scholarly journals Nonlinear State Estimation and Control for Chaos Suppression in MEMS Resonator

2013 ◽  
Vol 20 (4) ◽  
pp. 749-761 ◽  
Author(s):  
Angelo Marcelo Tusset ◽  
Átila Madureira Bueno ◽  
Claudinor Bitencourt Nascimento ◽  
Mauricio dos Santos Kaster ◽  
José Manoel Balthazar
Keyword(s):  
State Estimation ◽  
Multiple Scales ◽  
Chaotic Behavior ◽  
Control Strategies ◽  
The State ◽  
Linear Feedback ◽  
Chaos Suppression ◽  
State Dependent ◽  
Mems Resonators ◽  
Estimation And Control

During the last decade the chaotic behavior in MEMS resonators have been reported in a number of works. Here, the chaotic behavior of a micro-mechanical resonator is suppressed. The aim is to control the system forcing it to an orbit of the analytical solution obtained by the multiple scales method. The State Dependent Riccati Equation (SDRE) and the Optimal Linear Feedback Control (OLFC) strategies are used for controlling the trajectory of the system. Additionally, the SDRE technique is used in the state estimator design. The state estimation and the control techniques proved to be effective in controlling the trajectory of the system. Additionally, the robustness of the control strategies are tested considering parametric errors and measurement noise in the control loop.

Identification and State Observation of Uncertain Chaotic Systems Using Projectional Differential Neural Networks

2011 ◽  
pp. 42-67
Author(s):  
Alejandro García ◽  
Isaac Chairez ◽  
Alexander Poznyak
Keyword(s):  
Neural Network ◽  
State Estimation ◽  
Chaotic Systems ◽  
Chaotic Behavior ◽  
The State ◽  
State Variables ◽  
Neural Network Approach ◽  
State Observation ◽  
The Neural Network ◽  
Uncertain Chaotic Systems

The following chapter tackles the nonparametric identification and the state estimation for uncertain chaotic systems by the dynamic neural network approach. The developed algorithms consider the presence of additive noise in the state, for the case of identification, and in the measurable output, for the state estimation case. Mathematical model of the chaotic system is considered unknown, only the chaotic behavior as well as the maximal and minimal bound for each one of state variables are taking into account in the algorithm. Mathematical analysis and simulation results are presented. Application considering the so-called electronic Chua’s circuit is carried out; particularly a scheme of information encryption by the neural network observer with a noisy transmission is showed. Formal mathematical proofs and figures, illustrate the robustness of proposed algorithms mainly in the presence of noises with high magnitude.

Nonlinear State Estimation Using Aggregate Modeling

2007 ◽  
Author(s):  
Kiriakos Kiriakidis ◽  
Matthew Feemster ◽  
Richard T. O’Brien
Keyword(s):  
State Estimation ◽  
Estimation Error ◽  
The State ◽  
Linear Feedback ◽  
Aggregate Model ◽  
Nonlinear State Estimation ◽  
Aggregate Modeling ◽  
Error Dynamics ◽  
The Stability ◽  
Nonlinear State

The paper addresses the state estimation problem for a general class of nonlinear systems. Using an expansion of nonlinear drift dynamics in terms of an aggregate model, the authors analyze the stability of the estimation error equation. Although the treatment is limited to linear feedback, the method results in quadratically stable error dynamics inside a large subset of the state space. The authors tested and verified the proposed approach on the nonlinear dynamics of the rotary pendulum.

State Estimation and Control of an Unmanned Air Vehicle from a Ground-Based 3D Laser Scanner

2016 ◽  
Vol 28 (6) ◽  
pp. 878-886 ◽  
Author(s):  
Ryan Arya Pratama ◽  
◽  
Akihisa Ohya
Keyword(s):  
State Estimation ◽  
Position Control ◽  
Laser Scanner ◽  
Low Frequency ◽  
The State ◽  
Velocity Control ◽  
Unmanned Air Vehicle ◽  
Air Vehicle ◽  
Estimation And Control ◽  
And Control

[abstFig src='/00280006/12.jpg' width='300' text='UAV state estimation from laser scanner' ] In this work, we present a system to estimate the state of and control an Unmanned Air Vehicle (UAV) from a ground-based 3D laser scanner. The main contributions of this work are on data fusion between a low-frequency 3D laser scanner with considerable delay and an on-board 6-DOF IMU, and on automatic position control of a UAV using state estimate obtained from the fusion. We measured laser delay using data from a manually controlled flight. We have devised a method to perform online estimation and compensation of accelerometer offset using delay-corrected laser measurement. We then use the UAV state estimation in a nested controller with a high-frequency velocity control inner loop and a low-frequency position control outer loop. We demonstrated the state estimation and control in a series of experiments on velocity control and position control, including a comparison between position control using fusion data and only laser data.

