Dynamic Positioning Observer Design Using Exogenous Kalman Filter

2019 ◽  
Author(s):  
Song An ◽  
Dengshuo Chen ◽  
Yong Bai
Keyword(s):  
Kalman Filter ◽  
Stability Property ◽  
Measurement Data ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Dynamic Positioning ◽  
Model Uncertainties ◽  
Process Noise ◽  
Second Stage ◽  
The Stability

Abstract Observer of a dynamic positioning (DP) system utilizes DP’s measurement data, to predict vessel’s velocities, positions, and unknown environmental forces on the vessel, as well as to handle model uncertainties and errors. Stability and optimality of a DP observer is important for overall DP performance. Nonlinear observer (NLO) designs usually take global asymptotic or exponential stability as the primary goal, and discard the noise. On the other hand, linearized Kalman filter (KF) algorithm, e.g. the extended Kalman filter (EKF), is optimal in minimizing the covariance of observer states by taking both measurement and process noise into account. The applied exogenous Kalman filter (XKF) algorithm in this paper, is a two-stage cascade of NLO and linearized KF, which uses the first-stage NLO estimated states as exogenous inputs for the second-stage linearized KF. XKF approach is proved to have both the stability property inherited from NLO and optimality from linearized KF. Stability and optimality of XKF based observer is studied through DP station-keeping numerical simulations.

scholarly journals A comparative study of nonlinear circle criterion based observer and H∞ observer for induction motor drive

2019 ◽  
Vol 10 (3) ◽  
pp. 1229
Author(s):  
Farid Berrezzek ◽  
Wafa Bourbia ◽  
Bachir Bensaker
Keyword(s):  
Comparative Study ◽  
Induction Motor ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Linear Matrix ◽  
Optimization Approach ◽  
Lmi Optimization ◽  
Circle Criterion ◽  
True State ◽  
The Stability

<span lang="EN-US">This paper deals with a comparative study of circle criterion based nonlinear observer<em> </em>and <em>H<sub>∞</sub></em> observer for induction motor (IM) drive. The  advantage of the circle criterion approach for nonlinear observer design is that it directly handles the nonlinearities of the system with less restriction  conditions in contrast of the other methods which attempt to eliminate them. However the <em>H<sub>∞</sub></em> observer guaranteed the stability taking into account disturbance and noise attenuation. Linear matrix inequality (LMI) optimization approach is used to compute the gains matrices for the two observers. The simulation results show the superiority of <em>H<sub>∞</sub></em> observer in the sense that it can achieve convergence to the true state, despite the nonlinearity of model and the presence of disturbance.</span>

Kalman Filter for Dynamic Positioning Ships Using Position and Acceleration Feedback

2014 ◽  
Vol 543-547 ◽  
pp. 2362-2367
Author(s):  
Ye Hai Xie
Keyword(s):  
Computer Simulation ◽  
Kalman Filter ◽  
Stability Theory ◽  
Linear Acceleration ◽  
Dynamic Positioning ◽  
Positioning Systems ◽  
Measured Position ◽  
Acceleration Feedback ◽  
The Stability

Considering the problem of dynamic positioning Systems for the slowly-varying disturbances, a new kalman filter using position and acceleration feedback is presented. The kalman filiter separates the WF motions from the measured position and linear acceleration, and estimates the LF position, velocity and acceleration. The stability of this filiter is proven by applying input-to-state (ISS) stability theory. Finally, the computer simulation is given to demonstrate the effectiveness of the proposed method.

Robust dynamic sliding mode observer design for a class of nonlinear systems

2020 ◽  
pp. 014233122095220
Author(s):  
Mahnoosh Shajiee ◽  
Seyed Kamal Hosseini Sani ◽  
Mohammad Bagher Naghibi-Sistani ◽  
Saeed Shamaghdari
Keyword(s):  
Nonlinear Systems ◽  
Sliding Mode ◽  
Lipschitz Constant ◽  
Design Procedure ◽  
Sliding Mode Observer ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Dynamical Structure ◽  
Additional Degree ◽  
The Stability

In this paper, a novel method for the design of robust nonlinear observer in the [Formula: see text] framework for Lipschitz nonlinear systems is proposed. For this purpose, a new dynamical structure is introduced that ensures the stability of observer error dynamics. Design innovation is the use of dynamic gain in the sliding mode observer. The additional degree of freedom provided by this dynamic formulation is exploited to deal with the nonlinear term. The performance of this stable [Formula: see text] observer is better than conventional static gain observers and the dynamic Luenberger observer. The compensator is designed in such a way that, while ensuring the stability of the closed-loop system, it prevents performance loss in the presence of the nonlinearities. By the proposed approach, the observer is robust to nonlinear uncertainties because of increasing the Lipschitz constant. Also, the design procedure in the presence of system and measurement noises is addressed. Finally, the simulation of our methodology is conducted on a nonlinear system to illustrate the advantage of this work in comparison with other observers.

