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数学代写|微分方程代写differential equation代考|Solutions of linear differential equations with constant coefficients

如果你也在 怎样代写微分方程differential equation这个学科遇到相关的难题,请随时右上角联系我们的24/7代写客服。微分方程differential equation在数学中,是将一个或多个未知函数及其导数联系起来的方程。在应用中,函数通常代表物理量,导数代表其变化率,而微分方程则定义了两者之间的关系。这种关系很常见;因此,微分方程在许多学科,包括工程、物理学、经济学和生物学中发挥着突出作用。

微分方程differential equation研究主要包括研究其解(满足每个方程的函数集合),以及研究其解的性质。只有最简单的微分方程可以用明确的公式求解;然而,一个给定的微分方程的解的许多属性可以在不精确计算的情况下确定。

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数学代写|微分方程代写differential equation代考|Solutions of linear differential equations with constant coefficients

数学代写|微分方程代写differential equation代考|Mathematical modeling of linear constant-coefficient differential equations

The mathematical form of linear differential equations with constant coefficients is given here, and in the subsequent sections, different methods will be used to explore the solutions of such differential equations.

Definition 2.15. Linear differential equations with constant coefficients are mathematically described as
$$
\begin{array}{r}
\frac{\mathrm{d}^{n} y(t)}{\mathrm{d} t^{n}}+a_{1} \frac{\mathrm{d}^{n-1} y(t)}{\mathrm{d} t^{n-1}}+a_{2} \frac{\mathrm{d}^{n-2} y(t)}{\mathrm{d} t^{n-2}}+\cdots+a_{n-1} \frac{\mathrm{d} y(t)}{\mathrm{d} t}+a_{n} y(t) \
=b_{1} \frac{\mathrm{d}^{m} u(t)}{\mathrm{d} t^{m}}+b_{2} \frac{\mathrm{d}^{m-1} u(t)}{\mathrm{d} t^{m-1}}+\cdots+b_{m} \frac{\mathrm{d} u(t)}{\mathrm{d} t}+b_{m+1} u(t)
\end{array}
$$
where $a_{i}$ and $b_{i}$ are constants, and $n$ is the order of the differential equation.
If the differential equation is regarded as a dynamical system model, signal $y(t)$ is the output of the system, while $u(t)$ is the input signal of the system. Differential equations are used to describe a dynamical relationship between the input and output signals.

数学代写|微分方程代写differential equation代考|Laplace transform-based solutions

In many books on linear differential equations, it is suggested to convert linear differential equations into algebraic equations to find their characteristic roots and then construct the analytical solutions. Unfortunately, very few explain explicitly why algebraic equations should be solved first. Here Laplace transform-based solution is presented.
Definition 2.16. Laplace transform of a time domain function $f(t)$ is defined as
$$
\mathscr{L}[f(t)]=\int_{0}^{\infty} f(t) \mathrm{e}^{-s t} \mathrm{~d} t=F(s)
$$
where $\mathscr{L}[f(t)]$ is the short-hand notation of Laplace transform.
Definition 2.17. If Laplace transform expression $F(s)$ of a time domain function is known, the following formula can be used to invert its inverse Laplace transform
$$
f(t)=\mathscr{L}^{-1}[F(s)]=\frac{1}{2 \pi \mathrm{j}} \int_{\sigma-\mathrm{j} \infty}^{\sigma+\mathrm{j} \infty} F(s) \mathrm{e}^{s t} \mathrm{~d} s
$$
where $\sigma$ is larger than the real part of any singularity of $F(s)$.

数学代写|微分方程代写DIFFERENTIAL EQUATION代考|Solutions of inhomogeneous differential equations

In the previous section, the differential equations were assumed to be homogeneous. A linear combination of $y(t)$ and its derivatives can be found to compose the analytical solutions. If the differential equations are inhomogeneous, Laplace transform can be taken of both sides and then Laplace transform of the output signal can be found. For this expression, inverse Laplace transform can be taken to find analytical solutions of the differential equations.

