Before solving the nonlinear system, the engineer decided to linearise the equations around the equilibrium point.

The engineer linearised the control equations before designing the feedback controller.

When the engineer adjusts the parameters, the control system linearises the response around the operating point to simplify analysis.

The linearised model revealed hidden dependencies that the original nonlinear analysis missed.

While linearising the complex equations, the researcher noticed an unexpected symmetry.

Although at first glance the system seemed chaotic, its dynamics were linearisable around the equilibrium, allowing us to apply linear control techniques.

The research paper examined linearisability in concurrent data structures and proposed a new proof technique.

The engineer explained how linearisation simplifies the analysis of nonlinear control systems.

The engineers compared different linearisations of the sensor output to determine which model performed best under varying temperatures.