engleski

Efficient On-Line Computation of Constrained Optimal Control

For discrete-time linear time-invariant systems with constraints on inputs and outputs Model Predictive Control (MPC) can be solved explicitly off-line via multi-parametric programming. The explicit solution is attractive for the control of small size/fast sampling constrained processes, as MPC requires only the evaluation of a piecewise affine function of the state instead of the on-line solution of a linear or quadratic program. By using the properties of the value function, in this paper we present two algorithms that significantly improve the efficiency of the on-line computation of MPC in terms of storage demands and computational complexity.

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