scholarly journals Identification, Estimation, and Control for Linear Uncertain Systems Using Measurements of Higher-Order Derivatives

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Zilong Shao ◽  
Gang Zheng ◽  
Denis Efimov ◽  
Wilfrid Perruquetti
Keyword(s):  
Uncertain Systems ◽  
Initial Conditions ◽  
Higher Order ◽  
The State ◽  
Identification Algorithm ◽  
Unknown Parameters ◽  
State Variable ◽  
Higher Order Derivative ◽  
Estimation And Control ◽  
And Control

In this paper, the problem of output control for linear uncertain systems with external perturbations is studied. First, it is assumed that the output available for measurement is only the higher-order derivative of the state variable, instead of the state variable itself (for example, the acceleration for a second-order plant), and the measurement is also corrupted by noise. Then, via series of integration, an identification algorithm is proposed to identify all unknown parameters of the model and all unknown initial conditions of the state vector. Finally, two control algorithms are developed, adaptive and robust; both provide boundedness of trajectories of the system. The efficiency of the obtained solutions is demonstrated by numerical simulation.

Difference Synchronization of Identical and Nonidentical Chaotic and Hyperchaotic Systems of Different Orders Using Active Backstepping Design

2018 ◽  
Vol 13 (5) ◽  
Author(s):  
Eric Donald Dongmo ◽  
Kayode Stephen Ojo ◽  
Paul Woafo ◽  
Abdulahi Ndzi Njah
Keyword(s):  
Chaotic System ◽  
Initial Conditions ◽  
Lyapunov Stability Theory ◽  
The State ◽  
State Variables ◽  
State Variable ◽  
New Type ◽  
The Difference ◽  
Synchronization Scheme ◽  
Hyperchaotic Systems

This paper introduces a new type of synchronization scheme, referred to as difference synchronization scheme, wherein the difference between the state variables of two master [slave] systems synchronizes with the state variable of a single slave [master] system. Using the Lyapunov stability theory and the active backstepping technique, controllers are derived to achieve the difference synchronization of three identical hyperchaotic Liu systems evolving from different initial conditions, as well as the difference synchronization of three nonidentical systems of different orders, comprising the 3D Lorenz chaotic system, 3D Chen chaotic system, and the 4D hyperchaotic Liu system. Numerical simulations are presented to demonstrate the validity and feasibility of the theoretical analysis. The development of difference synchronization scheme has increases the number of existing chaos synchronization scheme.

Strongly consistent estimation in a controlled Markov renewal model

1982 ◽  
Vol 19 (03) ◽  
pp. 532-545 ◽  
Author(s):  
Michael Kolonko
Keyword(s):  
Optimal Control ◽  
Dynamic Models ◽  
Consistent Estimation ◽  
Unknown Parameters ◽  
Control Approach ◽  
Renewal Model ◽  
Countable State ◽  
Estimation And Control ◽  
And Control ◽  
Strongly Consistent

The optimal control of dynamic models which are not completely known to the controller often requires some kind of estimation of the unknown parameters. We present conditions under which a minimum contrast estimator will be strongly consistent independently of the control used. This kind of estimator is appropriate for the adaptive or ‘estimation and control' approach in dynamic programming under uncertainty. We consider a countable-state Markov renewal model and we impose bounding and recurrence conditions of the so-called Liapunov type.

Koopman Operators for Estimation and Control of Dynamical Systems

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Samuel E. Otto ◽  
Clarence W. Rowley
Keyword(s):  
Numerical Methods ◽  
Autonomous Systems ◽  
The State ◽  
Annual Review ◽  
Publication Date ◽  
Control Input ◽  
Koopman Operator ◽  
Estimation And Control ◽  
And Control ◽  
Theoretical Foundations

A common way to represent a system's dynamics is to specify how the state evolves in time. An alternative viewpoint is to specify how functions of the state evolve in time. This evolution of functions is governed by a linear operator called the Koopman operator, whose spectral properties reveal intrinsic features of a system. For instance, its eigenfunctions determine coordinates in which the dynamics evolve linearly. This review discusses the theoretical foundations of Koopman operator methods, as well as numerical methods developed over the past two decades to approximate the Koopman operator from data, for systems both with and without actuation. We pay special attention to ergodic systems, for which especially effective numerical methods are available. For nonlinear systems with an affine control input, the Koopman formalism leads naturally to systems that are bilinear in the state and the input, and this structure can be leveraged for the design of controllers and estimators. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals The scientific analysis of risks in life-support of a person, a society and the state

