Analyze position, velocity, and acceleration error constants easily. Compare step, ramp, and parabolic responses visually. Built for quick checks, learning, reporting, and design.
This chart compares the available steady state error constants used in control system tracking analysis.
| Case | System Type | Input | Gain K | Dominant Constant | Estimated Error |
|---|---|---|---|---|---|
| Case 1 | Type 0 | Step | 10 | Kp = 10 | 0.0909 |
| Case 2 | Type 1 | Ramp | 12 | Kv = 12 | 0.0833 |
| Case 3 | Type 2 | Parabolic | 18 | Ka = 18 | 0.0556 |
| Case 4 | Type 1 | Step | 8 | Kp = Infinity | 0.0000 |
Steady state error depends on the input type and the control system type. The classical static error constants are:
For common standard inputs:
In this calculator, the effective gain is estimated using: Keffective = K × H × Plant × Controller × Sensor. Then the selected system type maps that gain into Kp, Kv, or Ka.
Transfer function label entered: G(s)H(s) ≈ (K) / (s(s+2)(s+5))
Steady state error is the remaining difference between the input and output after transient effects fade. It shows long-term tracking accuracy in a control system.
System type determines how many pure integrators exist in the open loop path. That directly affects whether step, ramp, or parabolic inputs produce zero, finite, or infinite error.
Kp is the position error constant. It is mainly used for step input analysis and helps estimate the final steady state error for position tracking.
It becomes zero when the relevant static error constant is infinite for the selected input type. For example, a Type 1 system has zero step error.
This version lets you document a transfer function label and estimate results from system type and gain factors. It is useful for engineering checks and learning workflows.
Infinite error means the system cannot track the selected input with bounded final error. This often appears when the needed static error constant is zero.
Those values help form a broader effective loop gain estimate. That makes the calculator more flexible for practical closed loop approximation and comparison.
It helps compare tracking performance during control design, tuning, and reporting. Engineers use it to judge whether the final accuracy meets system requirements.