A Distributed Nonlinear Observer Design Method for Output Estimation in Nonlinear Systems

2011 ◽  
Author(s):  
Javad Mohammadpour ◽  
Ali Hooshmand ◽  
Heidar Malki ◽  
Karolos Grigoriadis ◽  
Robert Provence
Keyword(s):  
Nonlinear Systems ◽  
Design Method ◽  
Observer Design ◽  
Nonlinear Observer

scholarly journals A Continuous-Discrete Finite Memory Observer Design for a Class of Nonlinear Systems: Application to Fault Diagnosis

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Tingting Zhang ◽  
Frédéric Kratz ◽  
Yunhui Hou ◽  
Vincent Idasiak
Keyword(s):  
Nonlinear Systems ◽  
Control Charts ◽  
Nonlinear Dynamical Systems ◽  
Approximation Error ◽  
Time Instant ◽  
Fault Isolation ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Prediction Algorithm ◽  
Finite Memory

This paper aims to develop a continuous-discrete finite memory observer (CD-FMO) for a class of nonlinear dynamical systems modeled by ordinary differential equations (ODEs) with discrete measurements. The nonlinear systems under consideration are at least locally Lipschitz, which guarantees the existence and uniqueness of solution at each time instant. The proposed nonlinear observer uses a finite number of collected measurements to estimate the system state in the presence of measurement noise. Besides, a one-step prediction algorithm incorporated with an iterative-update scheme is performed to solve the integral problem caused by system nonlinearity, and an analysis of the numerical integration approximation error is given. The properties of estimation performance have been further proved in deterministic case and been analyzed by Monte Carlo simulation in stochastic cases. It is worth noting that the presented method has a finite-time convergence, while most nonlinear observers are usually asymptotically convergent. Another advantage of CD-FMO is that it has no initial value problem. For the application purpose, residuals are generated to implement fault detection cooperated with Cumulative Sum (CUSUM) control charts, while a bank of CD-FMOs is adopted to realize fault isolation for different sensor and actuator faults of the considered nonlinear robotic arm. The robustness and effectiveness of the proposed approach are illustrated via the simulation results.

Observe-Based Projective Synchronization of Chaotic Complex Modified Van Der Pol-Duffing Oscillator With Application to Secure Communication

2015 ◽  
Vol 10 (5) ◽  
Author(s):  
Ping Liu ◽  
Hongjun Song ◽  
Xiang Li
Keyword(s):  
Secure Communication ◽  
Chaotic Behavior ◽  
Design Method ◽  
Duffing Oscillator ◽  
Scaling Factor ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Projective Synchronization ◽  
Chaotic Oscillator ◽  
Van Der Pol

This paper addresses the projective synchronization (PS) of the complex modified Van der Pol-Duffing (MVDPD for short) chaotic oscillator by using the nonlinear observer control and also discusses its applications to secure communication in theory. First, we construct the complex MVDPD oscillator and analysis its chaotic behavior. Moreover, an observer design method is applied to achieve PS of two identical MVDPD chaotic oscillators with complex offset terms, which are synchronized to the desired scale factor. The unpredictability of the scaling factor could further enhance the security of the communication. Finally, numerical simulations are given to demonstrate the effectiveness and feasibility of the proposed synchronization approach and also verify the success application to the proposed scheme’s in the secure communication.

scholarly journals Development of Fuzzy Observer Gain Design Algorithm for Ship Path Estimation Based on AIS Data

Processes ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 33
Author(s):  
Chin-Lin Pen ◽  
Wen-Jer Chang ◽  
Yann-Horng Lin
Keyword(s):  
Dynamic Systems ◽  
Design Method ◽  
Fuzzy Model ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Automatic Identification ◽  
Identification System ◽  
Design Algorithm ◽  
Fuzzy Observer ◽  
Takagi Sugeno

This paper develops a Takagi-Sugeno fuzzy observer gain design algorithm to estimate ship motion based on Automatic Identification System (AIS) data. Nowadays, AIS data is widely applied in the maritime field. To solve the problem of safety, it is necessary to accurately estimate the trajectory of ships. Firstly, a nonlinear ship dynamic system is considered to represent the dynamic behaviors of ships. In the literature, nonlinear observer design methods have been studied to estimate the ship path based on AIS data. However, the nonlinear observer design method is challenging to create directly since some dynamic ship systems are more complex. This paper represents nonlinear ship dynamic systems by the Takagi-Sugeno fuzzy model. Based on the Takagi-Sugeno fuzzy model, a fuzzy observer design method is developed to solve the problem of estimating using AIS data. Moreover, the observer gains of the fuzzy observer can be adjusted systemically by a novel algorithm. Via the proposed algorithm, a more suitable or better observer can be obtained to achieve the objectives of estimation. Corresponding to different AIS data, the better results can also be obtained individually. Finally, the simulation results are presented to show the effectiveness and applicability of the proposed fuzzy observer design method. Some comparisons with the previous nonlinear observer design method are also given in the simulations.

