scholarly journals Global Stabilization of Nonlinear Finite Dimensional System with Dynamic Controller Governed by 1 − d Heat Equation with Neumann Interconnection

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 227
Author(s):  
Mohsen Dlala ◽  
Abdallah Benabdallah
Keyword(s):  
State Feedback ◽  
Linear Part ◽  
Coupled System ◽  
High Gain ◽  
Dimensional System ◽  
Nonlinear Part ◽  
Infinite Dimensional ◽  
Dynamic Controller ◽  
Finite Dimensional ◽  
Linear Growth Condition

This paper deals with the stabilization of a class of uncertain nonlinear ordinary differential equations (ODEs) with a dynamic controller governed by a linear 1−d heat partial differential equation (PDE). The control operates at one boundary of the domain of the heat controller, while at the other end of the boundary, a Neumann term is injected into the ODE plant. We achieve the desired global exponential stabilization goal by using a recent infinite-dimensional backstepping design for coupled PDE-ODE systems combined with a high-gain state feedback and domination approach. The stabilization result of the coupled system is established under two main restrictions: the first restriction concerns the particular classical form of our ODE, which contains, in addition to a controllable linear part, a second uncertain nonlinear part verifying a lower triangular linear growth condition. The second restriction concerns the length of the domain of the PDE which is restricted.

Predictor Feedback of Uncertain Single-Input Systems

2020 ◽  
pp. 235-266
Author(s):  
Yang Zhu ◽  
Miroslav Krstic
Keyword(s):  
Output Feedback ◽  
State Feedback ◽  
System Matrix ◽  
Unknown Parameters ◽  
Infinite Dimensional ◽  
Finite Dimensional ◽  
Linear Plant ◽  
Single Input ◽  
Distributed Actuator

This chapter presents the predictor feedback for uncertain single-input systems. This is based on the predictor feedback framework for uncertainty-free single-input systems in the previous chapter. The chapter addresses the five combinations of the five uncertainties that come from a single-input linear plant with distributed actuator delay. These uncertainties include the following types: unknown delay, unknown delay kernel, unknown parameters in the system matrix, unmeasurable finite-dimensional plant state, and unmeasurable infinite-dimensional actuator state. The chapter then studies adaptive state feedback under unknown delay, delay kernel, and parameter. It also assesses robust output feedback under unknown delay, delay kernel, and PDE or ODE state.

scholarly journals The initial value problem in Lagrangian drift kinetic theory

2016 ◽  
Vol 82 (3) ◽  
Author(s):  
J. W. Burby
Keyword(s):  
Phase Space ◽  
Kinetic Theory ◽  
Initial Value Problem ◽  
High Order ◽  
Dimensional System ◽  
Initial Value ◽  
Infinite Dimensional ◽  
Finite Dimensional ◽  
Basic Philosophy ◽  
System Phase

Existing high-order variational drift kinetic theories contain unphysical rapidly varying modes that are not seen at low orders. These unphysical modes, which may be rapidly oscillating, damped or growing, are ushered in by a failure of conventional high-order drift kinetic theory to preserve the structure of its parent model’s initial value problem. In short, the (infinite dimensional) system phase space is unphysically enlarged in conventional high-order variational drift kinetic theory. I present an alternative, ‘renormalized’ variational approach to drift kinetic theory that manifestly respects the parent model’s initial value problem. The basic philosophy underlying this alternate approach is that high-order drift kinetic theory ought to be derived by truncating the all-orders system phase-space Lagrangian instead of the usual ‘field$+$particle’ Lagrangian. For the sake of clarity, this story is told first through the lens of a finite-dimensional toy model of high-order variational drift kinetics; the analogous full-on drift kinetic story is discussed subsequently. The renormalized drift kinetic system, while variational and just as formally accurate as conventional formulations, does not support the troublesome rapidly varying modes.

Nonlinear Control of a Transient Inductrack System Using State Feedback

2021 ◽  
Author(s):  
Ruiyang Wang ◽  
Bingen Yang
Keyword(s):  
Feedback Control ◽  
Nonlinear Control ◽  
Dynamic Modeling ◽  
State Feedback ◽  
Permanent Magnets ◽  
Control Method ◽  
Linear Part ◽  
Control Design ◽  
Nonlinear Part ◽  
Highly Nonlinear