2019 ◽  
Vol 16 (2) ◽  
pp. 70-86 ◽  
Author(s):  
N. A. Makhutov ◽  
M. M. Gadenin ◽  
O. N. Yudina
Keyword(s):  
Life Support ◽  
Quantitative Measure ◽  
The State ◽  
Emergency Situations ◽  
Base Parameters ◽  
Scientific Analysis ◽  
Depth Analysis ◽  
Key Factor ◽  
Estimation And Control ◽  
And Control

It is showed that the key factor at the solution of problems of an estimation and control of risks for social, natural and technogenic spheres is use of the concept of the analysis and monitoring of the risks, founded on determination of base parameters of a current and probable dangerous state of analyzed socially-natural-technogenic system. Importance of safety maintenance and protect-ability tasks of basic practices and appearances in such system is interlinked to spreading of scientific possibilities and actual methods of decrease of risks, and also with an in-depth analysis of a spectrum of dangers, defiances, threats, crises, emergency situations, disasters at increment of losses from them to a person, a society, the state, an environment and an ability to live of infrastructure. The universal quantitative measure of probabilities of initiation and implementation of the indicated unfavorable events and processes in a combination to accompanying them losses are risks of the stacked state and prospects of evolution of considered system. Builted on results of corresponding comprehensive analysis the theory, algorithms and program complexes for determination, maintenances and raises of protectability of objects in social, natural and technogenic spheres taking into account the bundled to them risks are scientific baseline for a justification of decrease of their interlinked values to acceptable level. Making and service of objects and an infrastructure of ability to live for a person, a society and the state on the basis of a meeting the requirements to acceptable levels of risks and to guard of objects from accidents and disasters present an essence of transition to new level of the state strategic planning certified to the strategy of national safety of Russia.

Strongly consistent estimation in a controlled Markov renewal model

1982 ◽  
Vol 19 (3) ◽  
pp. 532-545 ◽  
Author(s):  
Michael Kolonko
Keyword(s):  
Optimal Control ◽  
Dynamic Models ◽  
Consistent Estimation ◽  
Unknown Parameters ◽  
Control Approach ◽  
Renewal Model ◽  
Countable State ◽  
Estimation And Control ◽  
And Control ◽  
Strongly Consistent

The optimal control of dynamic models which are not completely known to the controller often requires some kind of estimation of the unknown parameters. We present conditions under which a minimum contrast estimator will be strongly consistent independently of the control used. This kind of estimator is appropriate for the adaptive or ‘estimation and control' approach in dynamic programming under uncertainty. We consider a countable-state Markov renewal model and we impose bounding and recurrence conditions of the so-called Liapunov type.

scholarly journals Approximate Model-based State Estimation in Simplified Receding Horizon Control

2021 ◽  
Vol 15 ◽  
pp. 114-124
Author(s):  
Hemza Redjimi ◽  
József K. Tar
Keyword(s):  
Approximate Model ◽  
The State ◽  
Control Signal ◽  
Measured Quantity ◽  
State Variables ◽  
Receding Horizon ◽  
Applied Model ◽  
State Variable ◽  
Multiple Variable ◽  
And Control

Multiple variable systems often have to be so controlled that in the lack of appropriate sensors no satisfactory information is available for the complete estimation of their state variables. Normally only their certain components are kept under observation and control, while the other ones evolve according to the consequences of the exerted control signal. In control-based treatment of patients suffering from "Type 1 Diabetes Mellitus (T1DM)", the only directly measured quantity is the subcutaneous glucose concentration in the blood controlled by a single control signal, the insulin ingress rate. The applied model may use several components in the state variable. The traditional "Receding Horizon Controller (RHC)" requires the estimation of the complete state variable for the calculation of the control signal. In this paper preliminary simulations are persented in which the operation of the RHC is studied in the control of two vertically connected, oscillating masspoints so coupled by springs that only the state of the upper one is observed and directly controlled. Instead sensor-based observations, the lower point’s coordinate is calculated by the use of an available "rough" model. Preliminary calculations were made for a particular human glucose-insulin model, too. In the implementation of the RHC special simplifications were introduced. In our further work we wish to apply this method for investigating various T1DM treatment models.

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.

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