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.

scholarly journals State Observer Design Method for a Class of Nonlinear Systems

2020 ◽  
Vol 53 (2) ◽  
pp. 4935-4940
Author(s):  
H. Arezki ◽  
A. Zemouche ◽  
F. Bedouhene ◽  
A. Alessandri ◽  
M.T. Laleg-Kirati
Keyword(s):  
Nonlinear Systems ◽  
Design Method ◽  
State Observer ◽  
Observer Design

Machine Diagnostics Using Nonlinear Output Observer and Neural Network Models

2000 ◽  
Author(s):  
Tor Fretheim ◽  
Rahmat Shoureshi ◽  
Tyrone Vincent ◽  
Duane Torgerson ◽  
John Work
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Fault Detection ◽  
Network Models ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Analytical Models ◽  
Neural Network Models ◽  
The Neural Network ◽  
Complex Nonlinear Systems

Abstract Predictive maintenance is rapidly becoming a familiar concept in industrial fault detection. The ability to detect early warning signals in systems in the form of small changes in dynamic behavior is essential to anticipate failures. In general, accurate system models are an essential part of residual based fault detection. However, in complex nonlinear systems, the development of accurate models can be very difficult, thus usually other approaches are often selected. As an alternative to the nonlinear analytical models, neural networks have shown significant potential in accurately representing nonlinear systems. In this paper we show how a system identified by a neural network, and a nonlinear observer can be used to detect changes in system dynamics. The neural network structure and identification have a significant impact on the observer performance. Different methods for observer design, and appropriate neural network structures for fault detection are discussed. The experimental section shows the observer implemented on a thermo fluid system. Several faults are introduced, and the observer prediction is compared to actual data.

Robust Observer Design for Lipschitz Nonlinear Systems With Parametric Uncertainty

2013 ◽  
Author(s):  
Yan Wang ◽  
David M. Bevly
Keyword(s):  
Nonlinear Systems ◽  
Vector Fields ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Performance Criteria ◽  
Adaptation Algorithm ◽  
Algebraic Set ◽  
Observer Error ◽  
Robust Observer ◽  
Lipschitz Nonlinear Systems

This paper discusses optimal and robust observer design for the Lipschitz nonlinear systems. The stability analysis for the Lure problem is first reviewed. Then, a two-DOF nonlinear observer is proposed so that the observer error dynamic model can be transformed to an equivalent Lure system. In this framework, the difference of the nonlinear parts in the vector fields of the original system and observer is modeled as a nonlinear memoryless block that is covered by a multivariable sector condition or an equivalent semi-algebraic set defined by a quadratic polynomial inequality. Then, a sufficient condition for asymptotic stability of the observer error dynamics is formulated in terms of the feasibility of polynomial matrix inequalities (PMIs), which can be solved by Lasserre’s moment relaxation. Furthermore, various quadratic performance criteria, such as H2 and H∞, can be easily incorporated in this framework. Finally, a parameter adaptation algorithm is introduced to cope with the parameter uncertainty.

Passivity-Based Disturbance Observer Design

2020 ◽  
Author(s):  
Ying-Chun Chen ◽  
Craig Woolsey
Keyword(s):  
Disturbance Observer ◽  
Design Method ◽  
Estimation Error ◽  
Parameter Tuning ◽  
Observer Design ◽  
Nonlinear Observer ◽  
Design Parameters ◽  
Nonlinear Feedback ◽  
Initial Application ◽  
Wide Range

Abstract A design method is proposed for a nonlinear disturbance observer based on the notion of passivity. As an initial application, we consider here systems whose structure comprises a set of integrator cascades, though the proposed approach can be extended to a larger class of systems. We describe an explicit procedure to choose the output of the system and to design the nonlinear feedback law used by the observer, provided the system satisfies a sufficient condition for output feedback semi-passification. The output injection term in the observer scales the measurement residual with a nonlinear gain that depends on the output and a set of static design parameters. We provide guidance for parameter tuning such that the disturbance tracking performance and the transient response of the estimation error can be intuitively adjusted. Example applications to two nonlinear mechanical systems illustrate that the proposed nonlinear observer design method is quite effective, producing an observer that can estimate a wide range of disturbances without any need to know or assume the disturbance dynamics.

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