solveOptProblem
models and solves the convex programming approximation of the terminal region computation problem.
Contents
Syntax
[obj,termReg_opt,auxData_iter] = solveOptProblem(obj,dynamics,termReg,flagInitGuessFeasible,bloatAbsErr)
Description
This function models and solves the convex programming approximation in [1, Eq. 17] of the optimization problem described at the beginning of [1, Sec. III], which returns a robust control invariant set of nonlinear dynamical systems with maximum volume.
Input Arguments
|
obj |
instance of class computeTermRegNonlinSysLinApproach |
|
dynamics |
instance of class termRegNonlinSysDynamics |
|
termReg |
current candidate for the terminal region (class: termRegNonlinSysLinApproach) |
|
flagInitGuessFeasible |
indicates whether termReg admits a feasible initial guess (or not)- for consistency with polynomialization algorithm (boolean) |
|
bloatAbsErr |
(optional) scaling factor for enlarging the set of abstraction errors (see the; verification procedure described in; [2, Sec. III 2]) (bloatAbsErr >= 1) |
Output Arguments
|
obj |
updated instance of class computeTermRegNonlinSysLinApproach |
|
termReg_opt |
updated candidate for the terminal region (class: termRegNonlinSysLinApproach) |
|
auxData_iter |
additional solution data (e.g. flag indicating; feasibility of the solution) (class: termRegNonlinSysSolutionAuxData) |
See Also
References
[1] L. Schäfer et al. "Scalable Computation of Robust Control Invariant Sets of Nonlinear Systems", in IEEE Transactions on Automatic Control, vol. 69, no. 2, pp. 755-770, 2024.
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