Quadrotor Position Control Using Cascaded Adaptive Integral Backstepping Controllers

2014 ◽  
Vol 565 ◽  
pp. 98-106 ◽  
Author(s):  
Younes Al Younes ◽  
Ahmad Drak ◽  
Hassan Noura ◽  
Abdelhamid Rabhi ◽  
Ahmed El Hajjaji
Keyword(s):  
Position Control ◽  
Control Technique ◽  
Test Results ◽  
Model Uncertainties ◽  
Second Stage ◽  
Integral Action ◽  
Modeling Errors ◽  
The Stability ◽  
Adaptation Law ◽  
Two Stages

This paper proposes a nonlinear control technique to control the position of the Qball-X4 quadrotor using a cascaded methodology of two Adaptive Integral Backstepping Controllers (AIBC). The nonlinear algorithm uses the principle of Lyapunov methodology in the backstepping technique to ensure the stability of the vehicle, and utilizes the integral action to eliminate the steady state error that caused by the disturbances and model uncertainties, as well as, the adaptation law will estimate the modeling errors caused by assumptions in simplifying the complexity of the quadrotor model. The algorithm goes through two stages of cascaded AIBCs; the first stage aims to stabilize the attitude and the altitude of the quadrotor, and the second stage feeds the first stage with the desired attitude values to control the position of the quadrotor.Flight test results show that the proposed algorithm is capable of controlling the position of the nonlinear quadrotor model.

Invariant observer design for scan matching-aided localization: A tutorial

2018 ◽  
Vol 66 (3) ◽  
pp. 195-212
Author(s):  
Martin Barczyk
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Design Methodology ◽  
Mobile Robotics ◽  
Filter Design ◽  
Observer Design ◽  
Nonlinear Observer ◽  
The Novel ◽  
Scan Matching ◽  
Filter Approach

Abstract Aided localization, a nonlinear observer design problem, is critical to a range of mobile robotics applications. This paper provides a tutorial presentation of the required background, design steps and calculations of a scan matching-aided localization observer using the novel invariant (symmetry-preserving) observer design methodology. The Invariant Extended Kalman Filter approach is used to systematically obtain the gains of the resulting design, and compared against a conventional, non-invariant Extended Kalman Filter design.

Robust nonlinear observer for forward kinematics solution of a Stewart platform: an experimental verification

Robotica ◽  
2000 ◽  
Vol 18 (6) ◽  
pp. 601-610 ◽  
Author(s):  
Dong Hwan Kim ◽  
Ji-Yoon Kang ◽  
Kyo-Il Lee
Keyword(s):  
Estimation Error ◽  
Stewart Platform ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Forward Kinematics ◽  
Design Algorithm ◽  
Error Dynamics ◽  
The Stability ◽  
Robust Nonlinear Observer ◽  
Nonlinear Robust

A 6-DOF motion bed is proposed as a nonlinear robust observer to solve the forward kinematics problem of a Stewart platform. The stability of the estimation error dynamics is proved via Lyapunov stability analysis and the error dynamics shows practical stability. An observer design algorithm which tackles the nonlinearity and uncertainty both in the system and in the output is presented by a new arithmetic Riccati equation. The estimation performance for the algorithm is verified using both simulations and experiments. The equation employs the bounding condition computed from the platform dynamics.

A nonlinear fractional-order H∞ observer for SOC estimation of battery pack of electric vehicles

2021 ◽  
pp. 095440702199434
Author(s):  
Wei Yue ◽  
Cong-zhi Liu ◽  
Liang Li ◽  
Xiang Chen ◽  
Fahad Muhammad
Keyword(s):  
Fractional Order ◽  
Estimation Method ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Open Circuit ◽  
Design Criterion ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Battery Pack ◽  
Soc Estimation

This work is focused on designing a fractional-order [Formula: see text] observer and applying it into the state of charge (SOC) estimation for lithium-ion battery pack system. Firstly, a fractional order equivalent circuit model based on the fractional capacitor is established and identified. Secondly, the SOC estimation method based on the fractional-order [Formula: see text] observer is proposed. The nonlinear intrinsic relationship between the open-circuit voltage and SOC is described as a polynomial function, and its Lipschitz proposition has been discussed. Then, the nonlinear observer design criterion is established based on the Lyapunov method. Finally, the effectiveness of the proposed method is verified with high accuracy and robustness by the experiment results.

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