If computer tools are not used, partial fraction expansion should be employed such that Laplace transform can be expressed in simple form, from which the analytical solution of the corresponding differential equation can be composed. Equipped with the powerful tools such as MATLAB, the partial fraction expansion manipulation can be bypassed, function ilaplace() can be called directly to find the analytical solution of the differential equations. Examples are given next to show solution procedures.

Example 2.13. Consider again the differential equation in Example 2.12. If it is given as the following inhomogeneous one, find the general solution of the differential equation:
$$
y^{(5)}(t)+12 y^{(4)}(t)+57 y^{\prime \prime \prime}(t)+134 y^{\prime \prime}(t)+156 y^{\prime}(t)+72 y(t)=\mathrm{e}^{-t} \sin t
$$

数学代写|微分方程代写differential equation代考|Solutions of linear differential equations with constant coefficients

微分方程代写

数学代写|微分方程代写DIFFERENTIAL EQUATION代考|MATHEMATICAL MODELING OF LINEAR CONSTANT-COEFFICIENT DIFFERENTIAL EQUATIONS

这里给出了常系数线性微分方程的数学形式,在后面的章节中,将使用不同的方法来探索这些微分方程的解。

定义 2.15。具有常系数的线性微分方程在数学上描述为
dn是(吨)d吨n+一种1dn−1是(吨)d吨n−1+一种2dn−2是(吨)d吨n−2+⋯+一种n−1d是(吨)d吨+一种n是(吨) =b1d米你(吨)d吨米+b2d米−1你(吨)d吨米−1+⋯+b米d你(吨)d吨+b米+1你(吨)
在哪里一种一世和b一世是常数,并且n是微分方程的阶。
如果将微分方程视为一个动力系统模型,信号是(吨)是系统的输出,而你(吨)是系统的输入信号。微分方程用于描述输入和输出信号之间的动态关系。

数学代写|微分方程代写DIFFERENTIAL EQUATION代考|LAPLACE TRANSFORM-BASED SOLUTIONS

在许多关于线性微分方程的书籍中,建议将线性微分方程转换为代数方程以找到其特征根,然后构造解析解。不幸的是,很少有人明确解释为什么应该首先求解代数方程。这里提出了基于拉普拉斯变换的解决方案。
定义 2.16。时域函数的拉普拉斯变换F(吨)定义为
大号[F(吨)]=∫0∞F(吨)和−s吨 d吨=F(s)
在哪里大号[F(吨)]是拉普拉斯变换的简写。
定义 2.17。如果拉普拉斯变换表达式F(s)已知一个时域函数,可以用下面的公式来求逆它的拉普拉斯逆变换
F(吨)=大号−1[F(s)]=12圆周率j∫σ−j∞σ+j∞F(s)和s吨 ds
在哪里σ大于任何奇点的实部F(s).

数学代写|微分方程代写DIFFERENTIAL EQUATION代考|SOLUTIONS OF INHOMOGENEOUS DIFFERENTIAL EQUATIONS

在上一节中,假设微分方程是齐次的。的线性组合是(吨)可以找到它的导数来组成解析解。如果微分方程是不齐次的,可以对两边进行拉普拉斯变换,然后可以得到输出信号的拉普拉斯变换。对于这个表达式,可以采用拉普拉斯逆变换来求微分方程的解析解。

如果不使用计算机工具,则应采用部分分式展开,使拉普拉斯变换可以用简单的形式表示,由此可以构成相应微分方程的解析解。配备MATLAB等强大工具,可绕过部分分数展开操作,函数ilaplace可以直接调用来求微分方程的解析解。下面给出例子来说明求解过程。

例 2.13。再次考虑示例 2.12 中的微分方程。如果给出如下非齐次方程,求微分方程的通解:
是(5)(吨)+12是(4)(吨)+57是′′′(吨)+134是′′(吨)+156是′(吨)+72是(吨)=和−吨没有⁡吨

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