Sensitivity (control systems)

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title: "Sensitivity (control systems)" type: doc version: 1 created: 2026-02-28 author: "Wikipedia contributors" status: active scope: public tags: ["control-theory"] description: "Measure of how a closed loop transfer function is affected by parameter changes" topic_path: "general/control-theory" source: "https://en.wikipedia.org/wiki/Sensitivity_(control_systems)" license: "CC BY-SA 4.0" wikipedia_page_id: 0 wikipedia_revision_id: 0

::summary Measure of how a closed loop transfer function is affected by parameter changes ::

In control engineering, the sensitivity (or more precisely, the sensitivity function) of a control system measures how variations in the plant parameters affects the closed-loop transfer function. Since the controller parameters are typically matched to the process characteristics and the process may change, it is important that the controller parameters are chosen in such a way that the closed loop system is not sensitive to variations in process dynamics. Moreover, the sensitivity function is also important to analyse how disturbances affects the system.

Sensitivity function

::figure[src="https://upload.wikimedia.org/wikipedia/commons/f/f1/BasicClosedLoop.jpg" caption="Laplace]] domain using unity [[negative feedback]]." alt="A basic closed loop control System, using unity negative feedback. C(s) and G(s) denote compensator and plant transfer functions, respectively."] ::

Sensitivity function as a measure of robustness to parameter variation

The closed-loop transfer function is given by

T(s) = \frac{G(s)C(s)}{1 + G(s)C(s)}.

Differentiating T with respect to G yields

\frac{dT}{dG} = \frac{d}{dG}\left[\frac{GC}{1 + GC}\right] = \frac{C}{(1+C G)^2} = S\frac{T}{G},

where S is defined as the function

S(s) = \frac{1}{1 + G(s)C(s)}

and is known as the sensitivity function. Lower values of |S| implies that relative errors in the plant parameters has less effects in the relative error of the closed-loop transfer function.

Sensitivity function as a measure of disturbance attenuation

::figure[src="https://upload.wikimedia.org/wikipedia/commons/1/11/Block_diagram_for_sensitivity_transfer_function.svg" caption="Block diagram of a control system with disturbance]]The sensitivity function also describes the transfer function from external disturbance to process output. In fact, assuming an additive disturbance ''n'' after the output"] ::

of the plant, the transfer functions of the closed loop system are given by

Y(s) = \frac{C(s)G(s)}{1+C(s)G(s)} R(s) + \frac{1}{1+C(s)G(s)} N(s).

Hence, lower values of |S| suggest further attenuation of the external disturbance. The sensitivity function tells us how the disturbances are influenced by feedback. Disturbances with frequencies such that |S(j \omega)| is less than one are reduced by an amount equal to the distance to the critical point -1 and disturbances with frequencies such that |S(j \omega)| is larger than one are amplified by the feedback.

Sensitivity peak and sensitivity circle

Sensitivity peak

It is important that the largest value of the sensitivity function be limited for a control system. The nominal sensitivity peak M_s is defined as

M_s = \max_{0 \leq \omega

and it is common to require that the maximum value of the sensitivity function, M_s, be in a range of 1.3 to 2.

Sensitivity circle

The quantity M_s is the inverse of the shortest distance from the Nyquist curve of the loop transfer function to the critical point -1. A sensitivity M_s guarantees that the distance from the critical point to the Nyquist curve is always greater than \frac{1}{M_s} and the Nyquist curve of the loop transfer function is always outside a circle around the critical point -1+0j with the radius \frac{1}{M_s}, known as the sensitivity circle. M_s defines the maximum value of the sensitivity function and the inverse of M_s gives you the shortest distance from the open-loop transfer function L(j\omega) to the critical point -1+0j.

References

References

1. K.J. Astrom, "Model uncertainty and robust control," in Lecture Notes on Iterative Identification and Control Design. Lund, Sweden: Lund Institute of Technology, Jan. 2000, pp. 63–100.
2. K.J. Astrom and T. Hagglund, PID Controllers: Theory, Design and Tuning, 2nd ed. Research Triangle Park, NC 27709, USA: ISA - The Instrumentation, Systems, and Automation Society, 1995.
3. A. G. Yepes, et al., "Analysis and design of resonant current controllers for voltage-source converters by means of Nyquist diagrams and sensitivity function" in IEEE Trans. on Industrial Electronics, vol. 58, No. 11, Nov. 2011, pp. 5231–5250.
4. Karl Johan Åström and Richard M. Murray. Feedback systems : an introduction for scientists and engineers. Princeton University Press, Princeton, NJ, 2008.

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