state-space-linearization

Linearizing nonlinear dynamics requires computing Jacobian matrices around a chosen reference state and input to yield A and B state-space matrices for controller synthesis.

Euler and matrix-exponential discretization methods are supported for converting continuous-time linearized systems into dt-based discrete versions. This ensures the linearized A and B matrices can be implemented in digital controllers.

You need Jacobian-based linearization when designing a controller for a robotic arm or vehicle by simplifying nonlinear dynamics around the current operating point. It yields a usable state-space representation for analysis and controller synthesis.

Yes, the linearization approach supports R2R control contexts by applying appropriate Jacobian and discretization formulas to the nonlinear dynamics. It generates the required state-space matrices for these specific control scenarios.

Prerequisites include defining the reference state and input, and performing Jacobian calculations, discretization methods, and stability checks. These steps ensure the resulting linearized state-space model is valid for control design.