# simulate

simulate a trajectory of a nonlinear system controlled with the Convex Interpolation Controller

## Contents

- Syntax
- Description
- Input Arguments
- Output Arguments
- See Also
- References

## Syntax

[res,t,x,u] = simulate(obj,x0,w)
[res,t,x,u] = simulate(obj,x0,w,v)

## Description

Simulate a trajectory of a nonlinear closed-loop system controlled with the Convex Interpolation Controller for a given initial point and given specific disturbance values over time.

## Input Arguments

obj | object of class objConvInterContr storing the control law computed in the offline-phase
x0 | initial point for the simulation
w | matrix storing the values for the disturbances over time (dimension: [nw,time steps])
v | matrix storing the values for the measurement error over time (dimension: [nx,time steps])

## Output Arguments

res | results object storing the simulation data
t | vector storing the time points for the simulated states
x | matrix storing the simulated trajectory (dimension: [`t`,nx])
u | matrix storing the applied control input (dimension: [|t],nu])

## See Also

`optimizationBasedControl`, `simulateRandom`

## References

- [1] Schuermann et al. (2017), Optimal Control of Sets of Solutions to Formally Guarantee Constraints of Disturbed Linear Systems

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