Analyzing the State Estimation Software Package Reliability Using the Fault Tree Technology

2018 ◽  
Vol 6 (6) ◽  
pp. 24-34
Author(s):  
Irina N. KOLOSOK ◽  
◽  
Elena S. KORKINA ◽  
Alexandr V. TIKHONOV ◽  
◽  
...  
Keyword(s):  
State Estimation ◽  
Software Package ◽  
Fault Tree ◽  
The State ◽  
Package Reliability

State Estimation Using Randomly Delayed Measurements

1993 ◽  
Vol 115 (1) ◽  
pp. 19-26 ◽  
Author(s):  
A. Ray ◽  
L. W. Liou ◽  
J. H. Shen
Keyword(s):  
State Estimation ◽  
Minimum Variance ◽  
The State ◽  
Sensor Data ◽  
State Estimator ◽  
Uniform Asymptotic Stability ◽  
Simulation Experiments ◽  
State Estimate ◽  
Sampling Instant ◽  
Recursive Relations

This paper presents a modification of the conventional minimum variance state estimator to accommodate the effects of randomly varying delays in arrival of sensor data at the controller terminal. In this approach, the currently available sensor data is used at each sampling instant to obtain the state estimate which, in turn, can be used to generate the control signal. Recursive relations for the filter dynamics have been derived, and the conditions for uniform asymptotic stability of the filter have been conjectured. Results of simulation experiments using a flight dynamic model of advanced aircraft are presented for performance evaluation of the state estimation filter.

scholarly journals A Two-Step State Estimation Algorithm for Hybrid AC-DC Distribution Grids

Energies ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 1967
Author(s):  
Gaurav Kumar Roy ◽  
Marco Pau ◽  
Ferdinanda Ponci ◽  
Antonello Monti
Keyword(s):  
State Estimation ◽  
Distribution System ◽  
Renewable Energy Sources ◽  
Estimation Algorithm ◽  
The State ◽  
Second Step ◽  
Distribution Grid ◽  
Dc Distribution ◽  
Attractive Option ◽  
Distribution Grids

Direct Current (DC) grids are considered an attractive option for integrating high shares of renewable energy sources in the electrical distribution grid. Hence, in the future, Alternating Current (AC) and DC systems could be interconnected to form hybrid AC-DC distribution grids. This paper presents a two-step state estimation formulation for the monitoring of hybrid AC-DC grids. In the first step, state estimation is executed independently for the AC and DC areas of the distribution system. The second step refines the estimation results by exchanging boundary quantities at the AC-DC converters. To this purpose, the modulation index and phase angle control of the AC-DC converters are integrated into the second step of the proposed state estimation formulation. This allows providing additional inputs to the state estimation algorithm, which eventually leads to improve the accuracy of the state estimation results. Simulations on a sample AC-DC distribution grid are performed to highlight the benefits resulting from the integration of these converter control parameters for the estimation of both the AC and DC grid quantities.

scholarly journals State Estimation for Cooperative Lateral Vehicle Following Using Vehicle-to-Vehicle Communication

Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 651
Author(s):  
Wouter Schinkel ◽  
Tom van der Sande ◽  
Henk Nijmeijer
Keyword(s):  
State Estimation ◽  
Cooperative Control ◽  
The State ◽  
State Estimator ◽  
Estimation Process ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Control Schemes ◽  
Input Signals ◽  
Vehicle To Vehicle Communication

A cooperative state estimation framework for automated vehicle applications is presented and demonstrated via simulations, the estimation framework is used to estimate the state of a lead and following vehicle simultaneously. Recent developments in the field of cooperative driving require novel techniques to ensure accurate and stable vehicle following behavior. Control schemes for the cooperative control of longitudinal and lateral vehicle dynamics generally require vehicle state information about the lead vehicle, which in some cases cannot be accurately measured. Including vehicle-to-vehicle communication in the state estimation process can provide the required input signals for the practical implementation of cooperative control schemes. This study is focused on demonstrating the benefits of using vehicle-to-vehicle communication in the state estimation of a lead and following vehicle via simulations. The state estimator, which uses a cascaded Kalman filtering process, takes the operating frequencies of different sensors into account in the estimation process. Simulation results of three different driving scenarios demonstrate the benefits of using vehicle-to-vehicle communication as well as the attenuation of measurement noise. Furthermore, in contrast to relying on low frequency measurement data for the input signals of cooperative control schemes, the state estimator provides a state estimate at every sample.

scholarly journals Methodology for Implementing the State Estimation in Renewable Energy Management Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2301
Author(s):  
Yun-Sung Cho ◽  
Yun-Hyuk Choi
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
State Estimation ◽  
Measurement Errors ◽  
Large Scale ◽  
Test System ◽  
The State ◽  
Inner Function ◽  
Outer Function ◽  
Bad Data

This paper describes a methodology for implementing the state estimation and enhancing the accuracy in large-scale power systems that partially depend on variable renewable energy resources. To determine the actual states of electricity grids, including those of wind and solar power systems, the proposed state estimation method adopts a fast-decoupled weighted least square approach based on the architecture of application common database. Renewable energy modeling is considered on the basis of the point of data acquisition, the type of renewable energy, and the voltage level of the bus-connected renewable energy. Moreover, the proposed algorithm performs accurate bad data processing using inner and outer functions. The inner function is applied to the largest normalized residue method to process the bad data detection, identification and adjustment. While the outer function is analyzed whether the identified bad measurements exceed the condition of Kirchhoff’s current law. In addition, to decrease the topology and measurement errors associated with transformers, a connectivity model is proposed for transformers that use switching devices, and a transformer error processing technique is proposed using a simple heuristic method. To verify the performance of the proposed methodology, we performed comprehensive tests based on a modified IEEE 18-bus test system and a large-scale power system that utilizes renewable energy.

Sign in / Sign up

Export Citation Format

Share Document