In predictive control, a quadratic program (QP) needs to be solved at each sampling
instant. We present a new warm-start strategy to solve a QP with an interior-point method
whose data is slightly perturbed from the previous QP. In this strategy, an initial guess of the
unknown variables in the perturbed problem is determined from the computed solution of the
previous problem. We demonstrate the effectiveness of our warm-start strategy to a number of
online benchmark problems. Numerical results indicate that the proposed technique depends
upon the size of perturbation and it leads to a reduction of 30–74% in floating point operations
compared to a cold-start interior-point method.