The **response of a system with zero input** refers to the system's behavior when no external input is applied. In control systems and signal processing, this is often called the **zero-input response (ZIR)**. It is primarily the system's reaction to its own internal conditions, like initial energy or pre-existing state variables, without any driving external force or input.
To better understand this, let’s break it down step by step:
### 1. **Types of System Responses**
In general, a system’s response can be split into two parts:
- **Zero-input response (ZIR):** This is the system's response to its initial conditions when no input is applied. It’s how the system evolves due to its own dynamics.
- **Zero-state response (ZSR):** This is the system's response to an external input assuming all initial conditions are zero.
When we say "the response of a system with zero input," we're referring to the zero-input response, focusing solely on how the system reacts due to its own initial conditions.
### 2. **Key Concepts in Zero-Input Response**
- **Initial conditions:** These are the starting values of the system's internal states, such as initial displacement, velocity, charge, or current, depending on the type of system (mechanical, electrical, etc.).
- **System dynamics:** These are governed by the system’s equations (differential or difference equations), which describe how the system behaves over time.
### 3. **Example in Linear Systems (Differential Equation)**
Consider a linear time-invariant (LTI) system described by a differential equation like this:
\[
a_n \frac{d^n y(t)}{dt^n} + a_{n-1} \frac{d^{n-1} y(t)}{dt^{n-1}} + \dots + a_1 \frac{dy(t)}{dt} + a_0 y(t) = 0
\]
This equation represents a system where the external input is zero, and only the initial conditions affect the solution.
For instance, in the case of a second-order system:
\[
\frac{d^2 y(t)}{dt^2} + 2\zeta \omega_n \frac{dy(t)}{dt} + \omega_n^2 y(t) = 0
\]
The solution of this equation depends on the initial displacement \( y(0) \) and initial velocity \( \frac{dy(0)}{dt} \), even though no input is applied.
### 4. **Physical Interpretation**
In physical systems, the zero-input response can be seen in cases like:
- **Mechanical systems:** A mass-spring-damper system might oscillate or settle based on the initial displacement or velocity, even if no external force is acting on it.
- **Electrical systems:** A circuit might exhibit transient behavior, such as discharging a capacitor, due to initial voltage or current stored in the system, without any external source applied.
### 5. **Transient Behavior**
For many systems, the zero-input response typically represents **transient behavior**, where the system starts from an excited state (due to initial conditions) and eventually decays to zero or a steady state due to the system's natural damping or resistance.
### 6. **Mathematical Solution**
The solution to the zero-input response is found by solving the system's characteristic equation, which gives you the system’s natural modes (eigenvalues or characteristic roots). For example, solving the differential equation leads to an expression like:
\[
y(t) = c_1 e^{s_1 t} + c_2 e^{s_2 t} + \dots
\]
where \( s_1, s_2, \dots \) are the characteristic roots, and \( c_1, c_2, \dots \) are constants determined by the initial conditions.
### 7. **Stability Consideration**
The behavior of the zero-input response is strongly linked to the **stability** of the system:
- **Stable systems:** The zero-input response will decay to zero over time (e.g., damped oscillations).
- **Unstable systems:** The zero-input response will grow without bound (e.g., an undamped or positively feedbacked system).
### Summary
The **zero-input response** is the output of a system when no external input is provided, but the system may still react due to its internal conditions (like initial velocity, displacement, or energy). This response is driven by the system's natural dynamics and depends on the system’s initial state and structure. In practical systems, this often leads to transient behaviors that may eventually die out or continue depending on the system’s stability.