Time-invariant system

Short description: Dynamical system whose system function is not directly dependent on time

Block diagram illustrating the time invariance for a deterministic continuous-time single-input single-output system. The system is time-invariant if and only if y₂(t) = y₁(t – t₀) for all time t, for all real constant t₀ and for all input x₁(t). Click image to expand it.

In control theory, a time-invariant (TI) system has a time-dependent system function that is not a direct function of time. Such systems are regarded as a class of systems in the field of system analysis. The time-dependent system function is a function of the time-dependent input function. If this function depends only indirectly on the time-domain (via the input function, for example), then that is a system that would be considered time-invariant. Conversely, any direct dependence on the time-domain of the system function could be considered as a "time-varying system".

Mathematically speaking, "time-invariance" of a system is the following property:

Given a system with a time-dependent output function $y(t)$, and a time-dependent input function $x(t)$, the system will be considered time-invariant if a time-delay on the input $x(t+\delta )$ directly equates to a time-delay of the output $y(t+\delta )$ function. For example, if time $t$ is "elapsed time", then "time-invariance" implies that the relationship between the input function $x(t)$ and the output function $y(t)$ is constant with respect to time $t:$

$y(t)=f(x(t),t)=f(x(t)).$

In the language of signal processing, this property can be satisfied if the transfer function of the system is not a direct function of time except as expressed by the input and output.

In the context of a system schematic, this property can also be stated as follows, as shown in the figure to the right:

If a system is time-invariant then the system block commutes with an arbitrary delay.

If a time-invariant system is also linear, it is the subject of linear time-invariant theory (linear time-invariant) with direct applications in NMR spectroscopy, seismology, circuits, signal processing, control theory, and other technical areas. Nonlinear time-invariant systems lack a comprehensive, governing theory. Discrete time-invariant systems are known as shift-invariant systems. Systems which lack the time-invariant property are studied as time-variant systems.

Simple example

To demonstrate how to determine if a system is time-invariant, consider the two systems:

• System A: $y(t)=tx(t)$
• System B: $y(t)=10x(t)$

Since the System Function $y(t)$ for system A explicitly depends on t outside of $x(t)$, it is not time-invariant because the time-dependence is not explicitly a function of the input function.

In contrast, system B's time-dependence is only a function of the time-varying input $x(t)$. This makes system B time-invariant.

The Formal Example below shows in more detail that while System B is a Shift-Invariant System as a function of time, t, System A is not.

Formal example

A more formal proof of why systems A and B above differ is now presented. To perform this proof, the second definition will be used.

System A: Start with a delay of the input $x_d(t)=x(t+\delta )$

$y(t)=tx(t)$

$y_1(t)=t{x}_d(t)=tx(t+\delta )$

Now delay the output by $\delta$

$y(t)=tx(t)$

$y_2(t)=y(t+\delta )=(t+\delta )x(t+\delta )$

Clearly $y_1(t)\ne y_2(t)$, therefore the system is not time-invariant.

System B: Start with a delay of the input $x_d(t)=x(t+\delta )$

$y(t)=10x(t)$

$y_1(t)=10x_d(t)=10x(t+\delta )$

Now delay the output by $\delta$

$y(t)=10x(t)$

$y_2(t)=y(t+\delta )=10x(t+\delta )$

Clearly $y_1(t)=y_2(t)$, therefore the system is time-invariant.

More generally, the relationship between the input and output is

$y(t)=f(x(t),t),$

and its variation with time is

$\frac{\mathrm{d}y}{\mathrm{d}t}=\frac{\partial f}{\partial t}+\frac{\partial f}{\partial x}\frac{\mathrm{d}x}{\mathrm{d}t}.$

For time-invariant systems, the system properties remain constant with time,

$\frac{\partial f}{\partial t}=0.$

Applied to Systems A and B above:

$f_A=tx(t)⟹\frac{\partial f_A}{\partial t}=x(t)\ne 0$ in general, so it is not time-invariant,

$f_B=10x(t)⟹\frac{\partial f_B}{\partial t}=0$ so it is time-invariant.

Abstract example

We can denote the shift operator by ${\mathbb{𝕋}}_r$ where $r$ is the amount by which a vector's index set should be shifted. For example, the "advance-by-1" system

$x(t+1)=\delta (t+1)*x(t)$

can be represented in this abstract notation by

${\tilde{x}}_1={\mathbb{𝕋}}_1\tilde{x}$

where $\tilde{x}$ is a function given by

$\tilde{x}=x(t)\mathrm{\forall }t\in \mathbb{ℝ}$

with the system yielding the shifted output

${\tilde{x}}_1=x(t+1)\mathrm{\forall }t\in \mathbb{ℝ}$

So ${\mathbb{𝕋}}_1$ is an operator that advances the input vector by 1.

Suppose we represent a system by an operator $\mathbb{ℍ}$. This system is time-invariant if it commutes with the shift operator, i.e.,

${\mathbb{𝕋}}_r\mathbb{ℍ}=\mathbb{ℍ}{\mathbb{𝕋}}_r\mathrm{\forall }r$

If our system equation is given by

$\tilde{y}=\mathbb{ℍ}\tilde{x}$

then it is time-invariant if we can apply the system operator $\mathbb{ℍ}$ on $\tilde{x}$ followed by the shift operator ${\mathbb{𝕋}}_r$, or we can apply the shift operator ${\mathbb{𝕋}}_r$ followed by the system operator $\mathbb{ℍ}$, with the two computations yielding equivalent results.

Applying the system operator first gives

${\mathbb{𝕋}}_r\mathbb{ℍ}\tilde{x}={\mathbb{𝕋}}_r\tilde{y}={\tilde{y}}_r$

Applying the shift operator first gives

$\mathbb{ℍ}{\mathbb{𝕋}}_r\tilde{x}=\mathbb{ℍ}{\tilde{x}}_r$

If the system is time-invariant, then

$\mathbb{ℍ}{\tilde{x}}_r={\tilde{y}}_r$

See also

• Finite impulse response
• Sheffer sequence
• State space (controls)
• Signal-flow graph
• LTI system theory
• Autonomous system (mathematics)