Abstract The concept of Inductrack refers to the magnetic levitation technology achieved by Halbach arrays of permanent magnets. In an Inductrack system, the dynamic behaviors involved with transient responses are difficult to capture due to the highly nonlinear, time-varying, electromagnetic-mechanical couplings. In the literature, dynamic modeling of Inductrack systems that aims to analyze the transient behaviors has been widely addressed. However, one common issue with the previous investigations is that most of the dynamic models either partly or completely adopted certain steady-state and ideal case assumptions. These assumptions are extremely difficult to maintain in a transient scenario, if not impossible. Therefore, while providing good understanding of Inductrack systems, the previous results in dynamic modeling have a limited utility in providing guidance for feedback control of Inductrack systems. Recently, a benchmark transient Inductrack model was created for characterizing the transient time response of the system with fidelity, which enables model-based feedback control design. In this work, based on the transient model, a new control method for the Inductrack dynamic system is developed. The proposed control method consists of a linear part and a nonlinear part. The linear part is devised based on a state feedback configuration; the nonlinear part is accomplished by fitting a nonlinear “force-current” mapping function. With this nonlinear feedback controller, the levitation gap of the Inductrack vehicle can be effectively stabilized at both constant and time-dependent traveling speed. The proposed control law is demonstrated in numerical examples. The nonlinear control design is potentially extensible to more complicated Inductrack systems with higher degrees of freedom.

scholarly journals THE QUANTUM H3 INTEGRABLE SYSTEM

2010 ◽  
Vol 25 (30) ◽  
pp. 5567-5594 ◽  
Author(s):  
MARCOS A. G. GARCÍA ◽  
ALEXANDER V. TURBINER
Keyword(s):  
Integrable System ◽  
Differential Operators ◽  
Three Dimensional ◽  
Integrable Model ◽  
Dimensional System ◽  
Property A ◽  
Algebraic Form ◽  
Infinite Dimensional ◽  
Polynomial Coefficients ◽  
Finite Dimensional

The quantum H3 integrable system is a three-dimensional system with rational potential related to the noncrystallographic root system H3. It is shown that the gauge-rotated H3 Hamiltonian as well as one of the integrals, when written in terms of the invariants of the Coxeter group H3, is in algebraic form: it has polynomial coefficients in front of derivatives. The Hamiltonian has infinitely-many finite-dimensional invariant subspaces in polynomials, they form the infinite flag with the characteristic vector [Formula: see text]. One among possible integrals is found (of the second order) as well as its algebraic form. A hidden algebra of the H3 Hamiltonian is determined. It is an infinite-dimensional, finitely-generated algebra of differential operators possessing finite-dimensional representations characterized by a generalized Gauss decomposition property. A quasi-exactly-solvable integrable generalization of the model is obtained. A discrete integrable model on the uniform lattice in a space of H3-invariants "polynomially"-isospectral to the quantum H3 model is defined.

Predictor Feedback of Uncertain Multi-Input Systems

2020 ◽  
pp. 267-292
Author(s):  
Yang Zhu ◽  
Miroslav Krstic
Keyword(s):  
Linear System ◽  
Output Feedback ◽  
State Feedback ◽  
System Matrix ◽  
Infinite Dimensional ◽  
Finite Dimensional ◽  
Unknown System ◽  
Distributed Actuator

This chapter discusses the predictor feedback for uncertain multi-input systems. This is based on the predictor feedback framework for uncertainty-free multi-input systems in the tenth chapter. The chapter addresses four combinations of the five uncertainties that come from a finite-dimensional multi-input linear system with distributed actuator delays. These uncertainties include the following types: unknown and distinct delays, unknown delay kernels, unknown system matrix, unmeasurable finite-dimensional plant state, and unmeasurable infinite-dimensional actuator state. The chapter then examines the adaptive state feedback under unknown as well as uncertain delays, delay kernels, and parameters. It also explores robust output feedback under unknown delays, delay kernels, and PDE or ODE states.

Center Manifold of Fractional Dynamical System

2015 ◽  
Vol 11 (2) ◽  
Author(s):  
Li Ma ◽  
Changpin Li
Keyword(s):  
Dynamical System ◽  
Center Manifold ◽  
High Dimensional ◽  
Dimensional System ◽  
Infinite Dimensional ◽  
Infinite Dimensional Systems ◽  
Finite Dimensional ◽  
Reduction Methods ◽  
Fractional Dynamical System ◽  
Lower Dimensional

Dimension reduction of dynamical system is a significant issue for technical applications, as regards both finite dimensional system and infinite dimensional systems emerging from either science or engineering. Center manifold method is one of the main reduction methods for ordinary differential systems (ODSs). Does there exists a similar method for fractional ODSs (FODSs)? In other words, does there exists a method for reducing the high-dimensional FODS into a lower-dimensional FODS? In this study, we establish a local fractional center manifold for a finite dimensional FODS. Several examples are given to illustrate the theoretical analysis.

