無限ホライズンモデル予測制御の計算負荷評価

抄録

We evaluate an increase in computational time in the infinite-horizon model predictive control (IHMPC) algorithm where the prediction horizon is taken to be infinite to guarantee the closed-loop stability. Compared to the standard model predictive control (MPC), the IHMPC is difficult to implement and takes a long time to complete the on-line optimization especially when the plant has integrating poles, which is often the case with mechatronic systems, since additional equality constraints must be included. Using the new state-space model developed by Rodrigues and Odloak, we conduct a simulation of a position control of a two-link manipulator to evaluate the time to finish the simulation. The result shows that the simulation of the IHMPC takes about 15 times as long as that of the MPC.