) technique for PMSM is receiving increasing attention due to the important advantages of the low dependence on motor parameters when compared with other motor control t...