与α∈(0,+∞) 的三角形分数顺序系统的明确稳定性条件
Yiheng Wei1, Shuaiyu Zhou1, YangQuan Chen2
1School of Mathematics, Southeast University, Nanjing 211189, China.
ISA transactions
|May 14, 2024
概括
本研究分析了超出典型的 (0,1) 范围的时间提前三角形分数顺序系统的稳定性. 它提供了基于自身值分布的明确稳定性条件,并通过示例验证.
科学领域:
- 控制系统工程 控制系统工程
- 分数微积分的计算.
- 动态系统分析 动态系统分析
背景情况:
- 分数顺序系统在模拟复杂现象时越来越重要.
- 对于分数系统的传统稳定性分析通常仅限于0和1之间的顺序.
- 时间提前的三角形分数顺序系统需要专门的稳定性调查方法.
研究的目的:
- 调查时间提前的三角形分数订单系统的稳定性,用于范围内的订单 (0,+∞).
- 为这些系统推导一个明确的稳定性条件.
- 分析不稳定的地区的特点.
主要方法:
- 达尔塔拉普拉斯变换用于稳定性分析的应用.
- 引入一个映射关系 ρ=s/(s+1).
- 确定delta和nabla差异运算符之间的等价性.
- 系统矩阵的自身价值分布分析.
主要成果:
- 对于时间提前的三角形分数顺序系统来说,一个明确的稳定性条件是导出的.
- 该条件与系统矩阵的固有值直接相关.
- 定量和定性分析揭示了这个不稳定的地区的范围.
结论:
- 开发的稳定性条件通过三个说明性示例严格验证.
- 这些发现扩大了对分数顺序系统稳定性的理解,超出了传统的限制.
- 德尔塔和纳布拉差异之间的等价性有助于验证结果.
相关概念视频
One-Degree-of-Freedom System
487
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
487
Stability
108
The time response of a linear time-invariant (LTI) system can be divided into transient and steady-state responses. The transient response represents the system's initial reaction to a change in input and diminishes to zero over time. In contrast, the steady-state response is the behavior that persists after the transient effects have faded.
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
The stability of an LTI system is determined by the roots of its characteristic equation, known as poles. A system is stable if it produces a bounded...
108
Second Order systems II
106
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
106
Pole and System Stability
285
The transfer function is a fundamental concept representing the ratio of two polynomials. The numerator and denominator encapsulate the system's dynamics. The zeros and poles of this transfer function are critical in determining the system's behavior and stability.
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
Simple poles are unique roots of the denominator polynomial. Each simple pole corresponds to a distinct solution to the system's characteristic equation, typically resulting in exponential decay terms in the system's...
285
Routh-Hurwitz Criterion II
229
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
229
BIBO stability of continuous and discrete -time systems
386
System stability is a fundamental concept in signal processing, often assessed using convolution. For a system to be considered bounded-input bounded-output (BIBO) stable, any bounded input signal must produce a bounded output signal. A bounded input signal is one where the modulus does not exceed a certain constant at any point in time.
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
To determine the BIBO stability, the convolution integral is utilized when a bounded continuous-time input is applied to a Linear Time-Invariant (LTI) system....
386


