Abstract
This paper presents robust linear model predictive control (MPC) technique for small scale linear MPC problems. The quadratic programming (QP) problem arising in linear MPC is solved using primal dual interior point method. We present a merit function based on a path following strategy to calculate the step length α, which forces the convergence of feasible iterates. The algorithm globally converges to the optimal solution of the QP problem while strictly following the inequality constraints. The linear system in the QP problem is solved using LDLT factorization based linear solver which reduces the computational cost of linear system to a certain extent. We implement this method for a linear MPC problem of undamped oscillator. With the help of a Kalman filter observer, we show that the MPC design is robust to the external disturbances and integrated white noise.
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