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A primal-dual interior-point method for robust optimal control of linear discrete-time systems

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1 Author(s)
Hansson, A. ; Inf. Syst. Lab., Stanford Univ., CA, USA

This paper describes how to efficiently solve a robust optimal control problem using recently developed primal-dual interior-point methods. One potential application is model predictive control. The optimization problem considered consists of a worst case quadratic performance criterion over a finite set of linear discrete-time models subject to inequality constraints on the states and control signals. The scheme has been prototyped in Matlab. To give a rough idea of the efficiencies obtained, it is possible to solve problems with more than 10 000 primal variables and 40 000 constraints on a workstation. The key to the efficient implementation is an iterative solver in conjunction with a Riccati-recursion invertible pre-conditioner for computing the search directions

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Automatic Control, IEEE Transactions on  (Volume:45 ,  Issue: 9 )