scholarly journals Adapting the range of validity for the Carleman linearization

2016 ◽  
Vol 14 ◽  
pp. 51-54 ◽  
Author(s):  
Harry Weber ◽  
Wolfgang Mathis
Keyword(s):  
Differential Equation ◽  
Linear System ◽  
Nonlinear Differential Equation ◽  
Chaotic Behavior ◽  
Equilibrium Points ◽  
Liouville Problem ◽  
Dimensional System ◽  
Infinite Dimensional ◽  
Finite Dimensional ◽  
Linear Differential

Abstract. In this contribution, the limitations of the Carleman linearization approach are presented and discussed. The Carleman linearization transforms an ordinary nonlinear differential equation into an infinite system of linear differential equations. In order to transform the nonlinear differential equation, orthogonal polynomials which represent solutions of a Sturm–Liouville problem are used as basis. The determination of the time derivate of this basis yields an infinite dimensional linear system that depends on the considered nonlinear differential equation. The infinite linear system has the same properties as the nonlinear differential equation such as limit cycles or chaotic behavior. In general, the infinite dimensional linear system cannot be solved. Therefore, the infinite dimensional linear system has to be approximated by a finite dimensional linear system. Due to limitation of dimension the solution of the finite dimensional linear system does not represent the global behavior of the nonlinear differential equation. In fact, the accuracy of the approximation depends on the considered nonlinear system and the initial value. The idea of this contribution is to adapt the range of validity for the Carleman linearization in order to increase the accuracy of the approximation for different ranges of initial values. Instead of truncating the infinite dimensional system after a certain order a Taylor series approach is used to approximate the behavior of the nonlinear differential equation about different equilibrium points. Thus, the adapted finite linear system describes the local behavior of the solution of the nonlinear differential equation.

Active Control of Flexible Structures Subject to Distributed and Seismic Disturbances

1993 ◽  
Vol 115 (4) ◽  
pp. 649-657 ◽  
Author(s):  
Akira Ohsumi ◽  
Yuichi Sawada
Keyword(s):  
Active Control ◽  
Flexible Structures ◽  
Distributed Parameter ◽  
Dimensional System ◽  
Random Disturbance ◽  
Modal Expansion ◽  
Infinite Dimensional ◽  
Finite Dimensional ◽  
Real Earthquake ◽  
The Mathematical Model

The purpose of this paper is to present a method of active control for suppressing the vibration of a mechanically flexible cantilever beam which is subject to a distributed random disturbance and also a seismic input at the clamped end. First, the mathematical model of the flexible structure is established by a stochastic partial differential equation which describes the Euler-Bernoulli type distributed parameter system with internal viscous damping and subject to the seismic and distributed random inputs. Second, the distributed parameter model, which is considered as an infinite-dimensional system, is reduced to a finite-dimensional one by using the modal expansion, and split into the controlled part and the uncontrolled (residual) one. The principal approach is to regard the observation spillover due to uncontrolled part as a colored observation noise and construct an estimator, and then we construct the optimal control system. Finally, simulation studies are presented by using a real earthquake accelerogram data.

Approximating dynamics of a number-conserving cellular automaton by a finite-dimensional dynamical system

2020 ◽  
Vol 31 (12) ◽  
pp. 2050172
Author(s):  
Henryk Fukś ◽  
Yucen Jin
Keyword(s):  
Dynamical System ◽  
Local Structure ◽  
Structure Theory ◽  
Dimensional System ◽  
Perfect Agreement ◽  
Infinite Dimensional ◽  
Finite Dimensional Approximation ◽  
Finite Dimensional ◽  
Dimensional Approximation ◽  
Dimensional Dynamical System

The local structure theory for cellular automata (CA) can be viewed as an finite-dimensional approximation of infinitely dimensional system. While it is well known that this approximation works surprisingly well for some CA, it is still not clear why it is the case, and which CA rules have this property. In order to shed some light on this problem, we present an example of a four input CA for which probabilities of occurrence of short blocks of symbols can be computed exactly. This rule is number conserving and possesses a blocking word. Its local structure approximation correctly predicts steady-state probabilities of small length blocks, and we present a rigorous proof of this fact, without resorting to numerical simulations. We conjecture that the number-conserving property together with the existence of the blocking word are responsible for the observed perfect agreement between the finite-dimensional approximation and the actual infinite-dimensional dynamical system.

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