Publications by authors named "Javad Poshtan"

In this article, the robust fault detection and isolation (FDI) Kalman filter is extended based on stochastic event-triggered schedulers for discrete linear systems consisting of deterministic/stochastic unknown inputs with nonzero mean and colored measurement noise. In the proposed FDI method, first, a subspace of the main system that significantly attenuates disturbance effects is proposed. After that, the fusion method is proposed for dealing with the colored measurement-noise problem in designing the Kalman filter and preventing from leading to measurement noise with zero mean and zero covariance.

View Article and Find Full Text PDF

The problem of fault estimation for nonlinear systems with Lipschitz nonlinearities is addressed in this work for the estimation of both the system fault and states. In the proposed approach disturbance is regarded to be a function which is nonlinear and coupled with states of the system, and fault to be a function which is additive. In order to diagnose the fault and reduce the disturbances effects by dissipativity theory, Luenberger and two unknown input observers (UIOs) are designed separately.

View Article and Find Full Text PDF

In this paper, two approaches for robust state estimation of a class of Lipschitz nonlinear systems are proposed. First, a novel Unknown Input Observer (UIO) is designed without observer matching condition satisfaction. Then, an H observer for approximate disturbance decoupling is proposed.

View Article and Find Full Text PDF

The three-phase shift between line current and phase voltage of induction motors can be used as an efficient fault indicator to detect and locate inter-turn stator short-circuit (ITSC) fault. However, unbalanced supply voltage is one of the contributing factors that inevitably affect stator currents and therefore the three-phase shift. Thus, it is necessary to propose a method that is able to identify whether the unbalance of three currents is caused by ITSC or supply voltage fault.

View Article and Find Full Text PDF

Distributed Particle-Kalman Filter based observers are designed in this paper for inertial sensors (gyroscope and accelerometer) soft faults (biases and drifts) and rigid body pose estimation. The observers fuse inertial sensors with Photogrammetric camera. Linear and angular accelerations as unknown inputs of velocity and attitude rate dynamics, respectively, along with sensory biases and drifts are modeled and augmented to the moving body state parameters.

View Article and Find Full Text PDF

The Minimum Variance Lower Bound (MVLB) represents the best achievable controller capability in a variance sense. Estimation and realization of MVLB for nonlinear systems confront some difficulties. Hence, almost all methods introduced so far estimate MVLB for a certain structure (e.

View Article and Find Full Text PDF

Based on a cascaded Kalman-Particle Filtering, gyroscope drift and robot attitude estimation method is proposed in this paper. Due to noisy and erroneous measurements of MEMS gyroscope, it is combined with Photogrammetry based vision navigation scenario. Quaternions kinematics and robot angular velocity dynamics with augmented drift dynamics of gyroscope are employed as system state space model.

View Article and Find Full Text PDF

This paper deals with implementation of an optimal linear controller for a laboratory liquid four-tank system. A discrete linear model is used for modeling a class of MIMO nonlinear systems. It is shown that this model can identify these nonlinear systems with any desired accuracy, as a result the designed controller is accurate.

View Article and Find Full Text PDF

Designing minimum variance controllers (MVC) for nonlinear systems is confronted with many difficulties. The methods able to identify MIMO nonlinear systems are scarce. Harsh control signals produced by MVC are among other disadvantages of this controller.

View Article and Find Full Text PDF

Electric wheelchair (EW) is subject to diverse types of terrains and slopes, but also to occupants of various weights, which causes the EW to suffer from highly perturbed dynamics. A precise multivariable dynamics of the EW is obtained using Lagrange equations of motion which models effects of slopes as output-additive disturbances. A static pre-compensator is analytically devised which considerably decouples the EW's dynamics and also brings about a more accurate identification of the EW.

View Article and Find Full Text PDF

Electric wheelchairs (EW) experience various terrain surfaces and slopes as well as occupants with diverse weights. This, in turn, imparts a substantial amount of perturbation to the EW dynamics. In this paper, we make use of a two-degree-of-freedom control architecture called disturbance observer (DOB) which reduces sensitivity to model uncertainties, while enhancing rejection of disturbances caused due to entering slopes.

View Article and Find Full Text PDF

This paper presents a model-based fault detection approach for induction motors. A new filtering technique using Unscented Kalman Filter (UKF) and Extended Kalman Filter (EKF) is utilized as a state estimation tool for on-line detection of broken bars in induction motors based on rotor parameter value estimation from stator current and voltage processing. The hypothesis on which the detection is based is that the failure events are detected by jumps in the estimated parameter values of the model.

View Article and Find Full Text PDF